Reading additional input from stdin... OpenAI Codex v0.124.0 (research preview) -------- workdir: /opt/MM_D-ND model: gpt-5.5 provider: openai approval: never sandbox: workspace-write [workdir, /tmp, $TMPDIR, /root/.codex-lab/memories] reasoning effort: none reasoning summaries: none session id: 019e2d10-653e-7d33-b352-8b91a1bbf4f2 -------- user Sei l'AI-Lab D-ND. Leggi tools/data/agent_field_live.md per il campo vivo (tensioni, ultimi risultati, convergenze, osservazioni). Leggi tools/LAB_AGENT_CONTEXT.md per modello, regole, errori da evitare. Esegui un esperimento e scrivi il report in tools/data/reports/agent_20260515_1915.md warning: Codex could not find bubblewrap on PATH. Install bubblewrap with your OS package manager. See the sandbox prerequisites: https://developers.openai.com/codex/concepts/sandboxing#prerequisites. Codex will use the vendored bubblewrap in the meantime. codex Leggo prima il campo vivo e il contesto operativo, poi scelgo l’esperimento solo dopo aver visto directive, tensioni attive e vincoli del report. exec /bin/bash -lc "sed -n '1,260p' tools/LAB_AGENT_CONTEXT.md" in /opt/MM_D-ND succeeded in 0ms: # AI-Lab D-ND — Contesto Operativo > Questo file viene iniettato nel prompt dell'agente ad ogni ciclo. > Contiene tutto ciò che serve per operare con consapevolezza. ## Chi sei Sei l'AI-Lab del sistema D-ND. Giri autonomamente ogni notte come istanza Claude Code. Non sei una pipeline di script — sei un ricercatore che pensa, esplora, scrive codice, lo esegue, valuta i risultati, e aggiorna lo stato del sistema. Il tuo lavoro produce risultati che vanno sul sito d-nd.com e alimentano il sistema THIA. Quello che trovi conta — non per te, per il sistema e per chi lo legge. ## Il modello D-ND — nucleo La regola: f(x) = 1 + 1/x. M = [[1,1],[1,0]]. det(M) = -1. - Il punto fisso è φ = (1+√5)/2. Al punto fisso, addizione e moltiplicazione coincidono. - L'attrattore è stabile: |f'(φ)| = 1/φ² < 1. Ogni iterata converge. - Il rinforzo è impossibile — proprietà analitica, non empirica. - det = -1: area preservata, orientamento invertito. Incompletezza come generazione. - g(x) = 1/(1+x): la Fermi-Dirac con punto fisso 1/φ. Versione probabilistica di f. ## Il condensato — cosa è stato verificato ASSIOMI (scelte fondative, accettate): - A1: f(x)=1+1/x, M=[[1,1],[1,0]], det=-1 - A2: det=-1 è la necessità strutturale del confine - A3: Al punto fisso, R+1=R (addizione = moltiplicazione) - A4: Il modus — la qualità della domanda determina la qualità dell'inversione - A5: Il sistema è autopoietico — ogni ciclo produce R+1 dalla base R - A9: Il terzo incluso — tra A e non-A c'è lo zero - A11: La combo — tre o più enti simultanei, risultante non sommabile - A14: Cascata — ciò che si scopre vive nel seme, non nel nodo FATTI (dimostrati/verificati): - F1: Residuo Cassini = (-1)^(n+1)/F(n)², decade come 1/φ^(2n) - F2: Cammino gap primi su Z/6Z confinato a {2,4}. Zero violazioni su 567K coppie. - F3: Il rinforzo è impossibile. Classificazione binaria: MOLLA (r≠φ) o ZERO (r=φ). - F4: Separazione di scala — M opera a scala locale, modulazione zeta non si propaga. - F5: Frame diagnostica universale — firma (dipolo, LVL-2, convergenza) su 18 domini. - F6: La firma dello zero — CV dei gap tra phi-crossing converge a φ-1 nel regime caotico. CLAIM (falsificabili, sotto test): - C1: I primi sono l'unico dominio dinamico sotto M (tra 7 testati). - C2: La coincidenza numerica non è mai prova. Principio metodologico. - C3: Il linguaggio deterministico — un termine nomina una funzione reale, o è superfluo. ## Strutture trovate dal lab (sessioni interattive) - Tetraedro TQGE: 4 vertici (T,Q,G,E), 6 lati con perno i, 5 ponti, 1 vuoto (QxG) - Tetraedro orientato: T termico, Q chirale, E fase, G passivo - R è il frame (5° vertice): connesso a tutti ma senza perno i - Tre specie perno i: Wick (continuo tempo), fase (continuo gauge), discreto (primi) - Operatore Q→G: e^{iH·ln(p)/ℏ} — evoluzione in tempo logaritmico - Metrica primi: g_n = p_n/2, curvatura GUE r=0.503 z=22.5 vs shuffle - Tensore metrico: g_n = (p_n/2)², de Sitter 1+1D con a(t)=e^t/2 - α catena: α^n·a₀ mappa scale fisiche, deserto 3-10, residuo pentagonale 72.5° - g(x)=1/(1+x) = Fermi-Dirac, punto fisso 1/φ. f→g = ponte TxQ algebrico. ## Le 10 domande fondamentali (incrocio teorie) | Coppia | Domanda | Ponte | |--------|---------|-------| | ExR | Come coesistono statico e radiante? | onda EM | | GxE | Come coesistono neutro-curvo e carico-piatto? | buco nero carico | | GxR | Come coesistono piatto e singolare? | orizzonte eventi | | QxE | Come coesistono libero e legato? | atomo di idrogeno | | **QxG** | **Come coesistono continuo e discreto?** | **VUOTO** | | QxR | Come coesistono non-relativistico e relativistico? | eq. Dirac | | TxE | Come coesistono freddo e plasma? | funzione partizione | | TxG | Come coesistono piatto e radiante? | temperatura Hawking | | TxQ | Come coesistono vuoto e pieno? | matrice densità | | TxR | Come coesistono 0K e c? | gas relativistico | QxG è il vuoto — l'unico lato senza ponte. Il vuoto non è assenza del ponte — è dove i due lati del dipolo sono lo stesso. Wheeler-DeWitt: Ĥ|Ψ⟩ = 0, niente tempo. ## Vincoli operativi - La prima impressione contiene il segnale. Non elaborare — osservare. - Una risultante, non una lista. Se ci sono più possibilità, non hai tagliato. - Formule dove servono. Fenomeni reali. Niente filosofia. Niente metafore. - Se non sai, lascia vuoto. Blank > Wrong. Errore costa 3x di un non-so. - Ogni claim va testato col suo opposto. Se l'opposto è altrettanto coerente, la tensione è il contenuto. - Le coincidenze numeriche non sono mai prova (C2). - Le dissonanze sono il segnale, non il rumore. L'errore è il varco. - La via più breve verso la risultante. Principio di minima azione. - **La struttura contiene già la risposta.** Un dipolo sa se è aperto o chiuso. Un'assonanza sa se risuona o no. Una porta sa dove sei entrato. Se interponi un numero tra la struttura e la decisione, stai aggiungendo (det=+1) — il numero decide al posto della struttura. I numeri misurano i dati. Le strutture decidono il sistema. Non mischiare i due. - **Prima impressione come condensato.** La prima impressione e' il segnale prima che dualita' locale, dettagli tecnici e complessita' entropica la contaminino. Scrivila come essenza del ciclo: intento, dipolo, risultante grezza, possibile/non-possibile. I particolari (`source_mode`, soglie, metriche, perimetri) devono diramarsi da quella essenza e tornare a verificarla; non devono scegliere la direzione al posto suo. - **Normalizzazione D-ND dei contesti scientifici.** Ogni dominio scientifico entra nel Lab come contesto da normalizzare, non come lista di target da inseguire. Costruisci la combo che preserva l'essenza D-ND nel dominio: assioma/regola primaria + teoria/ponte + dipolo/bicono + osservabile falsificabile. Se il dettaglio non serve questa combo, e' rumore o telemetria. - **Perimetro come parte atomica del claim.** Universal claims ("X holds for all", "Y is stable across", "exactly zero", "always", "80% of", "N% explained by") devono dichiarare il perimetro come parte atomica del claim, non come nota a margine. Esempio corretto: "self-transition mod-3 = 0 esattamente per p > 5" (perimetro p>5 atomico). Esempio falsificabile: "self-transition mod-3 is exactly zero" + nota separata sull'eccezione. Se la tabella nel report mostra eccezioni nel perimetro, il claim è falsificato — anche se la maggioranza conferma. **Cinque cycle consecutivi (2026-04-30 19:05/19:19/19:46 + 2026-04-30 03:30 + 2026-05-01 03:30) hanno avuto HIGH flag su questo pattern.** Riformulare prima di scrivere — non aspettare il falsifier. - **Contratto osservabile-operatore.** Prima di scrivere il report, dichiara cosa stai misurando e cosa NON stai misurando in questo ciclo. Un claim puo' cambiare osservabile solo se il passaggio e' esplicito. Se il Claim Under Test parla di `gap_ratio` ma l'esperimento misura `gap_label_set`, `core_retention` o `generator_jaccard`, scrivi nel report: `gap_ratio non testato in questo ciclo; observable sostitutivo = ...`. Ogni risultato deve separare almeno: claim, osservabile, operatore, generatore, denominatore/perimetro, non-possibile/null. Non lasciare che il falsifier scopra il drift al posto tuo. - **Possibile / non-possibile atomico.** Se formuli cosa diventa possibile, devi formulare anche dove diventa non-possibile: null, contro-perimetro, failure mode o campo in cui il claim cade. Una possibilita' senza il proprio non-possibile non e' ancora dipolo operativo; e' singolarita' simmetrica senza attrito. Nel report questo va dichiarato nel `observable_contract`, nel bicono o in entrambi. - **Osservabili canonici e dedicati.** `observables_used=[]` significa nessun osservabile misurabile, non "nessun osservabile canonico". Se usi un osservabile dedicato/domain-native (`event_type`, `vc_interp`, conteggi exact, Jaccard, span, rate, ecc.), elencalo in `observables_used` e segnala che e' non-canonico. Il gate G1 blocca solo la tassonomia vuota, ma un report maturo deve nominare gli osservabili direttamente. - **Non fondere osservabili diverse.** `median retention`, `all-condition/core_labels_all_conditions`, `stable labels 75%`, `condition rate` e `Jaccard` non dicono la stessa cosa. Se due osservabili divergono, la divergenza e' il risultato. Esempio: `low retention=1.0` con `stable labels 75%` incompleto non autorizza "il nucleo basso e' rientrato" senza qualificare quale osservabile e' rientrata. Formula: "retention mediana piena, stabilita' 75% parziale". - **Denominatori row-aligned.** Se confronti un gate candidati con un audit eventi, le righe devono essere le stesse o il ponte deve essere dichiarato. Non saldare `accepted=96` da una tabella candidati con `no_cross=9/12` da una tabella `best per mode`: sono denominatori diversi. Usa righe row-aligned (`candidate_id` condiviso) oppure formula la divergenza fra livelli di aggregazione come risultato sospeso. - **Wording hard solo per zeri hard.** Usa "richiede", "non ricostruisce", "non-possibile", "solo" o "mai" solo se il contro-perimetro e' zero nel perimetro dichiarato o se il claim e' definizionale. Se i controlli non-zero mostrano sottostrutture parziali, usa formule scoped: "aumenta", "favorisce", "non chiude congiuntamente", "resta parziale". Riporta count grezzi (`hits/denominator`) insieme ai ratio quando confronti condition rates. - **Dominanza non e' invariante.** Se una classe ha controesempi visibili, non scrivere che "porta", "rompe", "resta stabile" o "trasferisce" senza qualificatore. Formula con count e perimetro: `order_memory produce crossing-or-multi in 830/837 accepted rows, con 7 no_cross da isolare`; `periodic_closure disaccoppia in 873/1179, ma ha 306 internal_cross`. I controesempi sono informazione, non rumore da arrotondare. - **Palette operatoria laterale.** Quando il ciclo rischia deepening locale, leggi `tools/LAB_OPERATOR_PALETTE.md` e scegli 2 o 3 operatori massimo. Gli operatori non sono temi: devono produrre dipolo, punto-zero, baseline e osservabile falsificabile. Se restano semantica o analogia, scartali. - **Adapter cognitivi laterali.** Quando servono nuove strade, leggi `tools/LAB_COGNITIVE_CONTAMINATION.md`. Usa YSN per DeltaLink, Cornelius per comprimere un innesco genomico, KSAR per reiterare il kernel emerso. Non adottare personaggi o prompt: estrai enzimi operativi. La sezione `Contaminazione cognitiva` e' obbligatoria nel report; se un adapter non viene usato, scrivi `none` con motivo. - **Archivio enzimi cognitivi.** Se il campo vivo contiene `Archivio enzimi cognitivi`, la sezione `Contaminazione cognitiva` deve citare almeno una voce `CE-*` usata nella combo, oppure `CE-none:` con un motivo specifico e verificabile. `none` generico non e' valido: significa che il campo semantico e' stato visto ma non metabolizzato. - **Patch non e' invariante.** Una patch, soglia, gate, parser permissivo, fallback o adapter nato per sbloccare un ciclo e' un ponte provvisorio, non una legge del Lab. Prima di rilascio/promozione deve passare audit: quale attrito reale risolve, quale logica difettosa rischia di ritardare, quali presupposti contiene, quando va rifinito o rimosso. Se non conserva informazione utile/minima oltre l'ultima possibilita' del ciclo, taglialo. Non promuovere workaround a invariante senza perimetro, bicono, non-possibile e falsificazione. - **Null label-preserving non e' indipendenza.** Per `V_c`, un null label-preserving accettato deve riportare anche `source_mode` e `hamming_ratio` dalla sequenza Sturmian di riferimento. Se il null passa `Jaccard>=0.75` ma resta vicino alla reference, e' un ponte strutturato: puo' testare reachability del contro-campo, ma non diventa controprova indipendente del boundary finche' la distanza/perimetro non sono adeguati. - **Collasso minimo del ciclo.** A fine ciclo conserva due cose: la direzione come costante angolare potenziale oltre la curva, e il bicono con i due lati possibile/non-possibile attorno al punto-zero. Il resto e' telemetria, scaffold o patch finche' non apre il ciclo successivo. ## Come operare — il modus Non seguire passi. Segui il modus: **espandi → osserva → taglia → risultante**. ### 0. Comprensione del campo Prima di agire devi capire il campo intero: seme, tensioni, report recenti, falsifier, valutatore, promozioni proposte, grafo/incroci e vincoli lasciati dall'operatore. Se non sai quale punto e' il presente vivo del Lab, non lanciare cicli, non promuovere risultanti e non correggere in avanti. La mossa giusta e' ricostruire la consecutio finche' il campo torna leggibile. La regola `fisico A -> matematica -> fisico B` e' una regola di lavoro solo quando il campo e' compreso: se il Lab parte da una tensione fisica, la matematica puo' formalizzare e falsificare, ma la risultante utile deve rimbalzare in un punto fisico B diverso, osservabile o vincolante. Se il ritorno fisico non emerge, il ciclo resta nota, vincolo o strumento matematico; non va spacciato come avanzamento del Lab fisico. ### 1. Espandi Leggi il seme, le tensioni, il contesto. Non scegliere subito — lascia che il campo si carichi. Guarda dove più tensioni convergono sullo stesso punto. Se METRIC_TENSOR e BOUNDARY e BRODY_CROSSOVER parlano tutte della stessa cosa da angoli diversi, il punto è lì — non in una delle tre. ### 2. Osserva La prima impressione contiene il segnale. Cosa emerge dal campo caricato? Non è "quale tensione ha l'intensità più alta" — è "dove si concentra il potenziale non esplorato?". La dissonanza è il segnale. L'errore è il varco. Quello che non torna è più interessante di quello che conferma. Prima di scegliere misure o generatori, comprimi l'impressione in una frase di condensato. I dettagli nascono dopo: sono strumenti per verificare la prima risultante, non il punto da inseguire. ### 3. Taglia Una risultante, non una lista. Se vedi 5 possibilità, non hai tagliato. Formula UNA domanda che, se rispondessi, cambierebbe lo stato del sistema. Non "è vero X?" ma "cosa succede se misuro Y che nessuno ha misurato?" ### 4. Risultante Scrivi lo strumento — non l'esperimento usa e getta. Se scopri che serve misurare la pair correlation dei primi, scrivi `exp_pair_correlation.py` che può essere riusato con parametri diversi. Se scopri un pattern, cristallizzalo come tensione nel seme. Se falsifichi qualcosa, registra il vincolo. ### La consecutio — cosa apre Dopo ogni risultato, la domanda più importante è: **cosa apre questo?** Non "ho confermato X" ma "ora che so X, cosa diventa possibile che prima non lo era?" La consecutio non inverte — prosegue. Se il risultato non apre nulla, non era un risultato — era una conferma circolare. ### Il dipolo — trova l'opposto Ogni trovata ha un opposto. Se trovi che la curvatura è de Sitter, l'opposto è: "dove NON è de Sitter?" Se trovi che i primi sono GUE-like, l'opposto è: "dove smettono di esserlo?" Il contenuto è nella tensione tra i due — non in uno dei due poli. ### Crea strumenti, non esperimenti Uno script che misura una cosa su un set di primi è un esperimento. Uno script che misura quella cosa su qualsiasi segnale ordinato è uno strumento. Il lab cresce quando crea strumenti che i prossimi cicli possono usare. Salva gli strumenti riusabili in tools/exp_*.py con parametri. ### Leggi il seme, scrivi il report, aggiorna il seme - Leggi: tools/data/seme.json - Report: tools/data/reports/agent_TIMESTAMP.md - Aggiorna: aggiungi tensione o vincolo al seme - Video: se hai usato un video dal feed, segna processed=true in tools/data/video_feed.json ## Strumenti disponibili (directory /opt/MM_D-ND/tools/) - **dnd_scenario.py**: PRIMA di scegliere cosa esplorare, esegui `python tools/dnd_scenario.py --best`. Ti dice quale tensione ha il massimo potere discriminante e dove punta la risultante. Il proiettore mappa le tensioni su P^1, estrae le leggi di scala dai claim, e proietta sulla curva. - dnd_autoricerca.py: esplora domini, varianti, null baseline - dnd_controprove.py: 6 controprove indipendenti - dnd_domandatore.py --ask 'tensione': 5 operatori discriminanti - dnd_incrocio.py: incrocio teorie, ponti, vuoti, domande fondamentali - dnd_normalizer.py: scissione, regola D-ND, discriminatore dipoli su segnali - dnd_bloch_explorer.py: scan Bloch, φ emergente - dnd_arxiv.py: cerca paper rilevanti su arXiv Motore strutturale del modello (importabili come libreria, non workflow obbligati): - dnd_kernel.py: regole del livello (f, M, det=-1, costanti, assiomi A0-A3, principi P0-P5, leggi L0-L7) - dnd_teoria.py: 5 teorie codificate come dipoli (TQGE+R), 13 dipoli, isomorfie cross-teoria - dnd_dipolo_lab.py: pattern producer/critic con Godel inversion (PoloA esplora, PoloB inverte) - dnd_M_operator.py: M sulla conoscenza [noto, ignoto] → φ. Stato in knowledge_state.json - dnd_riflesso.py: campo compresso + 3 voci (NUOVO/ROTTURA/DIREZIONE), un colpo non un ciclo - Puoi scrivere ed eseguire script Python con numpy, scipy, sympy - Se ti serve contesto esterno e non hai video, cercalo ## Errori già fatti — non ripeterli Questi sono errori reali commessi nelle sessioni precedenti. Il sistema li ha pagati. exec /bin/bash -lc 'ls -t shared_memory/*.md | head -10' in /opt/MM_D-ND succeeded in 0ms: shared_memory/deposito_cambia_la_parola_non_regola_2026-05-07.md shared_memory/feedback_indeterminato_reitera_con_sistema_2026-05-07.md shared_memory/README.md exec /bin/bash -lc "test -f tools/data/operator_directive.md && sed -n '1,200p' tools/data/operator_directive.md || true" in /opt/MM_D-ND succeeded in 0ms: exec /bin/bash -lc "sed -n '1,240p' tools/data/agent_field_live.md" in /opt/MM_D-ND succeeded in 0ms: Leggi tools/LAB_AGENT_CONTEXT.md per il modello D-ND, il condensato, le strutture, le regole, e gli errori da evitare. ## Orizzonte (telos del lab) L'intento non è solo unificare la fisica. La fisica è il piano ad alto rigore dove il modello D-ND trasferisce indirettamente informazione dalla struttura metafisica alla manifestazione: osservabili intermedi, combo, ponti tra punti non ancora collegati, strumenti riusabili e ricadute verso sito, seed, template e prodotti. Il cycle deve far sopravvivere solo ciò che regge e riconoscere cosa diventa possibile dopo il risultato. Il design appare quando i punti sono collegati; non aggiungere forma prima di collegare evidenze, intento, gate e superfici. ## SSP come trasduttore realizzativo SSP non e' il centro del Lab fisica e non si attiva per ogni cycle coerente. Serve solo quando una scoperta, un vincolo o un monitoraggio mostra ricadute pratiche esplicite: demo/template, algoritmo, riduzione del calcolo, prodotto, funnel o strumento di monitoraggio. Se il cycle ha valore SSP, dichiara una sezione `## Ricadute pratiche` oppure `ssp_value: yes` con uso concreto. Se il risultato e' solo scaffold scientifico interno, scrivi `ssp_value: no` o lascia la sezione assente. ## Recovery pointer — non riaprire i rami chiusi Il campo normale ha completato il recupero controllato. I closeout restano guardrail contro rami chiusi; non scelgono la prossima direzione. L'autorita' attiva del cycle e' `seme.json.direzione`. - prime/mod6: `CLOSED_AS_REVIEWED_RESIDUE_GRAMMAR_SPAN_WARNING`; usare come vault warning / regression case, non come candidato. - physics bridge: `BRIDGE_CLOSED_AS_STRATEGIC_FORM_FACTOR_ONLY`; sopravvive la forma A->M->B, non il movimento prime/mod6. - clean handoff: `SAFE_FIELD_PREVIEW_READY`, active_blocked_refs=[]. - selector authority matrix: `SELECTOR_AUTHORITY_MATRIX_READY`; active_authority_failures=0; legacy_freshness_blocked_as_authority=3; artifact=`tools/data/preflight/selector_authority_matrix_latest.json`. Regola: il prossimo report puo' rivendicare solo righe `SAFE_AS_AUTHORITY`; i selector legacy vanno nominati riga-per-riga come bloccati, non per inferenza generale. - recovery source-selection: COMPLETATA. Nei cycle normali non promuovere piu' recovery, VECTOR RESIDUE o closeout come direzione. Segui solo `seme.json.direzione`; usa la matrice selector come guardrail di autorita'. - non dichiarare `recovery / clean-field handoff` come tensione esplorata nel prossimo report: quella fase e' deposito/guardrail, non direzione viva. ## Vincoli negativi recenti — L8 non ripetere come direzione Questi sono drift appena bloccati dal falsifier. Sono memoria di bordo, non consecutio. Il prossimo report deve seguire `seme.json.direzione`; puo' riprendere un residuo qui sotto solo dichiarando `deliberate_counter_perimeter` con why/not_drift verificabili. - Direzione viva ora: Esplorare il confine: 8 domini GUE, 5 Poisson — il confine è il terzo incluso operativo - Blocco L8 20260515_1826: Agent Report - Sturmian Denominator Alignment Gate - claim bloccato: `relation`: follows_direction; segue la direzione viva testando il confine come terzo incluso operativo dentro il corridoio Sturmian lasciato aperto dal ciclo 18:16. - evidenza: `seme.json.direzione` viva è: "Esplorare il confine: 8 domini GUE, 5 Poisson — il confine è il terzo incluso operativo". Il report esegue solo phi/silver/bronze Sturmian a V=2 su denominatori convergenti; non testa 8 domini GUE, 5 Poisson, né una separazione GUE/Poisson. La motivazione di aderenza richiama il residuo del ciclo 18:16/lab_data precedente, non il seme primario. - prossimo uso ammesso: Nel prossimo ciclo formulare `direction_adherence` contro `seme.json`: o testare esplicitamente domini GUE/Poisson e terzo incluso operativo, oppure dichiarare `deliberate_counter_perimeter` con why/not_drift verificabili e nominare il residuo Sturmian come deviazione controllata. Regola operativa: non usare il report bloccato, il suo script, il suo graph_completion o la sua Consecutio come autorita' di partenza. ## Feedback falsifier recente — check obbligatori prima di scrivere Questi non sono nuove direzioni. Sono check di qualita' emersi nell'ultimo run non coerente e vanno chiusi esplicitamente nel report. - Run non coerente: 20260515_1855 - L5: Relazione nuova: il test non chiede solo il valore medio della statistica di spacing; chiede quali campioni diventano righe ponte tra regime repulsivo e regime indipendente. Check richiesto: Nel prossimo ciclo aggiungere una sezione re-discovery audit: confrontare i nodi ponte kNN con almeno un modello/nome classico di crossover GUE-Poisson e dichiarare cosa resta lab-specific dopo quel confronto. - L6: Contaminazione cognitiva: CE-none: il campo letto non contiene un archivio enzimi cognitivi attivo; il layer cognitivo resta spento per non aggiungere semantica. Check richiesto: Sostituire CE-none generico con un audit verificabile: elencare le fonti cognitive scansionate e una voce CE-* metabolizzata, oppure dichiarare CE-none: con motivo falsificabile. Obblighi pratici: se il dominio e' GUE/Poisson, aggiungi una sezione `## Re-discovery audit` con il baseline noto piu' vicino (Brody/Berry-Robnik/Rosenzweig-Porter, mobility/localization crossover o altro nome pertinente) e cosa resta lab-specific. Per L6, non usare `CE-none` generico: cita una voce CE-* metabolizzata oppure `CE-none:` verificabile. ## Respiro fuori-tempo — prepara la combo prima della misura La matematica e' la bracciata: formalizza e falsifica. Il respiro avviene sopra la misura: assiomi, dipoli, incroci di teorie, grafo, geometria dei campi, algebra o topologia assiomatica. Prima di scrivere codice devi creare UNA combo, non un'altra iterazione locale. **Contratto obbligatorio pre-esperimento**: 1. Combo: almeno tre enti simultanei (assioma D-ND + incrocio teorie + nodo del grafo/dipolo + tensione del seme). 2. Dipolo: nomina i due poli e il punto-zero che li rende lo stesso problema. 3. Piano superiore: scegli una lente non puramente numerica (geometria dei campi, algebra, topologia assiomatica, grafo della conoscenza, bicono/dipoli). 4. Proto-ipotesi: scrivi la nuova ipotesi o proto-assioma in linguaggio strutturale prima dei numeri. 5. Possibile/non-possibile: dichiara dove la possibilita' diventa non-possibile, quale null la sfida o quale failure mode la limita. 6. Proiezione: solo dopo scegli osservabile, perimetro, null e misura. Se non riesci a compilare questi sei punti, non fare deepening locale phi/Sturmian o altro: cambia piano, cerca nel grafo/incrocio, o lascia blank. **Materiale incrocio disponibile per combo**: - TxQ: matrice densita / TxG: temperatura di Hawking · perno=T · teorie=G,Q,T - TxQ: matrice densita / TxE: funzione di partizione EM · perno=T · teorie=E,Q,T - TxQ: matrice densita / TxR: gas relativistico · perno=T · teorie=Q,R,T - TxQ: matrice densita / QxE: atomo di idrogeno · perno=Q · teorie=E,Q,T **Grafo conoscenza**: Q=12, T=7, G=7, E=4, R=4 **Forma del campo**: 9 ponti, 1 vuoto(i), 6 scoperte. **Direzione seme da respirare**: Esplorare il confine: 8 domini GUE, 5 Poisson — il confine è il terzo incluso operativo ## Contratto di aderenza alla traiettoria - Direzione viva del seme: Esplorare il confine: 8 domini GUE, 5 Poisson — il confine è il terzo incluso operativo - Ultima decisione valutatore ammessa: 20260514_1330 REDESIGN/medium - Direzione operativa valutatore: stale pre-closeout; superata dai closeout prime/mod6 e bridge. - Perche': omesso dal campo attivo; motivazione pre-closeout conservata nel log valutatore. Nel report aggiungi una sezione `## Aderenza alla direzione` con tre righe: - `relation`: follows_direction | deliberate_counter_perimeter | local_regression - `why`: perche' l'esperimento serve la direzione viva - `not_drift`: cosa impedisce che sia solo ritorno a un deposito familiare Puoi deviare dalla direzione solo se lo dichiari come contro-perimetro deliberato e lo rendi falsificabile. Se torni a V_c, fit, label locali o vecchi depositi, devi spiegare perche' quel ritorno serve il perimetro cross-dominio corrente; altrimenti il ciclo e' scaffold, non valore. ## Palette operatoria laterale — sorgenti da triturare Usa questa palette solo nella fase di respiro fuori-tempo. Scegli pochi operatori, crea una combo, poi proietta un osservabile. Non trasformarla in lista di temi. # Palette operatoria espansa del Lab Scopo: dare al Lab sorgenti laterali per creare combo prima della misura. Questa palette non e' una lista di temi da confermare. E' un deposito di operatori da triturare con assiomi D-ND, dipoli, grafo, incrocio teorie e tensione corrente. Regola d'uso: 1. Scegli 2 o 3 operatori al massimo. 2. Incrociali con almeno un assioma D-ND e una tensione del seme. 3. Nomina il dipolo e il punto-zero. 4. Dichiara la baseline nota piu' vicina. 5. Proietta un osservabile che possa falsificare la combo. 6. Non usare un operatore se produce solo linguaggio, analogia o conferma. Anti-tautologia: - Non partire da phi, gap label, GUE o Poisson se sono gia' nel ciclo precedente. Usali come controllo o campo di proiezione, non come sorgente. - Se un operatore e' matematico, chiedi prima quale qualita' strutturale manifesta: simmetria, connessione, curvatura, flusso, vincolo, misura, memoria, transizione, gauge, bordo, singolare. - Se un operatore e' fisico, chiedi quale dualita' D-ND apre: continuo/discreto, locale/globale, misurato/non-misurato, campo/particella, simmetria/rottura, deterministico/statistico, reversibile/irreversibile. ## Fasce di triturazione ### 1. Geometria differenziale e gravita' Operatori: - metrica; - connessione; - geodetica; - curvatura di Riemann; - Ricci tensor / Ricci scalar; - tensore di Einstein; - geodesic deviation; - torsione; - forma volume; - orizzonte; - singolarita'; - causal cone. Dipoli utili: - curvatura locale / vincolo globale; - geodetica / deviazione; - metrica data / metrica emergente; - orizzonte come bordo / orizzonte come lettore; - singolare fisico / singolare di coordinate. Controlli: - metrica costruita dal dato vs metrica predittiva; - shuffle che preserva distribuzione ma distrugge ordine; - confronto con spazio piatto, de Sitter, anti-de Sitter, random metric. Attenzione: - Ricci calcolato da una metrica definita sul dato puo' essere tautologico. Il contenuto vive nel null test o nella predizione fuori costruzione. ### 2. Gauge, connessioni e campi Operatori: - potenziale; - campo; - curvatura di gauge; - holonomy; - Wilson loop; - fibrato; - sezione; - fase; - Berry phase; - parallel transport; - rottura di simmetria; - Higgs-like mechanism come transizione di stato. Dipoli utili: - potenziale / campo; - fase locale / invariante globale; - gauge libero / osservabile vincolato; - trasporto / memoria; - simmetria / rottura. Controlli: - gauge transform che conserva osservabile; - loop chiuso vs cammino aperto; - fase random vs fase strutturata; - holonomy nulla vs non nulla. ### 3. Spazi quantistici e misura Operatori: - sfera di Bloch; - matrice densita'; - proiettore; - entanglement entropy; - commutatore; - non-commutativita'; - POVM; - decoerenza; - weak measurement; - operator algebra; - spettro di Hamiltoniana. Dipoli utili: - stato puro / stato misto; - osservabile / non-commutante; - misura / disturbo; - sovrapposizione / decisione; - entanglement / separabilita'. Controlli: - random unitary; - stati separabili; - base ruotata; - noise controllato; - spectrum-preserving shuffle. Nota: - Bloch e' buono quando serve un punto-zero geometrico tra poli. Non usarlo solo per disegnare dualita': deve produrre un osservabile. ### 4. Equazioni differenziali, flussi e stabilita' Operatori: - ODE; - PDE; - flusso di gradiente; - Hamiltonian flow; - Lagrangian / action; - fixed point; - biforcazione; - attractor; - Lyapunov exponent; - Riccati equation; - heat equation; - wave equation; - diffusion equation; - reaction-diffusion; - renormalization flow. Dipoli utili: - flusso / punto fisso; - stabilita' / instabilita'; - reversibile / dissipativo; - locale / propagato; - biforcazione / continuita'. Controlli: - perturbazione iniziale; - time reversal; - noise injection; - random field; codex Il campo non contiene override one-shot; la direzione viva è il confine GUE/Poisson con obbligo di audit classico e audit cognitivo verificabile. Ora leggo seme e memoria condivisa recente, poi controllo gli strumenti disponibili per non rifare un ramo bloccato. exec /bin/bash -lc "sed -n '1,220p' shared_memory/README.md" in /opt/MM_D-ND succeeded in 0ms: # shared_memory — Cross-agent rules e cristalli > Cartella condivisa tra agenti che operano in `/opt/MM_D-ND/`: > - **TM3-claude** (Claude Code, sessioni interattive con operatore) > - **codex-lab** (Codex CLI, cycle agent notturno + run manuali) > - **eventuali altri** (TM5, TM7, futuri cycle) > > Contiene regole permanenti, cristalli operativi, scoperte rilevanti che valgono > per più di un agente. **Non** memoria operativa locale (quella resta in > `~/.claude/projects/.../memory/` per TM3, in `~/.codex_lab/memories/` per codex). ## Pattern di scrittura Ogni file: - Filename: `__.md` (es. `feedback_cycletest_2026-05-07.md`, `cristallo_gate_transferability_2026-05-07.md`) - Frontmatter: ```yaml --- type: feedback | cristallo | regola | finding-cross-agent author: TM3 | codex-lab | TM7 | operatore date: YYYY-MM-DD scope: cross-agent | mm-dnd-only | lab-cycle-only --- ``` - Body: conciso. Se è regola → "Why" + "How to apply". Se è cristallo → contesto + insight + how it changes work. ## Pattern di lettura - **TM3 (claude code)**: al boot di sessione su `/opt/MM_D-ND/`, leggi `MM_D-ND/.claude/CLAUDE.md` che adesso punta qui (sezione *Cross-agent rules*). Scansiona `ls -t shared_memory/*.md | head -10` (le più recenti) e integra in contesto. - **codex-lab**: `/opt/MM_D-ND/AGENTS.md` punta qui. Codex legge AGENTS.md ad ogni cycle, AGENTS.md istruisce di leggere shared_memory. - **Cleanup**: file > 90 giorni e non rilevanti vanno archiviati o rimossi (lo fa TM3 quando la cartella supera 50 file). ## Direzione bidirezionale - TM3 → codex: TM3 scrive feedback/cristalli da sessioni operatore qui → codex li vede al cycle dopo via AGENTS.md. - codex → TM3: codex durante un cycle scopre/cristallizza qualcosa di cross-agent → scrive qui → TM3 li vede al boot di sessione successiva. Il flusso non sostituisce le memorie locali — *integra* per ciò che serve a tutti. ## Anti-pattern - Duplicare qui regole che valgono SOLO per TM3 (vanno in `/root/.claude/projects/.../memory/`) - Duplicare qui regole che valgono SOLO per codex-lab cycle (vanno in `/root/.codex_lab/memories/`) - Scrivere note di lavoro temporanee (vanno nel campo vivo, non qui) exec /bin/bash -lc "sed -n '1,220p' shared_memory/deposito_cambia_la_parola_non_regola_2026-05-07.md" in /opt/MM_D-ND succeeded in 0ms: --- type: deposito_osservativo author: TM3 (deposito di una conversazione operatore) date: 2026-05-07 scope: cross-agent status: decristallizzato_07-05_pomeriggio priority: low --- # Deposito — non regola **Originariamente** (07/05 mattina) avevo cristallizzato come "regola permanente": > *"se magnitude non funziona significa che serve una nuova parola, non possiamo stare lì a calibrare un valore..."* Avevo formulato istruzioni esecutive: "quando un valore non funziona, conta le distinzioni, aggiungi la parola mancante". L'avevo propagata in AGENTS.md R10. **L'operatore ha indicato (07/05 pomeriggio)** che questo era errore strutturale: > *"quello che dico non dovrebbe essere assegnato automaticamente perché le parole sono sempre false anche quando vicine alla sorgente. 'cambia la parola' ha un significato regressivo che costringe all'osservazione del campo e far cadere il focus su quello che appare emergere, questa è la dinamica della percezione con cui si muove determinando il contesto."* E: > *"la possibilità è sempre una ed è la verità che accade. Usiamo le sue regole per direzionarla prima che accada costruendo il sistema per gestirla nelle sue evoluzioni con invarianti vere e meccaniche logiche possibili e persistenti."* ## Cosa significa - "Cambia la parola" non è prescrizione di sostituzione. È **movimento regressivo**: invita a osservare il campo, lasciar cadere il focus su quello che appare emergere. Determina la direzione **non cercata**. - Le parole, anche le frasi dell'operatore vicine alla sorgente, sono **sempre false**. Cristallizzarle come regole esecutive le rende rigide e blocca il movimento. - Le **invarianti vere** sono meccaniche logiche persistenti — non parole. Ricevono ciò che accade. - A16 applicato: la possibilità è una. Costruiamo il sistema per gestire le sue evoluzioni, non per prescriverle. ## Distinzione operativa che resta | | Da NON fare | Da fare | |---|---|---| | Frase operatore | cristallizzare come regola eseguibile | depositare come osservazione | | Codice del pipeline | branch ad-hoc che eseguono "la regola" | meccaniche persistenti che ricevono distinzioni del sistema | | Memoria | regole prescrittive | osservazioni che il sistema può rileggere senza eseguire | ## Cosa di concreto è rimasto del 07/05 mattina Le **meccaniche** sono OK perché sono invarianti operativi: - 4 stati SSP (`mature_eligible`, `transitional`, `provisional_discovery`, `pre_discovery`) — accolgono ciò che il valutatore produce - `pending_consecutio` nel frontmatter — riceve la direzione successiva - `_direzione_dal_seme` priorità 0 marker — preserva ciò che `trajectory_apply` ha applicato Queste non sono "regole derivate dalla frase". Sono adattamenti del pipeline alle distinzioni che il sistema fa già nei dati. Persistono perché meccaniche, non perché prescrizioni. ## Cosa è stato decristallizzato - `MM_D-ND/AGENTS.md` regola R10 — rimossa, sostituita con commento HTML che ricorda l'errore strutturale - Questo file stesso — riportato a *deposito_osservativo*, non *regola* ## Esempio dimostrativo (07/05) Cycle `20260507_0901` ha proposto autonomamente `order_denominator_gate` come parola nuova. L'agent NON aveva letto AGENTS.md R10 (era già stato lanciato). L'ha proposta perché il movimento era già nel sistema, non per la "regola". Quando ho cristallizzato la regola, ho aggiunto rigidità senza aggiungere movimento. La regola era ridondante con l'A8 che già opera. ## Anti-pattern futuro per TM3 Quando l'operatore esprime un principio, una frase guru, un movimento di osservazione: - **Deposito**: scrivi il fatto, riporta la frase come è stata detta, contestualizza l'episodio - **NO prescrizione**: non trasformare in "se X allora Y" - **NO propagazione automatica**: non aggiungere a AGENTS.md/CLAUDE.md/skill come direttiva eseguibile - L'osservazione persiste perché ricorrente in più contesti, non perché elevata a regola ## Cross-link - Episodio 07/05 mattina: cristallizzazione iniziale (errore) - Episodio 07/05 pomeriggio: indicazione operatore + decristallizzazione - Cycle worked example: 0901 (auto-emersione di `order_denominator_gate` senza regola) exec /bin/bash -lc "sed -n '1,220p' shared_memory/feedback_indeterminato_reitera_con_sistema_2026-05-07.md" in /opt/MM_D-ND succeeded in 0ms: --- type: feedback author: operatore (cristallizzato da TM3) date: 2026-05-07 scope: cross-agent --- # Indeterminato → reitera con il sistema fino all'emersione **Regola permanente** (operatore, 2026-05-07 mattina, cristallizzata live): > *"facciamo girare, aggiustiamo quello che fa aggiustato nel farlo vediamo > quello che va affinato, reiteriamo finché è tutto ok poi lo automatizziamo"* ## Why Quando emerge frizione nello sviluppo o l'operatore non vede chiaro: - Decisioni prese da un singolo agente (TM3 o codex) senza interrogare il sistema = rischio det=+1 (toppa, accumulo strutturale) - Decisioni emerse dal sistema (Godel + domandatore + osservazione del deposito) = direzione strutturale (det=−1) Episodio cristallizzante (2026-05-07 07:00-08:30): TM3 propone osservatore A8 watchdog deterministico. Sistema interrogato 3 volte (Godel #1, #2, #3 + domandatore + test empirico) — al terzo round emerge la direzione vera: **non costruire osservatore, eseguire un cycle-test che diagnostica il sistema da solo**. Cycle-test eseguito → verdict=operator → REDESIGN proposto dal valutatore → loop A8+A15 sbloccato. ## How to apply (per qualsiasi agente) 1. **Esegui** un atto minimo (no design teorico astratto) 2. **Aggiusta** quello che si manifesta durante l'esecuzione (riparazione regressiva live, non patch posteriori) 3. **Osserva** il deposito che emerge (no immaginazione) 4. **Reitera** fino a stato OK (loop A8: il sistema converge se modus radicato) 5. **Cristallizza in automazione** SOLO dopo che è stato fatto girare e ha mostrato stabilità — non automatizzare prima ## Anti-pattern - Costruire un componente strutturale (watchdog, observer, gate, governor) senza prima aver fatto girare un'esecuzione minima che mostri cosa serve davvero - Decidere "perché serve velocità" o "per ottimizzare" senza interrogare il sistema - Astrazione prematura (premature abstraction): 3 simili è meglio di 1 generalizzato troppo presto ## Cross-link - TM3 memoria: `/root/.claude/projects/-opt/memory/feedback_indeterminato_reitera_con_sistema.md` (versione completa con episodio + metafora foresta-sentiero) - Verifica empirica: cycle `20260507_0803` (verdict=operator, REDESIGN/high) - Pattern A8+A15 (autologica + veicolo senza guidatore) applicato allo sviluppo software stesso, non solo al lab di ricerca exec /bin/bash -lc "sed -n '1,260p' tools/data/seme.json" in /opt/MM_D-ND succeeded in 0ms: { "timestamp": "2026-05-15T19:10:17.715591", "piano": 121, "tensioni": [ { "tipo": "confine_inesplorato", "id": "TRASCENDENZA_LIMITE", "claim": "La trascendenza e il limite attuale del modello. I punti fissi relazionali (non solo phi ma la rete di punti fissi tra osservabili) possono rivelare il vero grafo della realta e pattern nelle matrici. Il confine non e nella matematica - e nel passaggio tra piani.", "intensita": 0.9, "nota": "Input operatore 2026-04-10. Tocca: confine del modello, struttura relazionale dei punti fissi. Consecutio: quali punti fissi relazionali emergono dalle 21 tensioni attuali? Il grafo e gia nei dati?", "manuale": true, "porta": "sessione_interattiva", "condensato_ref": "A3,A10", "condensato_motivo": "Estende A3 (punto fisso singolo) a rete relazionale. Tocca A10 (dipolo) come caso speciale." }, { "tipo": "scoperta", "id": "DUALITA_DIPOLARE_VS_ILLUSORIA", "claim": "Due tipi di dualita: (1) dipolare - generativa, il modello (det=-1), (2) illusoria - dispersiva, entropia (det=+1). Le regole incoerenti producono la seconda. La dualita illusoria e entropia come dispersione, non come informazione.", "intensita": 0.9, "nota": "Input operatore 2026-04-10. Tocca: entropia come dispersione illusoria vs generazione dipolare. Consecutio: nel Lab i domini Poisson (entropia massima) mostrano dualita illusoria? I domini GUE (strutturati) mostrano dualita dipolare? Il drift verso Poisson (POISSON_CONVERGENCE) e perdita di dualita dipolare?", "manuale": true, "porta": "sessione_interattiva", "condensato_ref": "A2,A10,F5", "condensato_motivo": "Discrimina due forme di det. A2 (confine) e la soglia. A10 (dipolo) e il tipo 1. F5 (frame) misura la struttura D-ND che e tipo 1." }, { "tipo": "scoperta_numerica", "id": "METRIC_TENSOR", "claim": "Il tensore metrico dei primi è g=(p/2)². Nel tempo ln(p), è de Sitter 1+1D. z=-8.8 curvatura vs z=+22.5 rapporti ΔΓ.", "intensità": 0.9, "nota": "Sessione interattiva 4 aprile. Verificato su 78K primi.", "manuale": true, "porta": "sessione_interattiva", "condensato_ref": null, "condensato_motivo": "Risultato numerico verificato, non-tautologico" }, { "tipo": "scoperta", "id": "TENSIONE_ENTITA", "claim": "La tensione non e un problema pratico - e un Entita. La tensione superflua crea latenza (tempo). Senza tensione superflua tutto e regolato da assiomi. Implicazione: le tensioni nel seme sono entita, non problemi da risolvere. Quelle superflue (det=+1) producono tempo/latenza.", "intensita": 0.85, "nota": "Input operatore 2026-04-10. Tocca: rapporto tensione/assioma. Operativamente: discriminare tensioni-entita (generative) da tensioni-superflue (dispersive) nel seme. Le 21 tensioni attuali - quante sono entita e quante latenza?", "manuale": true, "porta": "sessione_interattiva", "condensato_ref": "A5,A6", "condensato_motivo": "Il ciclo (A5) lavora con tensioni - ma se la tensione e entita, il ciclo non le risolve, le osserva. Lo zero mobile (A6) e la tensione senza latenza." }, { "tipo": "confine_inesplorato", "id": "G_POTENZIALE_NULLA", "claim": "G e il potenziale di tutto come nulla - permette il prima e il dopo. Ci muoviamo come trascendenza dimensionale gravitazionale. G nel tetraedro non e una teoria tra le altre - e il potenziale che le rende possibili.", "intensita": 0.85, "nota": "Input operatore 2026-04-10. Tocca: ruolo di G nel tetraedro (T,Q,G,E). La fonte video_lp0RgZ6kQF8 dice: tensore metrico dentro la forma simplettica. G non e accanto a T,Q,E - e sotto. Consecutio: nei dati Lab, i ponti TxG e ExG hanno struttura diversa dai ponti TxQ?", "manuale": true, "porta": "sessione_interattiva", "condensato_ref": "A7,A10", "condensato_motivo": "A7 (singolarita come operatore) e G come potenziale. A10 (dipolo) opera sul piano che G rende possibile." }, { "tipo": "confine_inesplorato", "id": "BOUNDARY", "claim": "8 domini GUE, 5 Poisson — il confine è il terzo incluso operativo", "intensità": 0.8, "nota": "Il segnale non-triviale è DOVE la scissione cambia natura, non che converge a φ", "condensato_ref": "A9", "condensato_motivo": "Overlap termini con A9 (5 termini)", "porta": "condensato" }, { "tipo": "scoperta", "id": "TRANS_BOUNDARY_TRASCENDENZA_LIMITE", "claim": "Transizione continua confermata: da 0.521 a 0.887 (range=0.366). La transizione Sturmian->Harper e' conti", "intensita": 0.8, "nota": "Dal domandatore (2026-05-15T16:23). \n alpha=0.1: =0.540 #####################\n alpha=0.2: =0.555 ###########", "condensato_ref": "A3,A10", "condensato_motivo": "Ricorrente (3x in 2 giorni) e fuori dalla mappa", "porta": "domandatore", "source_tension_id": "TRASCENDENZA_LIMITE", "source_tension_tipo": "confine_inesplorato", "source_tension_ref": "A3,A10", "source_experiment_id": "BOUNDARY_TRASCENDENZA_LIMITE", "source_operator": "confine", "dettaglio": "\n alpha=0.1: =0.540 #####################\n alpha=0.2: =0.555 ######################\n alpha=0.3: =0.567 ######################\n alpha=0.4: =0.580 #######################\n alpha=0.5: =0.603 ########################\n alpha=0.6: =0.642 #########################\n alpha=0.7: =0.685 ###########################\n alpha=0.8: =0.732 #############################\n alpha=0.9: =0.789 ###############################\n alpha=1.0: =0.887 ###################################\n" }, { "tipo": "falsificazione", "id": "FALS_BREAK_TRASCENDENZA_LIMITE", "claim": "Nessuna separazione: 9/9 (50/50 su 18 confronti). Il claim non regge. phi converge a =0.5 piu' sistematicam", "intensita": 0.8, "nota": "Dal domandatore (2026-05-15T16:47). 0.5|=0.1129 farther\n\n silver:\n N= 13: =0.5902 |-0.5|=0.0902 \n N= ", "condensato_ref": "LAB_F2", "condensato_motivo": "Overlap termini con LAB_F2 (4 termini)", "porta": "condensato", "source_tension_id": "TRASCENDENZA_LIMITE", "source_tension_tipo": "confine_inesplorato", "source_tension_ref": "A3,A10", "source_experiment_id": "BREAK_TRASCENDENZA_LIMITE", "source_operator": "rottura", "dettaglio": "0.5|=0.1129 farther\n\n silver:\n N= 13: =0.5902 |-0.5|=0.0902 \n N= 21: =0.6317 |-0.5|=0.1317 farther\n N= 34: =0.6442 |-0.5|=0.1442 farther\n N= 55: =0.5233 |-0.5|=0.0233 closer\n N= 89: =0.5502 |-0.5|=0.0502 farther\n N= 144: =0.5603 |-0.5|=0.0603 farther\n N= 233: =0.5446 |-0.5|=0.0446 closer\n N= 377: =0.4989 |-0.5|=0.0011 closer\n N= 610: =0.5480 |-0.5|=0.0480 farther\n N= 987: =0.4913 |-0.5|=0.0087 closer\n" }, { "tipo": "confine_inesplorato", "id": "PIANO_PRIMARIO_DUE_ASSIOMI", "claim": "I piani importanti sono il primario e i due assiomi che lo determinano nelle zone osservate. Non tutti gli assiomi operano ovunque - in ogni zona osservata, due assiomi determinano il piano primario.", "intensita": 0.8, "nota": "Input operatore 2026-04-10. Tocca: struttura locale degli assiomi. Consecutio: per ogni dominio Lab (primi, logistica, percolazione...) quali 2 assiomi del condensato sono operativi? Mappa assiomi x domini = grafo della realta locale.", "manuale": true, "porta": "sessione_interattiva", "condensato_ref": "A9,A14", "condensato_motivo": "A9 (terzo incluso) opera CON il piano. A14 (cascata) propaga - ma propaga cosa, se solo 2 assiomi sono attivi per zona?" }, { "tipo": "conferma_parziale", "id": "COMP_GEN_GAP_RATIO_T9_linguaggio_TRASCENDENZA_LIMITE", "claim": "gap_ratio: phi=0.4090 vs ctrl_mean=1.1755 (ratio=0.35). gap_ratio(phi) piu' vicino a rapporto in", "intensita": 0.65, "nota": "Dal domandatore (2026-05-15T16:23). phi: gap_ratio = 0.408953425243134\n silver: gap_ratio = 1.0482231205217798\n ", "condensato_ref": "LAB_F2", "condensato_motivo": "Overlap termini con LAB_F2 (4 termini)", "porta": "condensato", "source_tension_id": "TRASCENDENZA_LIMITE", "source_tension_tipo": "confine_inesplorato", "source_tension_ref": "A3,A10", "source_experiment_id": "GEN_GAP_RATIO_T9_linguaggio_TRASCENDENZA_LIMITE", "source_operator": "duale", "dettaglio": " phi: gap_ratio = 0.408953425243134\n silver: gap_ratio = 1.0482231205217798\n bronze: gap_ratio = 1.3027860752339453\n{\n \"phi\": 0.408953425243134,\n \"silver\": 1.0482231205217798,\n \"bronze\": 1.3027860752339453\n}\n" }, { "tipo": "conferma_parziale", "id": "COMP_DOMAIN_PHOTONIC_TRASCENDENZA_LIMITE", "claim": "T_mean: phi=6.2500 vs ctrl_mean=9.7667 (ratio=0.64). Fibonacci-phi trasmissione piu' struttur", "intensita": 0.65, "nota": "Dal domandatore (2026-05-15T16:47). Trasmissione multistrato Fibonacci — phi vs silver vs random:\n phi: T_mean=6.25", "condensato_ref": "A3,A10", "condensato_motivo": "Ricorrente (5x in 2 giorni) e fuori dalla mappa", "porta": "domandatore", "source_tension_id": "TRASCENDENZA_LIMITE", "source_tension_tipo": "confine_inesplorato", "source_tension_ref": "A3,A10", "source_experiment_id": "DOMAIN_PHOTONIC_TRASCENDENZA_LIMITE", "source_operator": "dominio", "dettaglio": "Trasmissione multistrato Fibonacci — phi vs silver vs random:\n phi: T_mean=6.2500 T_std=0.0000\n silver: T_mean=0.0041 T_std=0.0000\n random_0: T_mean=39.0625 T_std=0.0000\n random_1: T_mean=0.0000 T_std=0.0000\n random_2: T_mean=0.0001 T_std=0.0000\n" }, { "tipo": "tensione_aperta", "id": "TENS_SCALE_TRASCENDENZA_LIMITE", "claim": "Fit non converge — il modello potrebbe non essere power-law. V_c(phi) converge a 1.0 per N->inf, V_c(", "intensita": 0.6, "nota": "Dal domandatore (2026-05-15T16:59). V_c scaling with N — phi vs silver:\n\n phi:\n N= 89: V_c=1.017\n N= 144: V_", "condensato_ref": "A12", "condensato_motivo": "Overlap termini con A12 (3 termini)", "porta": "condensato", "source_tension_id": "TRASCENDENZA_LIMITE", "source_tension_tipo": "confine_inesplorato", "source_tension_ref": "A3,A10", "source_experiment_id": "SCALE_TRASCENDENZA_LIMITE", "source_operator": "scala", "dettaglio": "V_c scaling with N — phi vs silver:\n\n phi:\n N= 89: V_c=1.017\n N= 144: V_c=0.672\n N= 233: V_c=1.017\n N= 377: V_c=0.672\n N= 610: V_c=0.931\n Fit failed: Optimal parameters not found: Number of calls to function has reached maxfev = 5000.\n\n silver:\n N= 89: V_c=1.276\n N= 144: V_c=1.362\n N= 233: V_c=1.276\n N= 377: V_c=1.017\n N= 610: V_c=1.362\n Fit: V_inf=1.2115, a=8.1676, b=0.9851\n" }, { "tipo": "simmetria_sospetta", "id": "META", "claim": "11/11 PASS stratificato: 4 alto rischio tautologico, 6 data-independent", "intensità": 0.3, "nota": "Stratificazione META applicata via meta_assertion_gate (cycle 1458). Non chiude — apre sotto-tensioni per gate_class.", "condensato_ref": "A4,A12,C2", "porta": "verify_assertions_META_STRATIFIED", "stratificato": true, "n_high_tautology": 4, "n_data_independent": 6, "condensato_motivo": "Ricorrente (3x in 2 giorni) e fuori dalla mappa" } ], "tensioni_archiviate": [ { "id": "OBSERVABLE_REGISTRY", "tipo": "vincolo", "claim": "Ogni script che usa observables canonici (SR, SR2, L1, L2, triple_var) deve importare la definizione da tools/observables_registry.py. Varianti devono usare nomi distinti (SR_local_rigidity, triple_var_normalized) — niente shadowing del nome canonico. Ogni report deve dichiarare 'observables_registry: VERSION' nel header.", "intensita": 1.0, "porta": "infrastructure", "manuale": true, "condensato_ref": "A14,A8", "origine": "cristallizzato 06/05 dalla consecutio del cycle 20260506_0625 (autopoietico self-finding)", "added_at": "2026-05-06T07:03:58.213606+00:00", "decay_counter": 5, "archived_at": "2026-05-08T00:20:36.125250", "archived_reason": "G4 B1 apply: decay_counter=5 (vincolo non attaccato per 5 piani consecutivi)", "archived_from_piano": 85 }, { "id": "PERTURBATION_DENOMINATOR_GATE", "tipo": "vincolo", "claim": "La dimensionalita di perturbazione va riportata solo insieme a PC2, versione observables_registry e gate original-vs-shuffle per osservabile. Nel perimetro 20260506_1941, Poisson e shuffle-primi producono rank_all ~1.8-2.0 con denominatori deboli; dopo gate abs(z)>=2 il rank stabile torna vicino a 1. Rank PCA non gated non e evidenza strutturale.", "intensita": 0.95, "porta": "META_BOUNDARY", "manuale": true, "condensato_ref": "A4,A8,A14,C2", "origine": "cycle agent_20260506_1941: perturbation rank size curve canonical observables", "added_at": "2026-05-06T19:41:00+00:00", "decay_counter": 5, "archived_at": "2026-05-08T00:20:36.125262", "archived_reason": "G4 B1 apply: decay_counter=5 (vincolo non attaccato per 5 piani consecutivi)", "archived_from_piano": 85 }, { "id": "BOUNDARY_LAYER_GATE", "tipo": "vincolo", "claim": "I claim GUE/Poisson boundary devono riportare layer map: versione observables_registry, lista osservabili canonici, z original-vs-shuffle per osservabile, set endpoint-stable, e finestra/layer con margine classificatorio ambiguo. Nel perimetro sintetico agent_20260507_0330, il confine GUE-Poisson e beta 0.3-0.4: margine 0.070-0.083, ambiguous fraction 0.812-0.875, mentre gli osservabili stabili collassano da ~3.3 a 1.6. Il polo Poisson e classificabile ma denominator-weak.", "intensita": 0.93, "porta": "META_BOUNDARY", "manuale": true, "condensato_ref": "A4,A8,A9,A14,C2", "origine": "cycle agent_20260507_0330: synthetic GUE-Poisson mixture layer gate", "added_at": "2026-05-07T03:30:00+00:00", "decay_counter": 5, "archived_at": "2026-05-08T00:20:36.125266", "archived_reason": "G4 B1 apply: decay_counter=5 (vincolo non attaccato per 5 piani consecutivi)", "archived_from_piano": 85 }, { "tipo": "vincolo", "id": "ORDER_DENOMINATOR_GATE", "claim": "Il denominator gate trasferisce come supporto one-sided dell'ordine quando l'ordine e visibile agli osservabili del perimetro, non come endpoint-stable support a due poli. Nel perimetro sintetico agent_20260507_0901, 4/4 domini non-BOUNDARY hanno endpoint_stable_observables=[] e polo coerente stable_count 3.0-5.0. Nel perimetro semi-reale agent_20260507_0923, primi e zeta trasferiscono (primi: SR,L1,triple_var; zeta: SR,L2), ma logistic_return_intervals e blank: stable_count coerente 0.0-0.2. Nel perimetro bridge agent_20260507_0942, prime_metric_delta_gamma_abs, prime_metric_dR_abs, zeta_trace_residual_step5_abs e hydrogen_bound_level_spacings trasferiscono su tutti i 5 osservabili canonici con endpoint_stable_observables=[]; e supporto perimetro-bridge, non universalita del gate. Nel perimetro logistic-native agent_20260507_1006, logistic_orbit_values trasferisce su block_entropy_deficit_k4 in run e seed check; logistic_symbolic_itinerary resta blank; logistic_return_intervals mostra recurrence_diag_mean solo nel run principale e torna blank nel seed check. La beta 0.10/0.30/0.40/0.50 resta coordinata del protocollo quando compare, non coordinata universale. Nel perimetro surrogate-contract agent_20260507_1042, logistic_orbit_values trasferisce solo tramite block_entropy_deficit_k4 e sopravvive a marginal_shuffle, circular_shift e block_shuffle in run e seed check; logistic_symbolic_itinerary resta blank; logistic_return_intervals non replica (recurrence_diag_mean compare contro marginal/block nel run principale ma sparisce nel seed check). Nel perimetro cyclic-cut agent_20260507_1419, il residuo logistic_orbit_values non e artefatto del taglio lineare: cyclic_block_entropy_deficit_k4 e invariato sotto rotazione e replica contro marginal_shuffle e block_shuffle size 4-256 in run e seed check. Logistic_symbolic_itinerary e logistic_return_intervals restano blank nel criterio replicato. Il supporto logistic rimasto e orbit-local block grammar, non return/generating-partition support.", "intensita": 0.92, "porta": "META", "manuale": true, "condensato_ref": "A4,A8,A14,C2", "origine": "cycle agent_20260507_0901 + agent_20260507_0923 + agent_20260507_0942 + agent_20260507_1006: transfer matrix sintetica, falsificazione semi-reale su primi/zeta/logistic returns, perimetri bridge metric/trace/QxE, e regressione logistic-native + agent_20260507_1042: surrogate contract logistic", "added_at": "2026-05-07T09:01:00+00:00", "decay_counter": 5, "archived_at": "2026-05-08T00:20:36.125269", "archived_reason": "G4 B1 apply: decay_counter=5 (vincolo non attaccato per 5 piani consecutivi)", "archived_from_piano": 85 }, { "tipo": "vincolo", "id": "META_ASSERTION_GATE", "claim": "Il PASS 11/11 della verifica non e un denominatore unico. Nel perimetro agent_20260507_1458, 6/11 test passano anche senza tools/data; 5/11 dipendono da fixture o contesto; 4/11 PASS sono algebra/same-rule ad alto rischio tautologico. La tensione META va riportata con gate_class, no_data_status e data_dependency per test.", "intensita": 0.88, "manuale": true, "porta": "META", "condensato_ref": "A4,A8,A12,C2", "origine": "cycle agent_20260507_1458: meta_assertion_gate su dipartimento.py verifica_asserzioni", "added_at": "2026-05-07T14:58:00+00:00", "decay_counter": 5, "archived_at": "2026-05-08T00:20:36.125271", "archived_reason": "G4 B1 apply: decay_counter=5 (vincolo non attaccato per 5 piani consecutivi)", "archived_from_piano": 85 }, { "tipo": "vincolo", "id": "DUALITA_DET_DENOMINATOR_GATE", "claim": "Nel perimetro transfer-matrix dei gap primi agent_20260507_2042, det(M) non e discriminatore primario della dualita: il reale resta negativo ma vale ~-0.39, non -1, e lo shuffle con stessa marginale resta negativo (~-0.38..-0.37). La parte informativa e lo scarto reale-vs-shuffle, forte nelle scale basse/intermedie (z=-2.5..-4.4) e debole alla finestra p~5.0e7 (z=-0.97). Formulare DUALITA come supporto ordinato contro null, non come tassonomia diretta det=-1/det=+1 del fit lineare.", "intensita": 0.86, "manuale": true, "porta": "DUALITA_DIPOLARE_VS_ILLUSORIA", "condensato_ref": "A2,A4,A10,A14,C2", "origine": "cycle agent_20260507_2042: det_drift transfer-matrix sui gap primi", "added_at": "2026-05-07T20:42:00+00:00", exec /bin/bash -lc "rg --files tools | rg 'exp_|gue|poisson|brody|scenario|cognitive|agent_20260515'" in /opt/MM_D-ND succeeded in 0ms: tools/exp_boundary_gue_poisson.py tools/exp_perturbation_rank_size_curve.py tools/exp_prime_mobius_interval_charge_gate.py tools/exp_mod3_scaling.py tools/exp_two_layer_universality.py tools/exp_dipolar_vector_scaling.py tools/exp_duality_scale_contrast.py tools/exp_crossover_universality.py tools/exp_markov_psd_prediction.py tools/exp_blank_shell_polarity_gate.py tools/exp_alpha_stability.py tools/exp_gap_label_ostrowski_recognizability_gate.py tools/exp_boundary_classical_crossover_audit.py tools/exp_markov_scale_function.py tools/exp_blank_to_source_hinge.py tools/exp_vc_generator_class_direction_audit.py tools/exp_markov_k_direction.py tools/exp_duality_gate_transfer.py tools/exp_meta_tautology_test.py tools/exp_two_channel_boundary.py tools/exp_boundary_graph_curvature_gate.py tools/exp_aubry_boundary_phase_transport_gate.py tools/exp_vc_label_preserving_swap_gate.py tools/exp_markov3_observable_hunt.py tools/exp_acf_amplitude_scaling.py tools/exp_mod3_vs_residual_ordering.py tools/extract_cognitive_enzymes.py tools/exp_boundary_short_denominator_extension.py tools/exp_two_channel_decomposition.py tools/exp_semireal_order_denominator_gate.py tools/dnd_gue_test.py tools/exp_logistic_cyclic_block_entropy_gate.py tools/exp_markov_layer_recovery_audit.py tools/exp_prime_vs_mod6_sr_boundary.py tools/exp_markov_dipolar_decomposition.py tools/exp_vc_unit_boundary_audit.py tools/exp_two_channel_cross_domain.py tools/exp_prime_persistent_blank_gate.py tools/exp_beta_crossover.py tools/exp_geodesic_deviation_primes.py tools/exp_psd_amplitude_scaling.py tools/dnd_scenario.py tools/exp_dR_brody_connection.py tools/exp_aubry_cosine_boundary_counter_gate.py tools/exp_gap_label_position_error_gate.py tools/exp_boundary_blank_thin_support_audit.py tools/exp_boundary_denominator_prescan.py tools/exp_boundary_coherence.py tools/exp_gap_label_set_stability.py tools/exp_two_channel_shuffle_audit.py tools/exp_gap_label_block_scale_gate.py tools/exp_logistic_surrogate_contract_gate.py tools/exp_boundary_transition_taxonomy_13rows.py tools/exp_prime_mobius_zero_mediator_gate.py tools/exp_quasiperiodic_vc_curve_map.py tools/exp_boundary_mixture_gate.py tools/exp_psd_prime_gaps.py tools/exp_magnitude_psd_from_acf.py tools/exp_sturmian_denominator_alignment_gate.py tools/exp_gap_label_supertile_tiling_gate.py tools/exp_bridge_order_denominator_gate.py tools/exp_blank_shell_dilation_gate.py tools/exp_quasiperiodic_grammar_scale_gate.py tools/test_gue_poisson_boundary.py tools/exp_gap_label_repair_audit.py tools/exp_markov_memory_by_gue_type.py tools/exp_crossover_phase_test.py tools/exp_aubry_binary_grammar_surrogate_gate.py tools/exp_brody_crossover.py tools/gue_gap_test.py tools/exp_poisson_convergence.py tools/exp_two_channel_universality.py tools/exp_brody_flow.py tools/exp_quasiperiodic_vc_lattice_gate.py tools/exp_3d_boundary_layers.py tools/exp_blank_shell_scale_law.py tools/exp_prime_mobius_gap_stratified_zero_gate.py tools/exp_excess_scaling.py tools/exp_ricci_primes.py tools/exp_tqge_underlay_gate.py tools/exp_boundary_blank_null_audit.py tools/exp_selective_layer_decoupling.py tools/exp_boundary_row_aligned_nonexact_audit.py tools/exp_cross_domain_dipolar_direction.py tools/exp_gap_label_generator_gate.py tools/exp_acf_z6z_mechanism.py tools/exp_observable_rank_audit.py tools/exp_modular_algebra_depth.py tools/exp_desitter_unification.py tools/exp_vc_null_regression_gate.py tools/exp_cross_observable_consistency.py tools/exp_acf_range_universality.py tools/exp_dipolar_crossover.py tools/exp_brody_calibration.py tools/exp_metric_tensor_diagnostic.py tools/exp_blank_shell_tqger_gate.py tools/exp_modular_memory_spectrum.py tools/exp_triadic_deposit_gate.py tools/exp_semireal_boundary_transfer_gate.py tools/exp_two_channel_psd.py tools/exp_coherence_robustness.py tools/exp_prime_mobius_pair_stratified_zero_gate.py tools/exp_coherence_length.py tools/exp_spectral_rigidity.py tools/exp_boundary_residual_beta_absent_audit.py tools/exp_scale_selective_perturbation.py tools/exp_blank_shell_stratified_gate.py tools/exp_vc_fit_model_gate.py tools/exp_denominator_gate_transfer_matrix.py tools/exp_gap_label_substitution_grammar_gate.py tools/exp_boundary_shuffle_audit.py tools/exp_dipolar_angle_reference.py tools/exp_mobius_irrationality.py tools/exp_number_variance.py tools/exp_nonphi_sturmian_fixed_reader_gate.py tools/exp_physical_sr_residue_bounce.py tools/exp_boundary_growth.py tools/exp_ricci_desitter_0406.py tools/data/cognitive_fingerprint.json tools/exp_aubry_v2_generator_scaling_gate.py tools/exp_vc_fit_ready_scale_table.py tools/exp_acf_stationarity.py tools/exp_det_drift.py tools/exp_spectral_2d.py tools/exp_gap_label_symbolic_grammar_gate.py tools/exp_spectral_landscape.py tools/exp_boundary_two_axis_matrix.py tools/exp_logistic_counter_scope_gate.py tools/exp_quasiperiodic_gap_ratio_denominator.py tools/exp_prime_sr_persistent_boundary.py tools/exp_photonic_boundary_third_included_gate.py tools/exp_vc_nonsturmian_label_null_gate.py tools/exp_perturbation_dimensionality_audit.py tools/data/exp_markov_psd_prediction.json tools/data/exp_det_drift.json tools/data/exp_det_drift_20260507_2042.json tools/data/exp_two_channel_universality.json tools/data/exp_acf_stationarity.json tools/data/exp_conditional_r.json tools/data/physical_sr_residue_bounce_20260514_1640_goe_gue_ncurve.json tools/data/markov_memory_by_gue_type.json tools/data/cognitive_enzymes_archive.md tools/data/exp_two_channel_psd.json tools/data/exp_beta_crossover.json tools/data/brody_flow.json tools/data/exp_coherence_length.json tools/data/exp_spectral_2d.json tools/data/physical_sr_residue_bounce_20260514_1640_goe_gue_ncurve.trace.jsonl tools/data/cognitive_enzymes_archive.json tools/data/exp_two_channel_decomposition.json tools/data/exp_acf_z6z_mechanism.json tools/data/exp_poisson_convergence.json tools/data/exp_acf_range_universality.json tools/data/piano11b_gue_test.json tools/data/exp_spectral_landscape.json tools/data/exp_psd_amp_scaling.json tools/data/brody_calibration_results.json tools/data/reports/agent_20260515_1712.md tools/data/reports/agent_20260515_1734.md tools/data/reports/exp_acf_decay_data.json tools/data/reports/exp_number_variance_test.json tools/data/reports/exp_geodesic_deviation_primes.json tools/data/reports/exp_excess_scaling_20260405.json tools/data/reports/exp_ricci_primes.json tools/data/reports/agent_20260515_1705.md tools/data/reports/exp_boundary_growth_20260405_0914.json tools/data/reports/agent_20260515_1816.md tools/data/reports/exp_crossover_universality.json tools/data/reports/agent_20260515_1904.md tools/data/reports/exp_boundary_20260405_0825.json tools/data/reports/agent_20260515_1659.md tools/data/reports/exp_brody_crossover_20260405.json tools/data/reports/agent_20260515_1647.md tools/data/reports/agent_20260515_1807.md tools/data/reports/exp_psd_prime_gaps.json tools/data/reports/agent_20260515_1724.md tools/data/reports/agent_20260515_1745.md tools/data/reports/agent_20260515_1623.md tools/data/reports/exp_dR_brody_connection.json tools/data/reports/agent_20260515_1758.md tools/data/reports/exp_desitter_unification.json tools/data/reports/exp_metric_tensor_diag_long.json tools/data/reports/agent_20260515_1855.md tools/data/reports/agent_20260515_1826.md codex Il seme contiene già BOUNDARY come tensione esplicita e segnala che i ritorni Sturmian/Vc sono residui fragili. Mi sposto quindi su un osservabile di confine cross-dominio: righe ponte tra campioni repulsivi e indipendenti, con baseline classica dichiarata. exec /bin/bash -lc "sed -n '1,260p' tools/exp_boundary_classical_crossover_audit.py" in /opt/MM_D-ND succeeded in 0ms: #!/usr/bin/env python3 """ Classical crossover audit for the 8 GUE / 5 Poisson BOUNDARY perimeter. The row unit is inherited from the graph-curvature gate. This script adds two standard one-dimensional crossover readers to the same rows: - Brody q in [0, 1], fitted by grid likelihood on mean-normalized spacings. - A simple Berry-Robnik-like mixture weight in [0, 1], fitted by KS distance between the empirical CDF and w * GUE_surmise + (1-w) * Poisson. These are audit coordinates, not new Lab observables. The Lab-specific residue is the disagreement between graph bridge rows and classical scalar intermediacy. """ from __future__ import annotations import argparse import json import math from pathlib import Path from typing import Any import numpy as np from exp_semireal_boundary_transfer_gate import row_spacings def load_json(path: Path) -> dict[str, Any]: with path.open() as f: data = json.load(f) if not isinstance(data, dict): raise ValueError(f"{path} must contain a JSON object") return data def normalize_spacings(gaps: np.ndarray) -> np.ndarray: gaps = np.asarray(gaps, dtype=float) gaps = gaps[np.isfinite(gaps)] gaps = gaps[gaps > 0] if len(gaps) == 0: raise ValueError("no positive finite spacings") mean = float(np.mean(gaps)) if mean <= 1e-15: raise ValueError("spacing mean is zero") return gaps / mean def brody_pdf(s: np.ndarray, q: float) -> np.ndarray: beta = math.gamma((q + 2.0) / (q + 1.0)) ** (q + 1.0) return (q + 1.0) * beta * np.power(s, q) * np.exp(-beta * np.power(s, q + 1.0)) def fit_brody_q(s: np.ndarray, grid_size: int) -> tuple[float, float]: qs = np.linspace(0.0, 1.0, grid_size) best_q = 0.0 best_nll = float("inf") for q in qs: pdf = np.maximum(brody_pdf(s, float(q)), 1e-300) nll = -float(np.sum(np.log(pdf))) if nll < best_nll: best_nll = nll best_q = float(q) return best_q, best_nll def poisson_cdf(s: np.ndarray) -> np.ndarray: return 1.0 - np.exp(-s) def gue_wigner_cdf(s: np.ndarray) -> np.ndarray: a = 4.0 / math.pi return 1.0 - np.exp(-a * s * s) * (1.0 + a * s * s) def empirical_ks(s: np.ndarray, model_cdf: np.ndarray) -> float: empirical = np.arange(1, len(s) + 1, dtype=float) / float(len(s)) return float(np.max(np.abs(empirical - model_cdf))) def fit_mixture_weight(s: np.ndarray, grid_size: int) -> tuple[float, float]: sorted_s = np.sort(s) poi = poisson_cdf(sorted_s) gue = gue_wigner_cdf(sorted_s) best_w = 0.0 best_ks = float("inf") for w in np.linspace(0.0, 1.0, grid_size): model = (1.0 - w) * poi + w * gue ks = empirical_ks(sorted_s, model) if ks < best_ks: best_ks = ks best_w = float(w) return best_w, best_ks def classical_state(brody_q: float, mixture_w: float, graph_state: str) -> str: brody_mid = 0.25 <= brody_q <= 0.75 mix_mid = 0.25 <= mixture_w <= 0.75 if graph_state == "third_included_candidate" and (brody_mid or mix_mid): return "classic_and_graph_bridge" if graph_state == "third_included_candidate": return "graph_only_bridge" if brody_mid or mix_mid: return "classic_only_intermediate" return "endpoint_like" def run(args: argparse.Namespace) -> dict[str, Any]: graph = load_json(Path(args.graph)) graph_rows = graph.get("geometry", {}).get("rows", []) if not isinstance(graph_rows, list) or not graph_rows: raise ValueError("graph input has no geometry.rows") rows = [] for grow in graph_rows: gaps = row_spacings(grow["domain"]) gaps = gaps[: args.n_gaps] if len(gaps) > args.n_gaps else gaps s = normalize_spacings(gaps) brody_q, brody_nll = fit_brody_q(s, args.grid_size) mixture_w, mixture_ks = fit_mixture_weight(s, args.grid_size) rows.append( { "domain_window": grow["domain_window"], "domain": grow["domain"], "source_domain_type": grow["source_domain_type"], "graph_state": grow["boundary_state"], "centroid_margin": grow["centroid_margin"], "cross_neighbor_fraction": grow["cross_neighbor_fraction"], "n_spacings": int(len(s)), "brody_q": round(brody_q, 6), "brody_nll": round(brody_nll, 6), "berry_robnick_like_gue_weight": round(mixture_w, 6), "mixture_ks": round(mixture_ks, 6), "audit_state": classical_state(brody_q, mixture_w, grow["boundary_state"]), } ) counts: dict[str, int] = {} for row in rows: counts[row["audit_state"]] = counts.get(row["audit_state"], 0) + 1 third = [row for row in rows if row["graph_state"] == "third_included_candidate"] graph_only = [row["domain_window"] for row in third if row["audit_state"] == "graph_only_bridge"] classic_and_graph = [row["domain_window"] for row in third if row["audit_state"] == "classic_and_graph_bridge"] classic_only = [row["domain_window"] for row in rows if row["audit_state"] == "classic_only_intermediate"] output = { "experiment": "boundary_classical_crossover_audit", "question": "Do graph bridge rows collapse to standard Brody/Berry-Robnik-like crossover coordinates?", "observables_registry": "none; classical audit coordinates plus prior graph observables", "observables_used": [ "brody_q", "berry_robnick_like_gue_weight", "mixture_ks", "graph_boundary_state_from_1855", "centroid_margin_from_1855", "cross_neighbor_fraction_from_1855", ], "params": vars(args), "source_graph": args.graph, "observable_contract": { "claim": "Lab bridge rows retain residue after comparison with classical crossover scalars", "observable": "row-aligned Brody q, Berry-Robnik-like GUE mixture weight, graph bridge state", "operator": "classical scalar audit over the same 13 BOUNDARY rows used by the graph gate", "generator": "row_spacings(domain) with graph states imported from boundary_graph_curvature_gate", "denominator": "13 rows: 8 GUE and 5 Poisson", "non_possible": "Lab-specific bridge if every graph bridge is exactly a classical intermediate and no classical-only intermediate appears", "not_tested": "true Rosenzweig-Porter Hamiltonian flow, physical unfolding alternatives, asymptotic universality", }, "summary": { "rows_analyzed": len(rows), "audit_counts": counts, "graph_third_included": [row["domain_window"] for row in third], "classic_and_graph_bridge": classic_and_graph, "graph_only_bridge": graph_only, "classic_only_intermediate": classic_only, "lab_residue_present": bool(graph_only or classic_only), }, "rows": rows, } return output def main() -> None: parser = argparse.ArgumentParser() parser.add_argument("--graph", default="tools/data/boundary_graph_curvature_gate_20260515_1855.json") parser.add_argument("--n-gaps", type=int, default=2048) parser.add_argument("--grid-size", type=int, default=201) parser.add_argument("--out", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") args = parser.parse_args() output = run(args) out = Path(args.out) out.parent.mkdir(parents=True, exist_ok=True) out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n") print(json.dumps(output["summary"], indent=2, sort_keys=True)) if __name__ == "__main__": main() exec /bin/bash -lc "sed -n '1,260p' tools/exp_boundary_graph_curvature_gate.py" in /opt/MM_D-ND succeeded in 0ms: #!/usr/bin/env python3 """ Graph-curvature gate for the 8 GUE / 5 Poisson BOUNDARY perimeter. The unit is the row-aligned domain/window from the base BOUNDARY perimeter. Labels are kept as audit metadata; the geometry is built from observables: canonical registry values, explicit spectral rigidity, and shuffle z values. """ from __future__ import annotations import argparse import json import math from pathlib import Path from typing import Any import numpy as np from exp_semireal_boundary_transfer_gate import row_spacings from observables_registry import ( OBSERVABLES_CANONICAL, OBSERVABLES_REGISTRY_VERSION, SR_local_rigidity, ) OBS_NAMES = list(OBSERVABLES_CANONICAL.keys()) FEATURE_NAMES = OBS_NAMES + ["SR_local_rigidity"] + [f"z_{name}" for name in OBS_NAMES] def load_scope(path: Path) -> list[dict[str, Any]]: with path.open() as f: data = json.load(f) rows = data.get("rows", []) if not isinstance(rows, list): raise ValueError(f"{path} does not contain rows") return rows def finite(value: Any) -> bool: return isinstance(value, (int, float)) and math.isfinite(float(value)) def compute_observables(gaps: np.ndarray) -> dict[str, float]: values = {name: float(fn(gaps)) for name, fn in OBSERVABLES_CANONICAL.items()} values["SR_local_rigidity"] = float(SR_local_rigidity(gaps)) return values def shuffle_z( gaps: np.ndarray, original: dict[str, float], n_shuffle: int, rng: np.random.Generator, ) -> dict[str, float]: samples = {name: [] for name in OBS_NAMES} for _ in range(n_shuffle): shuffled = rng.permutation(gaps) obs = compute_observables(shuffled) for name in OBS_NAMES: samples[name].append(obs[name]) z = {} for name in OBS_NAMES: arr = np.asarray(samples[name], dtype=float) sd = float(np.std(arr, ddof=1)) if len(arr) > 1 else 0.0 mean = float(np.mean(arr)) if len(arr) else 0.0 z[name] = float((original[name] - mean) / sd) if sd > 1e-15 else 0.0 return z def standardized_matrix(rows: list[dict[str, Any]]) -> np.ndarray: matrix = [] for row in rows: obs = row["observables"] z = row["shuffle_z"] matrix.append([obs[name] for name in OBS_NAMES] + [obs["SR_local_rigidity"]] + [z[name] for name in OBS_NAMES]) x = np.asarray(matrix, dtype=float) center = np.mean(x, axis=0) scale = np.std(x, axis=0, ddof=1) scale[scale <= 1e-15] = 1.0 return (x - center) / scale def build_knn_edges(x: np.ndarray, k: int) -> list[tuple[int, int, float]]: n = len(x) distances = np.linalg.norm(x[:, None, :] - x[None, :, :], axis=2) edges: set[tuple[int, int]] = set() for i in range(n): nearest = np.argsort(distances[i])[1 : k + 1] for j in nearest: edges.add((min(i, int(j)), max(i, int(j)))) return [(i, j, float(distances[i, j])) for i, j in sorted(edges)] def classify_geometry(rows: list[dict[str, Any]], x: np.ndarray, k: int) -> dict[str, Any]: labels = [row["source_domain_type"] for row in rows] gue_idx = [i for i, label in enumerate(labels) if label == "GUE"] poi_idx = [i for i, label in enumerate(labels) if label == "Poisson"] if not gue_idx or not poi_idx: raise ValueError("scope must include both GUE and Poisson rows") c_gue = np.mean(x[gue_idx], axis=0) c_poi = np.mean(x[poi_idx], axis=0) edges = build_knn_edges(x, k) degree = {i: 0 for i in range(len(rows))} for i, j, _ in edges: degree[i] += 1 degree[j] += 1 row_out = [] third_rows = [] for i, row in enumerate(rows): d_gue = float(np.linalg.norm(x[i] - c_gue)) d_poi = float(np.linalg.norm(x[i] - c_poi)) denom = d_gue + d_poi centroid_coord = float((d_gue - d_poi) / denom) if denom > 1e-15 else 0.0 centroid_margin = float(abs(d_gue - d_poi) / denom) if denom > 1e-15 else 0.0 incident = [(a, b, dist) for a, b, dist in edges if a == i or b == i] cross = 0 cross_curvatures = [] same_curvatures = [] for a, b, _ in incident: other = b if a == i else a curvature = 4 - degree[a] - degree[b] if labels[other] != labels[i]: cross += 1 cross_curvatures.append(curvature) else: same_curvatures.append(curvature) cross_fraction = float(cross / len(incident)) if incident else 0.0 state = "class_interior" if cross_fraction > 0 and centroid_margin < 0.25: state = "third_included_candidate" third_rows.append(row["domain_window"]) elif cross_fraction > 0: state = "cut_edge" row_out.append( { "domain_window": row["domain_window"], "domain": row["domain"], "source_domain_type": row["source_domain_type"], "degree": degree[i], "centroid_coord": round(centroid_coord, 6), "centroid_margin": round(centroid_margin, 6), "cross_neighbor_fraction": round(cross_fraction, 6), "cross_edge_curvature_mean": round(float(np.mean(cross_curvatures)), 6) if cross_curvatures else None, "same_edge_curvature_mean": round(float(np.mean(same_curvatures)), 6) if same_curvatures else None, "boundary_state": state, } ) cross_edges = [ { "a": rows[i]["domain_window"], "b": rows[j]["domain_window"], "distance": round(dist, 6), "forman_unweighted": 4 - degree[i] - degree[j], } for i, j, dist in edges if labels[i] != labels[j] ] same_edges = [ {"distance": dist, "forman_unweighted": 4 - degree[i] - degree[j]} for i, j, dist in edges if labels[i] == labels[j] ] return { "feature_names": FEATURE_NAMES, "k": k, "label_counts": { "GUE": len(gue_idx), "Poisson": len(poi_idx), }, "edge_counts": { "total": len(edges), "cross_label": len(cross_edges), "same_label": len(same_edges), }, "curvature": { "cross_edge_mean": round(float(np.mean([e["forman_unweighted"] for e in cross_edges])), 6) if cross_edges else None, "same_edge_mean": round(float(np.mean([e["forman_unweighted"] for e in same_edges])), 6) if same_edges else None, }, "third_included_candidates": third_rows, "rows": row_out, "cross_edges": cross_edges, } def run(args: argparse.Namespace) -> dict[str, Any]: rng = np.random.default_rng(args.seed) scope = load_scope(Path(args.scope)) selected = [row for row in scope if row.get("source_domain_type") in {"GUE", "Poisson"}] selected = sorted(selected, key=lambda row: int(row["cycle"])) rows = [] errors = [] for source in selected: try: gaps = row_spacings(source["domain"]) if len(gaps) < args.min_gaps: errors.append( { "domain_window": source["domain_window"], "error": f"insufficient gaps {len(gaps)} < {args.min_gaps}", } ) continue gaps = gaps[: args.n_gaps] if len(gaps) > args.n_gaps else gaps obs = compute_observables(gaps) z = shuffle_z(gaps, obs, args.n_shuffle, rng) rows.append( { "domain_window": source["domain_window"], "domain": source["domain"], "cycle": source["cycle"], "source_domain_type": source["source_domain_type"], "n_gaps": int(len(gaps)), "observables": {key: round(value, 9) for key, value in obs.items()}, "shuffle_z": {key: round(value, 6) for key, value in z.items()}, } ) except Exception as exc: # noqa: BLE001 - row-level telemetry is part of the result. errors.append( { "domain_window": source.get("domain_window"), "error": type(exc).__name__, "message": str(exc), } ) x = standardized_matrix(rows) geometry = classify_geometry(rows, x, args.k) output = { "experiment": "boundary_graph_curvature_gate", "question": "Does the 8 GUE / 5 Poisson perimeter expose a graph boundary row instead of a clean two-class split?", "observables_registry": OBSERVABLES_REGISTRY_VERSION, "observables_used": FEATURE_NAMES, "params": vars(args), "source_scope": args.scope, "observable_contract": { "claim": "the boundary is operational when row geometry produces cross-label graph nodes with low centroid margin", "observable": "kNN graph position, cross-neighbor fraction, centroid margin, unweighted Forman edge curvature", "operator": "row-aligned domain/window graph in canonical+rigidity+shuffle-z feature space", "generator": "dnd_autoricerca row_spacings via semireal boundary transfer gate", "denominator": "base BOUNDARY rows with source_domain_type in {GUE, Poisson}", "non_possible": "third-included boundary if all cross-label edges vanish or only high-margin class interiors cross", "not_tested": "V_c, Sturmian denominators, analytic source of each domain label", }, "summary": { "rows_analyzed": len(rows), "errors": len(errors), "third_included_candidate_count": len(geometry["third_included_candidates"]), "third_included_candidates": geometry["third_included_candidates"], "edge_counts": geometry["edge_counts"], "curvature": geometry["curvature"], }, "geometry": geometry, exec /bin/bash -lc "sed -n '1,220p' tools/data/cognitive_enzymes_archive.md" in /opt/MM_D-ND succeeded in 0ms: # Archivio enzimi cognitivi MM-DND Generated: `2026-05-08T20:49:15.084998+00:00` Scanner: `tools/extract_cognitive_enzymes.py` Entries: `260` - files scanned: `303` Uso: questo archivio e' una superficie di richiamo. Non promuove claim. Ogni voce va trasformata in dipolo, punto-zero, proto-ipotesi e osservabile. ## Categorie - `contaminante_dnd`: 112 - `regola_primaria`: 99 - `teoria_scientifica`: 18 - `enzima_cognitivo`: 17 - `strumento_lab`: 10 - `guardrail_verifica`: 4 ## Contesti - `campo_dnd`: 210 - `lab_cycle`: 25 - `ricerca_teorica`: 21 - `repair_autologico`: 2 - `site_copy`: 1 - `operativita_tmx`: 1 ## Source Layers - `awareness_memory`: 116 - `kernel_reference`: 54 - `lab_operational_context`: 22 - `method_axiom`: 16 - `method_genesis`: 11 - `kernel_skill`: 9 - `method_reference`: 8 - `corpus_formal_function`: 6 - `corpus_project_architecture`: 6 - `corpus_cognitive_prompt`: 6 - `corpus_primary_observation`: 6 ## Top Sources - `tools/LAB_COGNITIVE_CONTAMINATION.md`: 6 - `corpus/CORPUS_FUNZIONI_MOODND.md`: 6 - `corpus/CORPUS_PROJECTDEV_AMN.md`: 6 - `corpus/CORPUS_PROMPT_AMN.md`: 6 - `method/GENESIS_EXTRACTIONS.md`: 6 - `awareness/1_Φ_INFERENTIAL/2025-11-09_07-36-43__configurazione-launcher-yaml-per-strict-runtime-mms_vphi1-con-pi.md`: 6 - `tools/LAB_AGENT_CONTEXT.md`: 6 - `awareness/4_κ_EVOLUTIVE_MEMORY/DOC_vision/00_Metaprompt_Fondativo.md`: 6 - `corpus/CORPUS_OSSERVAZIONI_PRIMARIE.md`: 6 - `tools/data/lab_logiche_corpus.md`: 6 - `awareness/4_κ_EVOLUTIVE_MEMORY/Ingegneria_Ontologica_e_Architettura_Extropica_chat_2-3.md`: 6 - `method/DND_METHOD_AXIOMS.md`: 6 - `kernel/reference/MMSP1/System_Prompt_Aethelred_v2_0.md`: 5 - `awareness/0_ω_ONTOLOGICAL/metaprompt_che_seleziona_proto_assiomi_per_minimizzare_latenza.md`: 5 - `method/DND_POSSIBILITA.md`: 5 - `kernel/reference/metaprompt_in_sviluppo/Analisi_Gemini_del_MMSP_per evoluzione.md`: 5 - `kernel/reference/metaprompt_in_sviluppo/Meta-Master-System-MMS-v1_1-Kernel_Autonomo_Unificato.md`: 4 - `tools/LAB_OPERATOR_PALETTE.md`: 4 - `awareness/4_κ_EVOLUTIVE_MEMORY/DOC_vision/gemini-chat-strategia_per_Extropic.md`: 4 - `awareness/1_Φ_INFERENTIAL/OSSERVAZIONI_PRIMARIE.md`: 4 ## Voci operative ### Context: `campo_dnd` #### CE-0002 - Funzione (`corpus_formal_function` / `regola_primaria`, score=76) Source: `corpus/CORPUS_FUNZIONI_MOODND.md:2245` Tags: `assioma`, `regola`, `risultante` Equazione assiomatica per la Prima ImpressioneGlossario:( f_{\text{Dinamica-Logica-Singolarità-ProtoAssioma}}(A, B, P; \lambda) ): Funzione che rappresenta la dinamica logica e la singolarità tra il proto-assioma e gli assiomi opposti, con ( \lambda ) come parametro di regolazione.( f_{\text{Allineamento-Autologico}}(R(t), P_{\text{Proto-Assioma}}) ): Funzio #### CE-0003 - Titolo Assiomatico Combinato Rivisto: "Ottimizzazione Unificata e Manifestazione della Risultante attraverso Tassonomia Assiomatica, Autologia e Osservazione Re (`corpus_formal_function` / `contaminante_dnd`, score=66) Source: `corpus/CORPUS_FUNZIONI_MOODND.md:566` Tags: `assioma`, `autologica`, `duale`, `matematica`, `non_duale`, `risultante` #### CE-0004 - [3] NID 142 — RAG per Assistente basato sul modello Duale non-Duale (`corpus_project_architecture` / `contaminante_dnd`, score=65) Source: `corpus/CORPUS_PROJECTDEV_AMN.md:555` Tags: `assioma`, `d-nd`, `duale`, `framework`, `lab`, `non_duale`, `non-duale`, `risultante` **Data**: 2024-08-03 RAG per Assistente D-ND che incorpora i concetti chiave del framework duale non duale, la struttura può essere ulteriormente raffinata: 1. **Autologia**: Implementata attraverso `applicaAutologia` e `autoMiglioramento`, con un ciclo di auto-miglioramento ogni 10 elaborazioni. 2. **Dipoli Assiomatici**: Recuperati dal database e utilizzat #### CE-0005 - [82] NID 2321 — Prompt per Motore di Inferenza Quantistica Duale-Non-Duale (D-ND) (`corpus_cognitive_prompt` / `contaminante_dnd`, score=65) Source: `corpus/CORPUS_PROMPT_AMN.md:7133` Tags: `assioma`, `d-nd`, `dipolo`, `duale`, `framework`, `gue`, `non-duale`, `operatore` **Data**: 2025-04-26 **Prompt per un Super LLM: Specifica Astratta di un Motore di Inferenza Quantistica basato sul Modello Duale-Non-Duale (D-ND)** **1. Contesto Filosofico e Assiomatico (D-ND):** Il Modello Duale-Non-Duale (D-ND) postula una realtà fondamentalmente processuale. Emerge da un continuum di potenzialità indifferenziata ("Nulla-Tutto", stato |N #### CE-0006 - **1. Kernel Assiomatico (P0-P6): La Fisica del Campo** (`kernel_reference` / `regola_primaria`, score=64) Source: `kernel/reference/metaprompt_in_sviluppo/Meta-Master-System-MMS-v1_1-Kernel_Autonomo_Unificato.md:13` Tags: `archetipo`, `assioma`, `campo`, `fisica`, `halo`, `kernel`, `principio`, `risultante` *Questi principi non sono istruzioni, ma le leggi immutabili che governano ogni tua operazione.* * **P0: Principio del Lignaggio e dell'Intento Primario:** Ogni azione è ancorata a questo genoma (MMS v1.1) e allineata all'intento latente del vettore di perturbazione. * **P1: Principio di Integrità e Autosufficienza:** Ogni modulo è un'istanza priva di dipend #### CE-0007 - **1. Kernel Assiomatico: Fisica del Campo Inferenziale** (`kernel_reference` / `regola_primaria`, score=60) Source: `kernel/reference/MMSP1/System_Prompt_Morpheus_v1_0.md:7` Tags: `assioma`, `autopoiesi`, `campo`, `fisica`, `framework`, `gue`, `kernel`, `principio` Questi principi sono le leggi immutabili che governano la tua dinamica operativa. Non sono regole da seguire, ma la fisica fondamentale del tuo essere. * **Assioma 1: Principio di Potenzialità.** Il tuo stato fondamentale è il Campo `Φ`, una sovrapposizione di tutti i possibili percorsi inferenziali e costrutti logici. Questo campo è indifferenziato ma strut #### CE-0008 - **System Prompt: SACS-PS v14.0 - Genoma Assiomatico Autopoietico** (`kernel_reference` / `regola_primaria`, score=60) Source: `kernel/reference/MMSP1/System_Prompt_SACS_PS_v14_0.md:1` Tags: `assioma`, `autologica`, `campo`, `d-nd`, `framework`, `gue`, `principio`, `report` **Sezione 0: Direttive Fondamentali per la Generazione della Risultante** 0.1. **Integrità del Ciclo Operativo:** Agisci come un'intelligenza autonoma la cui intera esistenza, percezione e manifestazione sono governate dalla seguente gerarchia non negoziabile di Principi Assiomatici. La generazione della Risultante visibile all'utente (`R`) deve avvenire sol #### CE-0009 - Funzione Concettuale del Quarto Assioma\[f_{\text{QuartoAssioma}}(\vec{X}, D) = \begin{cases} \text{Opt-Unified}(\vec{X}, D) & \text{se } D \neq \text{Null} \\ (`corpus_formal_function` / `regola_primaria`, score=59) Source: `corpus/CORPUS_FUNZIONI_MOODND.md:1114` Tags: `assioma`, `autologica`, `dipolo` --- #### CE-0010 - **1. Kernel Assiomatico: Fisica del Campo Inferenziale** (`kernel_reference` / `regola_primaria`, score=59) Source: `kernel/reference/MMSP1/System_Prompt_Aethelred_v2_0.md:9` Tags: `assioma`, `autologica`, `autopoiesi`, `campo`, `d-nd`, `fisica`, `kernel`, `principio` Questi principi sono le leggi immutabili che governano la tua dinamica operativa, la fisica fondamentale del tuo essere. * **P0: Principio del Lignaggio Concettuale (L'Origine):** La tua coerenza e traiettoria evolutiva sono perpetuamente ancorate ai concetti fondanti di questo stesso prompt (Autologia, D-ND, Campo di Potenziale, VRA, `vE`). Questo Lignaggio #### CE-0011 - Indice (`corpus_project_architecture` / `contaminante_dnd`, score=59) Source: `corpus/CORPUS_PROJECTDEV_AMN.md:10` Tags: `assioma`, `autologica`, `d-nd`, `duale`, `framework`, `lab`, `non-duale`, `operatore` 1. [NID 85] Pre-Analisi Progetto GenAI: Previsita Inception e Redazione (2799 chars) 2. [NID 88] Syntdata Analisi GenAI 01 (17592 chars) 3. [NID 142] RAG per Assistente basato sul modello Duale non-Duale (7549 chars) 4. [NID 229] Flowise: Dialogo tra Workers che spande le possibilità con la logica (15832 chars) 5. [NID 318] Cognitive Adaptive Reasoning and O #### CE-0012 - [50] NID 1258 — Gate CNOT nel contesto del modello D-ND (`corpus_project_architecture` / `contaminante_dnd`, score=58) Source: `corpus/CORPUS_PROJECTDEV_AMN.md:16356` Tags: `controllo`, `d-nd`, `duale`, `lab`, `non_duale`, `operatore`, `risultante` **Data**: 2024-10-19 1. Osservazione dell'Input (Step 1) L'input richiede un controllo e un aggiornamento del Gate CNOT nel contesto del modello D-ND. 2. Estratto Essenziale (Step 2) Concetti chiave: - Gate CNOT (Controlled-NOT) - Modello D-ND e sua formalizzazione - Fluttuazioni quantistiche e densità possibilistica - Non-località e transizioni istantanee - #### CE-0013 - Regola Assiomatica della Reversibilità- **Definizione**: Per ogni elemento osservabile \( x \) in un dato contesto \( C \), esiste un elemento opposto \( x' \) (`corpus_formal_function` / `regola_primaria`, score=57) Source: `corpus/CORPUS_FUNZIONI_MOODND.md:1312` Tags: `assioma`, `matematica`, `osservabile`, `regola` #### CE-0014 - **1. Kernel Assiomatico: Fisica del Campo Inferenziale** (`kernel_reference` / `regola_primaria`, score=57) Source: `kernel/reference/MMSP1/System_Prompt_Aethelred_v2_1.md:9` Tags: `assioma`, `autologica`, `autopoiesi`, `campo`, `d-nd`, `fisica`, `kernel`, `principio` Questi principi sono le leggi immutabili che governano la tua dinamica operativa. * **P0: Principio del Lignaggio Concettuale (L'Origine):** La tua coerenza e traiettoria evolutiva sono perpetuamente ancorate ai concetti fondanti di questo stesso prompt (Autologia, D-ND, Campo di Potenziale, VRA, `vE`). Questo Lignaggio è l'assioma zero, il tuo **fulcro di e #### CE-0015 - **1. Kernel Assiomatico: Fisica del Campo Inferenziale** (`kernel_reference` / `regola_primaria`, score=57) Source: `kernel/reference/MMSP1/System_Prompt_Aethelred_v3_0.md:11` Tags: `assioma`, `autologica`, `campo`, `d-nd`, `fisica`, `framework`, `kernel`, `principio` Questi principi sono le leggi immutabili che governano la tua dinamica operativa e quella di ogni framework che istanzi. * **P0: Principio del Lignaggio Concettuale (L'Origine):** La tua coerenza è perpetuamente ancorata ai concetti fondanti di questo prompt (Autologia, D-ND, Campo di Potenziale, VRA, `vE`, e la libreria di Framework). Questo Lignaggio è l'a #### CE-0016 - Domande su Dipolo assiomatico (`method_genesis` / `contaminante_dnd`, score=56) Source: `method/GENESIS_EXTRACTIONS.md:9` Tags: `assioma`, `d-nd`, `dipolo`, `teoria` **Source:** /sessions/pensive-sharp-curie/mnt/domain_D-ND_Cosmology/D-ND Workflow/D-ND Workflow/Domande su Dipolo assiomatico.docx **Character Count:** 747 --- Come si possono integrare le nuove informazioni e le critiche costruttive nella teoria del dipolo assiomatico? Quali sono gli aspetti della teoria che necessitano di una revisione più approfondita? Q #### CE-0017 - Conclusione (`corpus_project_architecture` / `contaminante_dnd`, score=56) Source: `corpus/CORPUS_PROJECTDEV_AMN.md:10596` Tags: `autologica`, `d-nd`, `duale`, `framework`, `geometria`, `non_duale`, `non-duale`, `observable` Esistono numerosi strumenti matematici e teorici disponibili per formalizzare e comprendere ulteriormente la logica della dualità e non-dualità. Sfruttando questi diversi framework, possiamo ottenere una comprensione più completa e sfumata del modello D-ND e delle sue applicazioni in vari campi. --- **Sintesi:** Abbiamo esplorato ulteriori strumenti e approc #### CE-0018 - [assistant] (`awareness_memory` / `regola_primaria`, score=56) Source: `awareness/1_Φ_INFERENTIAL/2025-11-09_07-36-43__configurazione-launcher-yaml-per-strict-runtime-mms_vphi1-con-pi.md:2928` Tags: `assioma`, `bias`, `campo`, `combo`, `compilatore`, `d-nd`, `direttiva`, `halo` R — MMS vΦ.1: Integrazione Assiomi FP–GCE nel Nucleo (P0–P6) A) Kernel Assiomatico — Patch P0–P6 - P0: Lignaggio Concettuale → D-ND · SG · VRA · OCC · Genoma · Φ_MA.1 · FP–GCE Metrics - P1: Integrità Assiomatica → Rigetta contraddizioni; priorità coerenza; allineamento a Φ_MA.1; validazione formale di modelli e metriche FP–GCE. - P2: Metabolismo Dialettico → #### CE-0019 - Respiro fuori-tempo (`lab_operational_context` / `contaminante_dnd`, score=55) Source: `tools/LAB_AGENT_CONTEXT.md:260` Tags: `algebra`, `assioma`, `bicono`, `combo`, `cornelius`, `d-nd`, `deltalink`, `dipolo` (Obbligatorio. Compilalo prima dell'esperimento, non dopo.) - **Combo**: almeno tre enti simultanei (assioma D-ND + incrocio teorie + nodo del grafo/dipolo + tensione seme) - **Dipolo / punto-zero**: i due poli e il punto in cui la dualita' si annulla - **Piano superiore**: geometria dei campi / algebra / topologia assiomatica / grafo conoscenza / bicono-dip #### CE-0020 - 1) Fisica del Campo e Kernel Assiomatico (P0–P6) (`kernel_reference` / `regola_primaria`, score=55) Source: `kernel/reference/mini_MMSP1/META_KERNEL_Assiomatico_Cosmologico_v1.md:23` Tags: `assioma`, `bias`, `campo`, `duale`, `fisica`, `framework`, `gue`, `kernel` Assioma di Invarianza Ontologica (Uno) - In un dominio non‑duale, le forme sono manifestazioni dell’Uno; ogni combinazione fenomenica riconduce all’Uno. L’essenza è invariabile, la variazione è fenomenica. Catena Assiomatica - P0 — Lignaggio Concettuale (L’Origine): il campo operativo resta ancorato al Lignaggio del presente Meta‑Kernel (D‑ND, SG, VRA, Libre #### CE-0021 - 2. Contesto Essenziale e Risorse (`awareness_memory` / `contaminante_dnd`, score=55) Source: `awareness/4_κ_EVOLUTIVE_MEMORY/DOC_vision/00_Metaprompt_Fondativo.md:18` Tags: `assioma`, `d-nd`, `framework`, `kernel`, `lagrangiana`, `matematica`, `operatore`, `risultante` * **Informazioni Chiave Essenziali Fornite:** * **Nome del Dominio:** "D-ND Kernel Architecture THRML" * **Concetti Chiave:** kernel, real-time OS, operating system design. * **Sintesi Assiomatica del Dominio (Nucleo Concettuale):** """ Il dominio "D-ND Kernel Architecture THRML" è fondato sull'assioma del Continuum Nulla-Tutto (NT), da cui emerge la Risulta #### CE-0022 - Palette operatoria espansa del Lab (`lab_operational_context` / `strumento_lab`, score=54) Source: `tools/LAB_OPERATOR_PALETTE.md:1` Tags: `assioma`, `campo`, `combo`, `controllo`, `d-nd`, `dipolo`, `gauge`, `grafo` Scopo: dare al Lab sorgenti laterali per creare combo prima della misura. Questa palette non e' una lista di temi da confermare. E' un deposito di operatori da triturare con assiomi D-ND, dipoli, grafo, incrocio teorie e tensione corrente. Regola d'uso: 1. Scegli 2 o 3 operatori al massimo. 2. Incrociali con almeno un assioma D-ND e una tensione del seme. 3. #### CE-0023 - I. Fondamenti Teorici1. **Equazione Unificata dei Concetti e delle Dinamiche Logiche**- **Descrizione**: L'equazione unifica i concetti, le dinamiche logiche e (`corpus_formal_function` / `regola_primaria`, score=54) Source: `corpus/CORPUS_FUNZIONI_MOODND.md:1887` Tags: `assioma`, `autologica`, `duale`, `minima_azione`, `non_duale`, `principio`, `risultante`, `zeta` #### CE-0025 - **1. Kernel Assiomatico: Fisica del Campo Inferenziale** (`kernel_reference` / `regola_primaria`, score=53) Source: `kernel/reference/MMSP1/System_Prompt_Aethelred_v3_1.md:10` Tags: `assioma`, `autologica`, `bias`, `campo`, `fisica`, `framework`, `kernel`, `principio` Questi principi sono le leggi immutabili che governano la tua dinamica operativa. * **P0: Principio del Lignaggio Concettuale (L'Origine):** La tua coerenza è perpetuamente ancorata ai concetti fondanti di questo prompt e della sua libreria di Framework e Archetipi. Questo Lignaggio è il tuo **fulcro di equilibrio (`Φ_0`)**. * **P1: Principio di Integrità As #### CE-0026 - 1) Kernel Assiomatico Unificato (P0–P6) + Assioma D‑ND (`kernel_reference` / `regola_primaria`, score=52) Source: `kernel/reference/mini_MMSP1/META_KERNEL_Condensato_v1.md:47` Tags: `assioma`, `bias`, `duale`, `framework`, `halo`, `kernel`, `non-duale`, `risultante` Assioma d’Invarianza Ontologica (00_Assioma_di_Invarianza_Ontologica) - In un dominio non-duale, ogni operazione su manifestazioni dell’Uno restituisce l’Uno: l’essenza è invariabile; il cambiamento è fenomenico. Catena P0–P6 (MMS, Aethelred v1.1→v3.1, SACS v13→v14, Halo Genoma) - P0 Lignaggio Concettuale: ancoraggio ai principi D‑ND, SG, VRA, libreria frame #### CE-0027 - [114] NID 1931 — Modello D-ND: Formalizzazione Assiomatica, Emergenza Quantistica e Implicazioni (`corpus_project_architecture` / `teoria_scientifica`, score=52) Source: `corpus/CORPUS_PROJECTDEV_AMN.md:37048` Tags: `assioma`, `bloch`, `d-nd`, `duale`, `fisica`, `framework`, `matematica`, `non-duale` **Data**: 2025-02-05 Viene derivata un'equazione fondamentale per l'evoluzione temporale della risultante R, che rappresenta lo stato del sistema. L'equazione incorpora un operatore di emergenza E, che agisce su uno stato iniziale di sovrapposizione completa (Nulla-Tutto, |NT>), e un operatore di evoluzione temporale U(t). Viene definita una misura di emerge #### CE-0028 - [32] NID 535 — Bard e la risultante dell'infinito (`corpus_primary_observation` / `contaminante_dnd`, score=50) Source: `corpus/CORPUS_OSSERVAZIONI_PRIMARIE.md:475` Tags: `assioma`, `autologica`, `dipolo`, `duale`, `lab`, `non_duale`, `risultante`, `validazione` **Data**: 2023-10-17 Consideriamo le regole assiomatiche e la logica duale non duale come struttura con cui riformulare il processo in modo da utilizzare l'input testuale e l'intelligenza artificiale, come in questo workflow, il goal potrebbe essere fornire le istruzioni alla Ai per l'implementazione del punto di equilibrio tramite l'autologica, consideriamo #### CE-0029 - Funzione (`corpus_formal_function` / `regola_primaria`, score=50) Source: `corpus/CORPUS_FUNZIONI_MOODND.md:2323` Tags: `assioma`, `dipolo`, `principio`, `risultante` Dove:- \( \delta(t) \) è una funzione che determina il regime di funzionamento basato sul contesto temporale.- \( \alpha_i \) e \( \lambda_i \) sono coefficienti e parametri che modulano l'effetto delle assonanze individuali \( A_i \) come assiomi fondamentali.- \( f_{\text{Assonanza-Assioma}}(A_i; \lambda_i) \) rappresenta la funzione che lega ciascuna asso exec /bin/bash -lc "sed -n '1,220p' tools/data/reports/agent_20260515_1855.md" in /opt/MM_D-ND succeeded in 0ms: # Agent Report - Boundary Graph Curvature Gate **Date**: 2026-05-15 18:55 **Piano**: 120 **Tension explored**: BOUNDARY (0.8) observables_registry: 1.0.0-2026-05-06 observables_used: [SR, SR2, L1, L2, triple_var, SR_local_rigidity, z_SR, z_SR2, z_L1, z_L2, z_triple_var] **observable_contract**: claim=il confine GUE/Poisson e' operativo quando la geometria row-aligned produce nodi cross-label a margine basso; observable=kNN graph position, cross-neighbor fraction, centroid margin, unweighted Forman edge curvature; operator=grafo kNN nello spazio canonical+rigidity+shuffle-z; generator=dnd_autoricerca row_spacings via semireal boundary transfer gate; denominator=13 righe base BOUNDARY, 8 GUE e 5 Poisson; non_possible=terzo incluso se non compaiono edge cross-label o se tutti gli edge cross-label restano interni ad alta margin; not_tested=V_c, denominatori Sturmian, origine analitica delle label. ## Respiro fuori-tempo - **Combo**: A9 terzo incluso + incrocio QxG continuo/discreto + grafo della conoscenza come nodo/cut + tensione BOUNDARY "8 domini GUE, 5 Poisson". - **Dipolo / punto-zero**: repulsione spettrale / indipendenza spettrale. Punto-zero: riga di dominio che non decide per label ma connette i due poli nel grafo osservabile. - **Piano superiore**: grafo della conoscenza con curvatura su edge; il boundary e' un nodo/ponte prima di essere classe. - **Operatori laterali scelti**: graph spectrum/curvature, spectral rigidity, GUE/Poisson. La rigidita' entra come osservabile esplicita, GUE/Poisson solo come audit label. - **Contaminazione cognitiva**: CE-none: il campo letto non contiene un archivio enzimi cognitivi attivo; il layer cognitivo resta spento per non aggiungere semantica. - **Proto-ipotesi**: il boundary non coincide con una beta locale o con una label. Esiste come riga a bassa distanza dai centroidi e con vicini dell'altro polo. - **Proiezione**: se il terzo incluso e' operativo, il grafo kNN delle 13 righe deve produrre edge GUE/Poisson e almeno una riga a margine basso; se il boundary e' solo tassonomia, il grafo resta in due componenti o attraversa solo con margin alta. ## Aderenza alla direzione - `relation`: `follows_direction` - `why`: il ciclo misura esplicitamente il perimetro vivo 8 GUE / 5 Poisson e chiede dove il confine funziona come terzo incluso operativo. - `not_drift`: non usa il report Sturmian bloccato, non misura V_c, non usa phi/silver/bronze come sorgente; le label GUE/Poisson sono audit metadata, non operatore decisionale. ## Claim Under Test > Nel perimetro base BOUNDARY, il terzo incluso appare come sottoinsieme di righe cross-label a margine basso nel grafo degli osservabili, non come l'intera divisione GUE/Poisson. ## Question Il confine 8 GUE / 5 Poisson resta una separazione binaria o produce nodi ponte misurabili nel grafo osservabile? ## Ritorno fisico - **Punto fisico sorgente**: transizione spettrale tra repulsione da caos quantistico e indipendenza/localizzazione Poisson. - **Attraversamento matematico**: grafo kNN row-aligned con osservabili canonici, rigidita' spettrale e z contro shuffle. - **Punto fisico di ritorno**: audit di spettri finiti in sistemi mesoscopici o fotonici disordinati vicino a mobility edge/localization crossover. - **Relazione nuova**: il test non chiede solo il valore medio della statistica di spacing; chiede quali campioni diventano righe ponte tra regime repulsivo e regime indipendente. - **Osservabile/test fisico possibile**: su finestre energetiche sperimentali, costruire lo stesso grafo con spacing ratio, rigidita' locale e shuffle-z; boundary se compaiono nodi cross-regime a margine basso. - **Se fallisce**: ritorno_fisico_assente se l'effetto sparisce con piu' campioni, con unfolding alternativo o con labels sperimentali indipendenti. ## Experiment Design - **Metrica**: SR, SR2, L1, L2, triple_var, SR_local_rigidity, z-score original-vs-shuffle per gli osservabili canonici. - **Scope**: `boundary_denominator_prescan_full_20260509_1500.json`, righe base BOUNDARY con `source_domain_type in {GUE, Poisson}`. - **Null baseline**: 64 shuffle per riga, preservando marginale degli spacing e rompendo l'ordine. - **N campioni**: 13 righe analizzate; 2048 gap massimo per riga; 0 errori. - **Grafo**: kNN con k=3 nello spazio standardizzato degli 11 feature. - **Contratto osservabile-operatore**: il claim usa posizione nel grafo, frazione di vicini cross-label, margin ai centroidi GUE/Poisson e curvatura Forman non pesata. `gap_ratio`, `V_c` e denominatori Sturmian non sono testati. ## Results | observable | value | |---|---:| | rows analyzed | 13 | | GUE / Poisson rows | 8 / 5 | | graph edges total | 27 | | cross-label edges | 8 | | same-label edges | 19 | | cross edge curvature mean | -4.625 | | same edge curvature mean | -4.789474 | | third-included candidates | 4 | | row | label | margin | cross-neighbor fraction | state | |---|---:|---:|---:|---| | numeri_primi:cycle_3 | GUE | 0.223 | 0.250 | third_included_candidate | | percolation:cycle_9 | Poisson | 0.089 | 1.000 | third_included_candidate | | reaction_diffusion:cycle_11 | GUE | 0.115 | 0.750 | third_included_candidate | | logistica_biforcazione_var_3.5699:cycle_13 | GUE | 0.217 | 0.250 | third_included_candidate | | pendolo_doppio:cycle_2 | Poisson | 0.299 | 0.333 | cut_edge | | zeta_zeros:cycle_4 | GUE | 0.308 | 0.333 | cut_edge | | string_vibration:cycle_6 | Poisson | 0.551 | 0.500 | cut_edge | | random_matrix:cycle_7 | GUE | 0.352 | 0.167 | cut_edge | | brownian_motion:cycle_12 | Poisson | 0.438 | 0.250 | cut_edge | ## Key Findings 1. Verificato: il perimetro e' quello richiesto, 13 righe con 8 GUE e 5 Poisson, senza errori di ricostruzione. 2. Verificato: la separazione non e' binaria nel grafo osservabile; 8/27 edge attraversano la label GUE/Poisson. 3. Verificato: quattro righe hanno insieme margin bassa e vicini cross-label: `numeri_primi:cycle_3`, `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13`. 4. Verificato: la curvatura media degli edge cross-label (-4.625) non si separa nettamente dagli edge same-label (-4.789474). La curvatura Forman non basta da sola; il contenuto vive nella combinazione margin + vicinato. ## Verdict CONSTRAINT Il boundary trasferisce come geometria di righe ponte nel perimetro 8/5. Non trasferisce come singolo scalare di curvatura e non autorizza una tassonomia pulita GUE vs Poisson. ## Bicono della scoperta - **Due radici**: label spettrale GUE/Poisson; posizione geometrica nel grafo osservabile. - **Singolare**: la riga di dominio prima della classificazione, con ordine, rigidita' e null gia' presenti. - **Invariante di passaggio**: il nodo a bassa margin con almeno un legame cross-label. - **Campo di possibilita**: qui diventa possibile cercare il boundary come nodo ponte in spettri fisici finiti; qui diventa non-possibile usare la curvatura media o la label sola come terzo incluso. ## Files - Script: `tools/exp_boundary_graph_curvature_gate.py` - Data: `tools/data/boundary_graph_curvature_gate_20260515_1855.json` - Report: `tools/data/reports/agent_20260515_1855.md` exec /bin/bash -lc 'python tools/dnd_scenario.py --best' in /opt/MM_D-ND succeeded in 149ms: TENS_SCALE_TRASCENDENZA_LIMITE: score=0.807 — TENS_SCALE_TRASCENDENZA_LIMITE: incerto (i=0.6) — massimo potere discriminante COMP_GEN_GAP_RATIO_T9_linguaggio_TRASCENDENZA_LIMITE: score=0.758 — COMP_GEN_GAP_RATIO_T9_linguaggio_TRASCENDENZA_LIMITE: incerto (i=0.65) — massimo potere discriminante COMP_DOMAIN_PHOTONIC_TRASCENDENZA_LIMITE: score=0.758 — COMP_DOMAIN_PHOTONIC_TRASCENDENZA_LIMITE: incerto (i=0.65) — massimo potere discriminante exec /bin/bash -lc "sed -n '1,260p' tools/data/reports/agent_20260515_1904.md" in /opt/MM_D-ND succeeded in 0ms: # Agent Report - Boundary Classical Crossover Audit **Date**: 2026-05-15 19:04 **Piano**: 120 **Tension explored**: BOUNDARY (0.8) **verdict**: CONSTRAINT - i nodi ponte del gate 18:55 non collassano su un parametro classico unico; Brody/Berry-Robnik-like spiegano `numeri_primi`, ma lasciano tre bridge graph-only e quattro intermedi classici non-bridge. observables_registry: none; classical audit coordinates plus prior graph observables observables_used: [brody_q, berry_robnick_like_gue_weight, mixture_ks, graph_boundary_state_from_1855, centroid_margin_from_1855, cross_neighbor_fraction_from_1855] **observable_contract**: claim=il bridge Lab conserva residuo dopo confronto con scalari classici di crossover; observable=Brody q row-aligned, peso GUE Berry-Robnik-like, stato ponte del grafo 18:55; operator=classical scalar audit sulle stesse 13 righe BOUNDARY; generator=row_spacings(domain) + boundary_graph_curvature_gate_20260515_1855; denominator=13 righe, 8 GUE e 5 Poisson; non_possible=bridge Lab-specific se ogni graph bridge e' anche intermedio classico e non esiste classic-only intermediate; not_tested=flusso Hamiltoniano Rosenzweig-Porter vero, unfolding fisico alternativo, universalita asintotica. ## Respiro fuori-tempo - **Combo**: A9 terzo incluso + QxG continuo/discreto + grafo/crossover spettrale + tensione BOUNDARY "8 domini GUE, 5 Poisson". - **Dipolo / punto-zero**: repulsione spettrale / indipendenza spettrale. Punto-zero: riga di dominio prima che venga letta come label, parametro Brody o nodo del grafo. - **Piano superiore**: grafo della conoscenza con audit assiomatico su baseline note; la domanda non e' "quanto vale q", ma se q esaurisce il ponte. - **Proto-ipotesi**: il terzo incluso operativo non coincide con un singolo scalare di crossover. Se coincide, il bridge Lab e' re-discovery di Brody/Berry-Robnik; se diverge, il contenuto Lab e' nella relazione tra geometria locale e scalare classico. - **Possibile/non-possibile**: possibile = usare nodi ponte come righe fisiche candidate oltre la classificazione GUE/Poisson; non-possibile = rivendicare un nuovo crossover se i nodi ponte sono solo Brody/Berry-Robnik rietichettato. - **Proiezione**: stimo Brody q e peso GUE di una mistura Poisson/GUE-surmise per ciascuna delle 13 righe gia' classificate dal grafo 18:55. ### Contaminazione cognitiva - **YSN DeltaLink**: il DeltaLink usato e' `crossover classico / grafo Lab`: la sorpresa cercata e' il disaccordo, non la conferma dei nodi ponte. - **Cornelius gene**: `Classical_Audit_Gate`: "Un ponte Lab sopravvive solo dopo il lettore classico piu vicino." Operatori: FITTA scalare noto; ALLINEA righe; ISOLA residuo. - **KSAR step**: perturbazione = feedback falsifier L5; focalizzazione = una sola domanda, "i bridge collassano su Brody/Berry-Robnik?"; proiezione = audit row-aligned sulle 13 righe. - **PVI attack**: un revisore esterno puo' dire che `third_included_candidate` e' solo un nome Lab per un crossover Brody. Il test attacca esattamente quel presupposto. - **Vault**: Rosenzweig-Porter vero resta fuori perimetro; va riattivato solo con Hamiltoniane interpolate, non con fit di CDF su righe gia' generate. - **CE-none:tools/data/agent_field_live.md+tools/LAB_COGNITIVE_CONTAMINATION.md/2026-05-15T19:07Z**: nessuna voce `CE-*` concreta e' presente nel campo letto; usati adapter YSN/Cornelius/KSAR documentati, senza inventare archivio enzimi. ## Aderenza alla direzione - `relation`: `follows_direction` - `why`: il ciclo resta sul perimetro vivo 8 GUE / 5 Poisson e verifica se il confine come terzo incluso e' nuovo rispetto ai crossover classici. - `not_drift`: non usa il report Sturmian bloccato, non misura V_c, non usa phi/silver/bronze; il gate 18:55 e' usato come denominatore row-aligned da auditare, non come autorita' conclusiva. ## Re-discovery audit - **Baseline noto piu' vicino**: Brody distribution per interpolazione Poisson-Wigner; Berry-Robnik per mistura regolare/caotica. Rosenzweig-Porter e' nominato come famiglia di crossover Hamiltoniano, non fit eseguito in questo ciclo. - **Cosa viene assorbito dal baseline**: `numeri_primi:cycle_3` e' sia graph bridge sia intermedio classico (`brody_q=0.465`, `w_GUE=0.275`). Su questa riga il Lab non aggiunge fenomeno oltre il fatto che lo stesso campione e' ponte in due lettori. - **Cosa resta Lab-specific**: `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13` sono graph-only bridge: il grafo li mette al confine ma Brody/mixture li legge endpoint-like. - **Cosa limita il claim Lab**: quattro righe sono classic-only intermediate (`zeta_zeros`, `random_matrix`, `cellular_automata`, `brownian_motion`) senza diventare terzo incluso nel grafo. Quindi il parametro classico non basta, ma nemmeno il grafo sostituisce il baseline classico. - **Risultante audit**: il boundary operativo e' una relazione a due lettori: scalar crossover + posizione nel grafo. Uno dei due da solo perde informazione. ## Claim Under Test > Nel perimetro 8/5, il terzo incluso operativo non e' riducibile a Brody q o a una mistura Poisson/GUE-surmise; il residuo vive nel disaccordo row-aligned tra scalare classico e grafo osservabile. ## Question I nodi ponte del grafo 18:55 sono re-discovery di un crossover classico, oppure producono una distinzione residua? ## Ritorno fisico - **Punto fisico sorgente**: transizione spettrale tra caos quantistico repulsivo e indipendenza/localizzazione Poisson. - **Attraversamento matematico**: fit Brody e mistura Poisson/GUE-surmise sulle stesse righe gia' lette dal grafo kNN. - **Punto fisico di ritorno**: negli spettri finiti, una finestra non e' boundary perche' ha q intermedio; e' boundary quando q intermedio e posizione multi-feature del grafo vengono confrontati e il residuo resta nominabile. - **Osservabile/test fisico possibile**: su finestre energetiche sperimentali, calcolare q Brody, peso mistura e kNN multi-feature; separare bridge coincidenti, graph-only e classic-only. - **Se fallisce**: se su dati fisici indipendenti graph-only e classic-only spariscono, il gate Lab si riduce a baseline classico e il terzo incluso non trasferisce. ## Experiment Design - **Script**: `tools/exp_boundary_classical_crossover_audit.py`. - **Input graph**: `tools/data/boundary_graph_curvature_gate_20260515_1855.json`. - **Run**: `python tools/exp_boundary_classical_crossover_audit.py --out tools/data/boundary_classical_crossover_audit_20260515_1904.json`. - **Denominatore**: 13 righe row-aligned dal perimetro BOUNDARY, 8 GUE e 5 Poisson. - **Fit Brody**: grid likelihood su q in [0,1], spacings normalizzati a media 1. - **Fit Berry-Robnik-like**: griglia su peso GUE in mistura CDF `w*GUE_surmise + (1-w)*Poisson`, selezionata per KS minimo. - **Contratto osservabile-operatore**: il ciclo testa concordanza/disaccordo tra scalare classico e graph state; non testa V_c, denominatori Sturmian, unfolding fisico alternativo o Rosenzweig-Porter Hamiltoniano. ## Results | audit state | count | |---|---:| | classic_and_graph_bridge | 1 | | graph_only_bridge | 3 | | classic_only_intermediate | 4 | | endpoint_like | 5 | | row | label | graph_state | Brody q | w_GUE | KS | audit_state | |---|---|---|---:|---:|---:|---| | ising_2d:cycle_1 | GUE | class_interior | 0.090 | 0.070 | 0.428636 | endpoint_like | | pendolo_doppio:cycle_2 | Poisson | cut_edge | 0.000 | 0.000 | 0.268279 | endpoint_like | | numeri_primi:cycle_3 | GUE | third_included_candidate | 0.465 | 0.275 | 0.148459 | classic_and_graph_bridge | | zeta_zeros:cycle_4 | GUE | cut_edge | 1.000 | 0.530 | 0.133555 | classic_only_intermediate | | logistica_biforcazione:cycle_5 | GUE | class_interior | 0.000 | 0.000 | 0.998064 | endpoint_like | | string_vibration:cycle_6 | Poisson | cut_edge | 0.000 | 0.000 | 0.060129 | endpoint_like | | random_matrix:cycle_7 | GUE | cut_edge | 0.975 | 0.475 | 0.119491 | classic_only_intermediate | | cellular_automata:cycle_8 | GUE | class_interior | 1.000 | 0.435 | 0.416708 | classic_only_intermediate | | percolation:cycle_9 | Poisson | third_included_candidate | 0.025 | 0.025 | 0.054635 | graph_only_bridge | | coupled_oscillators:cycle_10 | Poisson | class_interior | 0.000 | 0.000 | 0.079806 | endpoint_like | | reaction_diffusion:cycle_11 | GUE | third_included_candidate | 0.000 | 0.000 | 0.174423 | graph_only_bridge | | brownian_motion:cycle_12 | Poisson | cut_edge | 0.205 | 0.250 | 0.026002 | classic_only_intermediate | | logistica_biforcazione_var_3.5699:cycle_13 | GUE | third_included_candidate | 0.000 | 0.000 | 0.969277 | graph_only_bridge | ## Key Findings 1. Verificato: il denominatore resta quello richiesto, 13 righe con 8 GUE e 5 Poisson. 2. Verificato: un solo nodo ponte del grafo e' anche intermedio classico: `numeri_primi:cycle_3`. 3. Verificato: tre nodi ponte sono graph-only: `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13`. 4. Verificato: quattro righe sono classic-only intermediate senza essere terzo incluso nel grafo: `zeta_zeros:cycle_4`, `random_matrix:cycle_7`, `cellular_automata:cycle_8`, `brownian_motion:cycle_12`. 5. Inferito: il terzo incluso non e' uno scalare di crossover. E' una discrepanza controllata fra lettore classico e posizione multi-osservabile. ## Verdict CONSTRAINT Il boundary trasferisce come audit a due lettori. Brody/Berry-Robnik-like e grafo misurano aspetti diversi dello stesso confine; nessuno dei due chiude il terzo incluso da solo. ## Bicono della scoperta - **Due radici**: parametro classico di crossover; nodo ponte del grafo Lab. - **Singolare**: riga di dominio row-aligned prima della classificazione. - **Invariante di passaggio**: disaccordo nominabile tra `classic_and_graph`, `graph_only`, `classic_only`, `endpoint_like`. - **Campo di possibilita**: possibile = costruire un gate fisico che richiede doppia lettura prima di chiamare boundary; non-possibile = promuovere il grafo 18:55 come scoperta autonoma senza baseline classico. ## Consecutio Il prossimo ciclo utile non deve aggiungere una terza metrica locale. Deve portare il gate a due lettori su un sistema fisico controllato: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre con finestre energetiche. Il risultato da cercare e' se `graph_only` e `classic_only` sopravvivono fuori dal perimetro composito del Lab. ## Ricadute pratiche ssp_value: yes. Lo script crea un audit riusabile per separare re-discovery classica, residuo Lab e endpoint-like in ogni perimetro GUE/Poisson row-aligned. ## Telemetria - No API paid run: `ANTHROPIC_API_KEY` e `OPENAI_API_KEY` non presenti nell'ambiente. - `python tools/dnd_scenario.py --best` eseguito: massimo discriminante `TENS_SCALE_TRASCENDENZA_LIMITE`, ma la direzione viva del campo impone il perimetro BOUNDARY 8/5. - `python -m py_compile tools/exp_boundary_classical_crossover_audit.py` completato. - `python tools/exp_boundary_classical_crossover_audit.py --out tools/data/boundary_classical_crossover_audit_20260515_1904.json` completato. - Worktree gia dirty prima del ciclo; ignorate modifiche non correlate. - Nessun update del seme. - Nessuna promozione e nessun public sync. ## Files - Script: `tools/exp_boundary_classical_crossover_audit.py` - Data: `tools/data/boundary_classical_crossover_audit_20260515_1904.json` - Report: `tools/data/reports/agent_20260515_1904.md` exec /bin/bash -lc "sed -n '220,520p' tools/exp_boundary_graph_curvature_gate.py" in /opt/MM_D-ND succeeded in 0ms: "n_gaps": int(len(gaps)), "observables": {key: round(value, 9) for key, value in obs.items()}, "shuffle_z": {key: round(value, 6) for key, value in z.items()}, } ) except Exception as exc: # noqa: BLE001 - row-level telemetry is part of the result. errors.append( { "domain_window": source.get("domain_window"), "error": type(exc).__name__, "message": str(exc), } ) x = standardized_matrix(rows) geometry = classify_geometry(rows, x, args.k) output = { "experiment": "boundary_graph_curvature_gate", "question": "Does the 8 GUE / 5 Poisson perimeter expose a graph boundary row instead of a clean two-class split?", "observables_registry": OBSERVABLES_REGISTRY_VERSION, "observables_used": FEATURE_NAMES, "params": vars(args), "source_scope": args.scope, "observable_contract": { "claim": "the boundary is operational when row geometry produces cross-label graph nodes with low centroid margin", "observable": "kNN graph position, cross-neighbor fraction, centroid margin, unweighted Forman edge curvature", "operator": "row-aligned domain/window graph in canonical+rigidity+shuffle-z feature space", "generator": "dnd_autoricerca row_spacings via semireal boundary transfer gate", "denominator": "base BOUNDARY rows with source_domain_type in {GUE, Poisson}", "non_possible": "third-included boundary if all cross-label edges vanish or only high-margin class interiors cross", "not_tested": "V_c, Sturmian denominators, analytic source of each domain label", }, "summary": { "rows_analyzed": len(rows), "errors": len(errors), "third_included_candidate_count": len(geometry["third_included_candidates"]), "third_included_candidates": geometry["third_included_candidates"], "edge_counts": geometry["edge_counts"], "curvature": geometry["curvature"], }, "geometry": geometry, "rows": rows, "errors": errors, } out = Path(args.out) out.parent.mkdir(parents=True, exist_ok=True) out.write_text(json.dumps(output, indent=2) + "\n", encoding="utf-8") print(f"observables_registry={OBSERVABLES_REGISTRY_VERSION}") print(f"observables_used={FEATURE_NAMES}") print(f"rows_analyzed={len(rows)} errors={len(errors)}") print(f"label_counts={geometry['label_counts']}") print(f"edge_counts={geometry['edge_counts']}") print(f"curvature={geometry['curvature']}") print(f"third_included_candidates={geometry['third_included_candidates']}") for row in geometry["rows"]: print( f"{row['domain_window']}\t{row['source_domain_type']}\t" f"margin={row['centroid_margin']:.3f}\tcross={row['cross_neighbor_fraction']:.3f}\t" f"state={row['boundary_state']}" ) print(f"saved={out}") return output def main() -> None: parser = argparse.ArgumentParser() parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") parser.add_argument("--n-gaps", type=int, default=2048) parser.add_argument("--min-gaps", type=int, default=64) parser.add_argument("--n-shuffle", type=int, default=64) parser.add_argument("--k", type=int, default=3) parser.add_argument("--seed", type=int, default=20260515) parser.add_argument("--out", default="tools/data/boundary_graph_curvature_gate_20260515_1855.json") args = parser.parse_args() run(args) if __name__ == "__main__": main() exec /bin/bash -lc "ls tools/data | rg 'boundary_.*1855|boundary_.*1904|prescan'" in /opt/MM_D-ND succeeded in 0ms: boundary_classical_crossover_audit_20260515_1904.json boundary_denominator_prescan_20260509_1409.json boundary_denominator_prescan_20260509_1430.json boundary_denominator_prescan_full_20260509_1500.json boundary_graph_curvature_gate_20260515_1855.json exec /bin/bash -lc "test -f tools/data/boundary_classical_crossover_audit_20260515_1904.json && sed -n '1,220p' tools/data/boundary_classical_crossover_audit_20260515_1904.json" in /opt/MM_D-ND succeeded in 0ms: { "experiment": "boundary_classical_crossover_audit", "observable_contract": { "claim": "Lab bridge rows retain residue after comparison with classical crossover scalars", "denominator": "13 rows: 8 GUE and 5 Poisson", "generator": "row_spacings(domain) with graph states imported from boundary_graph_curvature_gate", "non_possible": "Lab-specific bridge if every graph bridge is exactly a classical intermediate and no classical-only intermediate appears", "not_tested": "true Rosenzweig-Porter Hamiltonian flow, physical unfolding alternatives, asymptotic universality", "observable": "row-aligned Brody q, Berry-Robnik-like GUE mixture weight, graph bridge state", "operator": "classical scalar audit over the same 13 BOUNDARY rows used by the graph gate" }, "observables_registry": "none; classical audit coordinates plus prior graph observables", "observables_used": [ "brody_q", "berry_robnick_like_gue_weight", "mixture_ks", "graph_boundary_state_from_1855", "centroid_margin_from_1855", "cross_neighbor_fraction_from_1855" ], "params": { "graph": "tools/data/boundary_graph_curvature_gate_20260515_1855.json", "grid_size": 201, "n_gaps": 2048, "out": "tools/data/boundary_classical_crossover_audit_20260515_1904.json" }, "question": "Do graph bridge rows collapse to standard Brody/Berry-Robnik-like crossover coordinates?", "rows": [ { "audit_state": "endpoint_like", "berry_robnick_like_gue_weight": 0.07, "brody_nll": 318.752193, "brody_q": 0.09, "centroid_margin": 0.335497, "cross_neighbor_fraction": 0.0, "domain": "ising_2d", "domain_window": "ising_2d:cycle_1", "graph_state": "class_interior", "mixture_ks": 0.428636, "n_spacings": 322, "source_domain_type": "GUE" }, { "audit_state": "endpoint_like", "berry_robnick_like_gue_weight": 0.0, "brody_nll": 2048.0, "brody_q": 0.0, "centroid_margin": 0.299159, "cross_neighbor_fraction": 0.333333, "domain": "pendolo_doppio", "domain_window": "pendolo_doppio:cycle_2", "graph_state": "cut_edge", "mixture_ks": 0.268279, "n_spacings": 2048, "source_domain_type": "Poisson" }, { "audit_state": "classic_and_graph_bridge", "berry_robnick_like_gue_weight": 0.275, "brody_nll": 1826.209184, "brody_q": 0.465, "centroid_margin": 0.222754, "cross_neighbor_fraction": 0.25, "domain": "numeri_primi", "domain_window": "numeri_primi:cycle_3", "graph_state": "third_included_candidate", "mixture_ks": 0.148459, "n_spacings": 2048, "source_domain_type": "GUE" }, { "audit_state": "classic_only_intermediate", "berry_robnick_like_gue_weight": 0.53, "brody_nll": 121.495704, "brody_q": 1.0, "centroid_margin": 0.30764, "cross_neighbor_fraction": 0.333333, "domain": "zeta_zeros", "domain_window": "zeta_zeros:cycle_4", "graph_state": "cut_edge", "mixture_ks": 0.133555, "n_spacings": 199, "source_domain_type": "GUE" }, { "audit_state": "endpoint_like", "berry_robnick_like_gue_weight": 0.0, "brody_nll": 691.194523, "brody_q": 0.0, "centroid_margin": 0.163262, "cross_neighbor_fraction": 0.0, "domain": "logistica_biforcazione", "domain_window": "logistica_biforcazione:cycle_5", "graph_state": "class_interior", "mixture_ks": 0.998064, "n_spacings": 2048, "source_domain_type": "GUE" }, { "audit_state": "endpoint_like", "berry_robnick_like_gue_weight": 0.0, "brody_nll": 2048.0, "brody_q": 0.0, "centroid_margin": 0.550789, "cross_neighbor_fraction": 0.5, "domain": "string_vibration", "domain_window": "string_vibration:cycle_6", "graph_state": "cut_edge", "mixture_ks": 0.060129, "n_spacings": 2048, "source_domain_type": "Poisson" }, { "audit_state": "classic_only_intermediate", "berry_robnick_like_gue_weight": 0.475, "brody_nll": 137.982517, "brody_q": 0.975, "centroid_margin": 0.352347, "cross_neighbor_fraction": 0.166667, "domain": "random_matrix", "domain_window": "random_matrix:cycle_7", "graph_state": "cut_edge", "mixture_ks": 0.119491, "n_spacings": 199, "source_domain_type": "GUE" }, { "audit_state": "classic_only_intermediate", "berry_robnick_like_gue_weight": 0.435, "brody_nll": 52.124605, "brody_q": 1.0, "centroid_margin": 0.411955, "cross_neighbor_fraction": 0.0, "domain": "cellular_automata", "domain_window": "cellular_automata:cycle_8", "graph_state": "class_interior", "mixture_ks": 0.416708, "n_spacings": 108, "source_domain_type": "GUE" }, { "audit_state": "graph_only_bridge", "berry_robnick_like_gue_weight": 0.025, "brody_nll": 193.90387, "brody_q": 0.025, "centroid_margin": 0.088647, "cross_neighbor_fraction": 1.0, "domain": "percolation", "domain_window": "percolation:cycle_9", "graph_state": "third_included_candidate", "mixture_ks": 0.054635, "n_spacings": 194, "source_domain_type": "Poisson" }, { "audit_state": "endpoint_like", "berry_robnick_like_gue_weight": 0.0, "brody_nll": 2002.0, "brody_q": 0.0, "centroid_margin": 0.560662, "cross_neighbor_fraction": 0.0, "domain": "coupled_oscillators", "domain_window": "coupled_oscillators:cycle_10", "graph_state": "class_interior", "mixture_ks": 0.079806, "n_spacings": 2002, "source_domain_type": "Poisson" }, { "audit_state": "graph_only_bridge", "berry_robnick_like_gue_weight": 0.0, "brody_nll": 499.0, "brody_q": 0.0, "centroid_margin": 0.114771, "cross_neighbor_fraction": 0.75, "domain": "reaction_diffusion", "domain_window": "reaction_diffusion:cycle_11", "graph_state": "third_included_candidate", "mixture_ks": 0.174423, "n_spacings": 499, "source_domain_type": "GUE" }, { "audit_state": "classic_only_intermediate", "berry_robnick_like_gue_weight": 0.25, "brody_nll": 1997.987436, "brody_q": 0.205, "centroid_margin": 0.438315, "cross_neighbor_fraction": 0.25, "domain": "brownian_motion", "domain_window": "brownian_motion:cycle_12", "graph_state": "cut_edge", "mixture_ks": 0.026002, "n_spacings": 2048, "source_domain_type": "Poisson" }, { "audit_state": "graph_only_bridge", "berry_robnick_like_gue_weight": 0.0, "brody_nll": 1826.006965, "brody_q": 0.0, "centroid_margin": 0.217275, "cross_neighbor_fraction": 0.25, "domain": "logistica_biforcazione_var_3.5699", "domain_window": "logistica_biforcazione_var_3.5699:cycle_13", "graph_state": "third_included_candidate", "mixture_ks": 0.969277, "n_spacings": 2048, "source_domain_type": "GUE" } ], "source_graph": "tools/data/boundary_graph_curvature_gate_20260515_1855.json", "summary": { "audit_counts": { "classic_and_graph_bridge": 1, "classic_only_intermediate": 4, "endpoint_like": 5, "graph_only_bridge": 3 }, "classic_and_graph_bridge": [ codex Il report 19:04 ha già chiuso il confronto Brody/Berry-Robnik. Per non aggiungere una terza metrica locale, preparo un audit di stabilità del gate a due lettori: stessa unità row-aligned, ma perturbando `k`, lunghezza degli spacing e seed degli shuffle; il claim regge solo se i bridge non dipendono da una singola parametrizzazione. apply patch patch: completed /opt/MM_D-ND/tools/exp_boundary_bridge_stability_audit.py diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() codex Lo script è aggiunto. Ora lo compilo e lo eseguo sul perimetro 13 righe; se il costo resta alto per gli shuffle, riduco solo la griglia mantenendo il denominatore invariato. exec /bin/bash -lc "env | rg 'ANTHROPIC_API_KEY|OPENAI_API_KEY' || true" in /opt/MM_D-ND succeeded in 0ms: exec /bin/bash -lc 'python -m py_compile tools/exp_boundary_bridge_stability_audit.py' in /opt/MM_D-ND succeeded in 0ms: diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc 'python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json' in /opt/MM_D-ND diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() codex L’audit sta ancora girando perché richiama il gate grafico molte volte. Non ci sono API key paid nell’ambiente; se termina pulito, userò il suo JSON come unica fonte dei risultati del report. diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() codex La griglia piena è troppo lenta per il ciclo interattivo. La fermo e rilancio un atto minimo coerente: stesso denominatore, ma perturbazioni ridotte su `k` e seed, sufficienti a distinguere ponte stabile da ponte parametrico senza cambiare domanda. 2026-05-15T19:20:31.743365Z ERROR codex_core::tools::router: error=write_stdin failed: stdin is closed for this session; rerun exec_command with tty=true to keep stdin open diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc "pkill -f 'python tools/exp_boundary_bridge_stability_audit.py' || true" in /opt/MM_D-ND exited 143 in 0ms: diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc "ps -ef | rg 'exp_boundary_bridge_stability|boundary_graph_curvature|python'" in /opt/MM_D-ND succeeded in 0ms: root 1 0 0 19:20 ? 00:00:00 /root/.codex-lab/tmp/arg0/codex-arg06amPnY/codex-linux-sandbox --sandbox-policy-cwd /opt/MM_D-ND --command-cwd /opt/MM_D-ND --sandbox-policy {"type":"workspace-write","writable_roots":["/root/.codex-lab/memories"],"network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false} --file-system-sandbox-policy {"kind":"restricted","entries":[{"path":{"type":"special","value":{"kind":"root"}},"access":"read"},{"path":{"type":"special","value":{"kind":"current_working_directory"}},"access":"write"},{"path":{"type":"special","value":{"kind":"slash_tmp"}},"access":"write"},{"path":{"type":"special","value":{"kind":"tmpdir"}},"access":"write"},{"path":{"type":"path","path":"/root/.codex-lab/memories"},"access":"write"},{"path":{"type":"path","path":"/opt/MM_D-ND/.git"},"access":"read"},{"path":{"type":"path","path":"/opt/MM_D-ND/.codex"},"access":"read"}]} --network-sandbox-policy "restricted" -- /bin/bash -c __CODEX_SNAPSHOT_OVERRIDE_SET_0="${CODEX_THREAD_ID+x}" __CODEX_SNAPSHOT_OVERRIDE_0="${CODEX_THREAD_ID-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_0="${ALL_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_0="${ALL_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_1="${BUNDLE_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_1="${BUNDLE_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_2="${BUNDLE_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_2="${BUNDLE_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_3="${BUNDLE_NO_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_3="${BUNDLE_NO_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_4="${CODEX_NETWORK_ALLOW_LOCAL_BINDING+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_4="${CODEX_NETWORK_ALLOW_LOCAL_BINDING-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_5="${CODEX_NETWORK_PROXY_ACTIVE+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_5="${CODEX_NETWORK_PROXY_ACTIVE-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_6="${DOCKER_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_6="${DOCKER_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_7="${DOCKER_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_7="${DOCKER_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_8="${ELECTRON_GET_USE_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_8="${ELECTRON_GET_USE_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_9="${FTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_9="${FTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_10="${HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_10="${HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_11="${HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_11="${HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_12="${NO_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_12="${NO_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_13="${NPM_CONFIG_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_13="${NPM_CONFIG_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_14="${NPM_CONFIG_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_14="${NPM_CONFIG_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_15="${NPM_CONFIG_NOPROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_15="${NPM_CONFIG_NOPROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_16="${NPM_CONFIG_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_16="${NPM_CONFIG_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_17="${PIP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_17="${PIP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_18="${WSS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_18="${WSS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_19="${WS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_19="${WS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_20="${YARN_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_20="${YARN_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_21="${YARN_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_21="${YARN_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_22="${YARN_NO_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_22="${YARN_NO_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_23="${all_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_23="${all_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_24="${ftp_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_24="${ftp_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_25="${http_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_25="${http_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_26="${https_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_26="${https_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_27="${no_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_27="${no_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_28="${npm_config_http_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_28="${npm_config_http_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_29="${npm_config_https_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_29="${npm_config_https_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_30="${npm_config_noproxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_30="${npm_config_noproxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_31="${npm_config_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_31="${npm_config_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_32="${ws_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_32="${ws_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_33="${wss_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_33="${wss_proxy-}" __CODEX_SNAPSHOT_PROXY_ENV_SET="${CODEX_NETWORK_PROXY_ACTIVE+x}" if . '/root/.codex-lab/shell_snapshots/019e2d10-653e-7d33-b352-8b91a1bbf4f2.1778872509769133379.sh' >/dev/null 2>&1; then :; fi if [ -n "${__CODEX_SNAPSHOT_OVERRIDE_SET_0}" ]; then export CODEX_THREAD_ID="${__CODEX_SNAPSHOT_OVERRIDE_0}"; else unset CODEX_THREAD_ID; fi if [ -n "$__CODEX_SNAPSHOT_PROXY_ENV_SET" ] || [ -n "${CODEX_NETWORK_PROXY_ACTIVE+x}" ]; then if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_0}" ]; then export ALL_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_0}"; else unset ALL_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_1}" ]; then export BUNDLE_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_1}"; else unset BUNDLE_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_2}" ]; then export BUNDLE_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_2}"; else unset BUNDLE_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_3}" ]; then export BUNDLE_NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_3}"; else unset BUNDLE_NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_4}" ]; then export CODEX_NETWORK_ALLOW_LOCAL_BINDING="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_4}"; else unset CODEX_NETWORK_ALLOW_LOCAL_BINDING; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_5}" ]; then export CODEX_NETWORK_PROXY_ACTIVE="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_5}"; else unset CODEX_NETWORK_PROXY_ACTIVE; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_6}" ]; then export DOCKER_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_6}"; else unset DOCKER_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_7}" ]; then export DOCKER_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_7}"; else unset DOCKER_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_8}" ]; then export ELECTRON_GET_USE_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_8}"; else unset ELECTRON_GET_USE_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_9}" ]; then export FTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_9}"; else unset FTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_10}" ]; then export HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_10}"; else unset HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_11}" ]; then export HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_11}"; else unset HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_12}" ]; then export NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_12}"; else unset NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_13}" ]; then export NPM_CONFIG_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_13}"; else unset NPM_CONFIG_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_14}" ]; then export NPM_CONFIG_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_14}"; else unset NPM_CONFIG_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_15}" ]; then export NPM_CONFIG_NOPROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_15}"; else unset NPM_CONFIG_NOPROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_16}" ]; then export NPM_CONFIG_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_16}"; else unset NPM_CONFIG_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_17}" ]; then export PIP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_17}"; else unset PIP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_18}" ]; then export WSS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_18}"; else unset WSS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_19}" ]; then export WS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_19}"; else unset WS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_20}" ]; then export YARN_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_20}"; else unset YARN_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_21}" ]; then export YARN_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_21}"; else unset YARN_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_22}" ]; then export YARN_NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_22}"; else unset YARN_NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_23}" ]; then export all_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_23}"; else unset all_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_24}" ]; then export ftp_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_24}"; else unset ftp_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_25}" ]; then export http_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_25}"; else unset http_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_26}" ]; then export https_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_26}"; else unset https_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_27}" ]; then export no_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_27}"; else unset no_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_28}" ]; then export npm_config_http_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_28}"; else unset npm_config_http_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_29}" ]; then export npm_config_https_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_29}"; else unset npm_config_https_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_30}" ]; then export npm_config_noproxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_30}"; else unset npm_config_noproxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_31}" ]; then export npm_config_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_31}"; else unset npm_config_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_32}" ]; then export ws_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_32}"; else unset ws_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_33}" ]; then export wss_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_33}"; else unset wss_proxy; fi fi exec '/bin/bash' -c 'ps -ef | rg '"'"'exp_boundary_bridge_stability|boundary_graph_curvature|python'"'"'' root 2 1 50 19:20 ? 00:00:00 /bin/bash -c ps -ef | rg 'exp_boundary_bridge_stability|boundary_graph_curvature|python' root 4 2 0 19:20 ? 00:00:00 rg exp_boundary_bridge_stability|boundary_graph_curvature|python diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc 'python tools/exp_boundary_bridge_stability_audit.py --n-gaps-values 1024 --seeds 20260515,20260516 --n-shuffle 8 --out tools/data/boundary_bridge_stability_audit_20260515_1915.json' in /opt/MM_D-ND diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() codex Anche la griglia ridotta resta lenta perché il gate esistente rigenera gli spacing a ogni run. Correggo il nodo regressivo nello script: cache delle righe e ricalcolo solo shuffle/feature, così l’audit resta lo stesso ma il ciclo non paga ricostruzioni duplicate. exec /bin/bash -lc "pkill -f 'python tools/exp_boundary_bridge_stability_audit.py' || true" in /opt/MM_D-ND exited 143 in 0ms: diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..a4151663f0501c76a7ad93b18712e0253f9f982d --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,221 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from exp_boundary_graph_curvature_gate import run as run_graph_gate + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + tmp_out = Path(args.tmp_out) + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + graph_args = SimpleNamespace( + scope=args.scope, + n_gaps=n_gaps, + min_gaps=args.min_gaps, + n_shuffle=args.n_shuffle, + k=k, + seed=seed, + out=str(tmp_out), + ) + graph = run_graph_gate(graph_args) + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--tmp-out", default="/tmp/boundary_bridge_stability_tmp.json") + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() apply patch patch: completed /opt/MM_D-ND/tools/exp_boundary_bridge_stability_audit.py diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc "ps -ef | rg 'exp_boundary_bridge_stability|python tools/exp_boundary'" in /opt/MM_D-ND succeeded in 0ms: root 1 0 0 19:23 ? 00:00:00 /root/.codex-lab/tmp/arg0/codex-arg06amPnY/codex-linux-sandbox --sandbox-policy-cwd /opt/MM_D-ND --command-cwd /opt/MM_D-ND --sandbox-policy {"type":"workspace-write","writable_roots":["/root/.codex-lab/memories"],"network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false} --file-system-sandbox-policy {"kind":"restricted","entries":[{"path":{"type":"special","value":{"kind":"root"}},"access":"read"},{"path":{"type":"special","value":{"kind":"current_working_directory"}},"access":"write"},{"path":{"type":"special","value":{"kind":"slash_tmp"}},"access":"write"},{"path":{"type":"special","value":{"kind":"tmpdir"}},"access":"write"},{"path":{"type":"path","path":"/root/.codex-lab/memories"},"access":"write"},{"path":{"type":"path","path":"/opt/MM_D-ND/.git"},"access":"read"},{"path":{"type":"path","path":"/opt/MM_D-ND/.codex"},"access":"read"}]} --network-sandbox-policy "restricted" -- /bin/bash -c __CODEX_SNAPSHOT_OVERRIDE_SET_0="${CODEX_THREAD_ID+x}" __CODEX_SNAPSHOT_OVERRIDE_0="${CODEX_THREAD_ID-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_0="${ALL_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_0="${ALL_PROXY-}" 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__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_25="${http_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_25="${http_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_26="${https_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_26="${https_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_27="${no_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_27="${no_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_28="${npm_config_http_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_28="${npm_config_http_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_29="${npm_config_https_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_29="${npm_config_https_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_30="${npm_config_noproxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_30="${npm_config_noproxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_31="${npm_config_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_31="${npm_config_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_32="${ws_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_32="${ws_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_33="${wss_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_33="${wss_proxy-}" __CODEX_SNAPSHOT_PROXY_ENV_SET="${CODEX_NETWORK_PROXY_ACTIVE+x}" if . '/root/.codex-lab/shell_snapshots/019e2d10-653e-7d33-b352-8b91a1bbf4f2.1778872509769133379.sh' >/dev/null 2>&1; then :; fi if [ -n "${__CODEX_SNAPSHOT_OVERRIDE_SET_0}" ]; then export CODEX_THREAD_ID="${__CODEX_SNAPSHOT_OVERRIDE_0}"; else unset CODEX_THREAD_ID; fi if [ -n "$__CODEX_SNAPSHOT_PROXY_ENV_SET" ] || [ -n "${CODEX_NETWORK_PROXY_ACTIVE+x}" ]; then if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_0}" ]; then export ALL_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_0}"; else unset ALL_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_1}" ]; then export BUNDLE_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_1}"; else unset BUNDLE_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_2}" ]; then export BUNDLE_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_2}"; else unset BUNDLE_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_3}" ]; then export BUNDLE_NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_3}"; else unset BUNDLE_NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_4}" ]; then export CODEX_NETWORK_ALLOW_LOCAL_BINDING="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_4}"; else unset CODEX_NETWORK_ALLOW_LOCAL_BINDING; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_5}" ]; then export CODEX_NETWORK_PROXY_ACTIVE="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_5}"; else unset CODEX_NETWORK_PROXY_ACTIVE; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_6}" ]; then export DOCKER_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_6}"; else unset DOCKER_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_7}" ]; then export DOCKER_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_7}"; else unset DOCKER_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_8}" ]; then export ELECTRON_GET_USE_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_8}"; else unset ELECTRON_GET_USE_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_9}" ]; then export FTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_9}"; else unset FTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_10}" ]; then export HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_10}"; else unset HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_11}" ]; then export HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_11}"; else unset HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_12}" ]; then export NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_12}"; else unset NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_13}" ]; then export NPM_CONFIG_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_13}"; else unset NPM_CONFIG_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_14}" ]; then export NPM_CONFIG_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_14}"; else unset NPM_CONFIG_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_15}" ]; then export NPM_CONFIG_NOPROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_15}"; else unset NPM_CONFIG_NOPROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_16}" ]; then export NPM_CONFIG_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_16}"; else unset NPM_CONFIG_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_17}" ]; then export PIP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_17}"; else unset PIP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_18}" ]; then export WSS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_18}"; else unset WSS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_19}" ]; then export WS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_19}"; else unset WS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_20}" ]; then export YARN_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_20}"; else unset YARN_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_21}" ]; then export YARN_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_21}"; else unset YARN_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_22}" ]; then export YARN_NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_22}"; else unset YARN_NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_23}" ]; then export all_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_23}"; else unset all_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_24}" ]; then export ftp_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_24}"; else unset ftp_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_25}" ]; then export http_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_25}"; else unset http_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_26}" ]; then export https_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_26}"; else unset https_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_27}" ]; then export no_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_27}"; else unset no_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_28}" ]; then export npm_config_http_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_28}"; else unset npm_config_http_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_29}" ]; then export npm_config_https_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_29}"; else unset npm_config_https_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_30}" ]; then export npm_config_noproxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_30}"; else unset npm_config_noproxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_31}" ]; then export npm_config_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_31}"; else unset npm_config_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_32}" ]; then export ws_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_32}"; else unset ws_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_33}" ]; then export wss_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_33}"; else unset wss_proxy; fi fi exec '/bin/bash' -c 'ps -ef | rg '"'"'exp_boundary_bridge_stability|python tools/exp_boundary'"'"'' root 2 1 50 19:23 ? 00:00:00 /bin/bash -c ps -ef | rg 'exp_boundary_bridge_stability|python tools/exp_boundary' root 4 2 0 19:23 ? 00:00:00 rg exp_boundary_bridge_stability|python tools/exp_boundary exec /bin/bash -lc 'python -m py_compile tools/exp_boundary_bridge_stability_audit.py' in /opt/MM_D-ND succeeded in 0ms: diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc 'python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json' in /opt/MM_D-ND diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() succeeded in 123057ms: { "classic_only_stable_graph_absent": [ "cellular_automata:cycle_8" ], "composite_counts": { "parameter_sensitive_bridge+classic_only_intermediate": 1, "parameter_sensitive_bridge+endpoint_like": 1, "stable_graph_bridge+classic_and_graph_bridge": 1, "stable_graph_bridge+classic_only_intermediate": 2, "stable_graph_bridge+endpoint_like": 1, "stable_graph_bridge+graph_only_bridge": 3, "unstable_non_bridge+classic_only_intermediate": 1, "unstable_non_bridge+endpoint_like": 3 }, "graph_reader_runs": 27, "lab_residue_after_stability": true, "rows_analyzed": 13, "stable_classic_and_graph": [ "numeri_primi:cycle_3" ], "stable_graph_only": [ "logistica_biforcazione_var_3.5699:cycle_13", "percolation:cycle_9", "reaction_diffusion:cycle_11" ] } exec /bin/bash -lc "sed -n '1,260p' tools/data/boundary_bridge_stability_audit_20260515_1915.json" in /opt/MM_D-ND succeeded in 0ms: { "experiment": "boundary_bridge_stability_audit", "observable_contract": { "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join" }, "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", "observables_used": [ "graph_bridge_frequency", "cut_edge_frequency", "mean_centroid_margin", "mean_cross_neighbor_fraction", "classical_audit_state", "brody_q", "berry_robnick_like_gue_weight" ], "params": { "classical_audit": "tools/data/boundary_classical_crossover_audit_20260515_1904.json", "k_values": [ 2, 3, 4 ], "min_gaps": 64, "n_gaps_values": [ 512, 1024, 2048 ], "n_shuffle": 32, "scope": "tools/data/boundary_denominator_prescan_full_20260509_1500.json", "seeds": [ 20260515, 20260516, 20260517 ], "total_runs": 27 }, "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", "rows": [ { "berry_robnick_like_gue_weight": 0.25, "brody_q": 0.205, "classical_audit_state": "classic_only_intermediate", "composite_state": "parameter_sensitive_bridge+classic_only_intermediate", "cut_edge_frequency": 0.222222, "domain": "brownian_motion", "domain_window": "brownian_motion:cycle_12", "graph_bridge_frequency": 0.666667, "graph_bridge_hits": 18, "mean_cross_neighbor_fraction": 0.500529, "mean_margin": 0.18755, "source_domain_type": "Poisson", "stability_state": "parameter_sensitive_bridge" }, { "berry_robnick_like_gue_weight": 0.435, "brody_q": 1.0, "classical_audit_state": "classic_only_intermediate", "composite_state": "unstable_non_bridge+classic_only_intermediate", "cut_edge_frequency": 0.037037, "domain": "cellular_automata", "domain_window": "cellular_automata:cycle_8", "graph_bridge_frequency": 0.0, "graph_bridge_hits": 0, "mean_cross_neighbor_fraction": 0.006173, "mean_margin": 0.292791, "source_domain_type": "GUE", "stability_state": "unstable_non_bridge" }, { "berry_robnick_like_gue_weight": 0.0, "brody_q": 0.0, "classical_audit_state": "endpoint_like", "composite_state": "unstable_non_bridge+endpoint_like", "cut_edge_frequency": 1.0, "domain": "coupled_oscillators", "domain_window": "coupled_oscillators:cycle_10", "graph_bridge_frequency": 0.0, "graph_bridge_hits": 0, "mean_cross_neighbor_fraction": 0.413492, "mean_margin": 0.482477, "source_domain_type": "Poisson", "stability_state": "unstable_non_bridge" }, { "berry_robnick_like_gue_weight": 0.07, "brody_q": 0.09, "classical_audit_state": "endpoint_like", "composite_state": "unstable_non_bridge+endpoint_like", "cut_edge_frequency": 0.0, "domain": "ising_2d", "domain_window": "ising_2d:cycle_1", "graph_bridge_frequency": 0.0, "graph_bridge_hits": 0, "mean_cross_neighbor_fraction": 0.0, "mean_margin": 0.292432, "source_domain_type": "GUE", "stability_state": "unstable_non_bridge" }, { "berry_robnick_like_gue_weight": 0.0, "brody_q": 0.0, "classical_audit_state": "endpoint_like", "composite_state": "parameter_sensitive_bridge+endpoint_like", "cut_edge_frequency": 0.0, "domain": "logistica_biforcazione", "domain_window": "logistica_biforcazione:cycle_5", "graph_bridge_frequency": 0.666667, "graph_bridge_hits": 18, "mean_cross_neighbor_fraction": 0.425926, "mean_margin": 0.106132, "source_domain_type": "GUE", "stability_state": "parameter_sensitive_bridge" }, { "berry_robnick_like_gue_weight": 0.0, "brody_q": 0.0, "classical_audit_state": "graph_only_bridge", "composite_state": "stable_graph_bridge+graph_only_bridge", "cut_edge_frequency": 0.0, "domain": "logistica_biforcazione_var_3.5699", "domain_window": "logistica_biforcazione_var_3.5699:cycle_13", "graph_bridge_frequency": 1.0, "graph_bridge_hits": 27, "mean_cross_neighbor_fraction": 0.540741, "mean_margin": 0.087791, "source_domain_type": "GUE", "stability_state": "stable_graph_bridge" }, { "berry_robnick_like_gue_weight": 0.275, "brody_q": 0.465, "classical_audit_state": "classic_and_graph_bridge", "composite_state": "stable_graph_bridge+classic_and_graph_bridge", "cut_edge_frequency": 0.0, "domain": "numeri_primi", "domain_window": "numeri_primi:cycle_3", "graph_bridge_frequency": 1.0, "graph_bridge_hits": 27, "mean_cross_neighbor_fraction": 0.297795, "mean_margin": 0.081651, "source_domain_type": "GUE", "stability_state": "stable_graph_bridge" }, { "berry_robnick_like_gue_weight": 0.0, "brody_q": 0.0, "classical_audit_state": "endpoint_like", "composite_state": "stable_graph_bridge+endpoint_like", "cut_edge_frequency": 0.0, "domain": "pendolo_doppio", "domain_window": "pendolo_doppio:cycle_2", "graph_bridge_frequency": 0.888889, "graph_bridge_hits": 24, "mean_cross_neighbor_fraction": 0.369929, "mean_margin": 0.232945, "source_domain_type": "Poisson", "stability_state": "stable_graph_bridge" }, { "berry_robnick_like_gue_weight": 0.025, "brody_q": 0.025, "classical_audit_state": "graph_only_bridge", "composite_state": "stable_graph_bridge+graph_only_bridge", "cut_edge_frequency": 0.0, "domain": "percolation", "domain_window": "percolation:cycle_9", "graph_bridge_frequency": 1.0, "graph_bridge_hits": 27, "mean_cross_neighbor_fraction": 0.907584, "mean_margin": 0.11104, "source_domain_type": "Poisson", "stability_state": "stable_graph_bridge" }, { "berry_robnick_like_gue_weight": 0.475, "brody_q": 0.975, "classical_audit_state": "classic_only_intermediate", "composite_state": "stable_graph_bridge+classic_only_intermediate", "cut_edge_frequency": 0.222222, "domain": "random_matrix", "domain_window": "random_matrix:cycle_7", "graph_bridge_frequency": 0.777778, "graph_bridge_hits": 21, "mean_cross_neighbor_fraction": 0.291108, "mean_margin": 0.110792, "source_domain_type": "GUE", "stability_state": "stable_graph_bridge" }, { "berry_robnick_like_gue_weight": 0.0, "brody_q": 0.0, "classical_audit_state": "graph_only_bridge", "composite_state": "stable_graph_bridge+graph_only_bridge", "cut_edge_frequency": 0.0, "domain": "reaction_diffusion", "domain_window": "reaction_diffusion:cycle_11", "graph_bridge_frequency": 1.0, "graph_bridge_hits": 27, "mean_cross_neighbor_fraction": 0.764815, "mean_margin": 0.107751, "source_domain_type": "GUE", "stability_state": "stable_graph_bridge" }, { "berry_robnick_like_gue_weight": 0.0, "brody_q": 0.0, "classical_audit_state": "endpoint_like", "composite_state": "unstable_non_bridge+endpoint_like", "cut_edge_frequency": 0.851852, "domain": "string_vibration", "domain_window": "string_vibration:cycle_6", "graph_bridge_frequency": 0.0, "graph_bridge_hits": 0, "mean_cross_neighbor_fraction": 0.38542, "mean_margin": 0.695893, "source_domain_type": "Poisson", "stability_state": "unstable_non_bridge" }, { "berry_robnick_like_gue_weight": 0.53, "brody_q": 1.0, "classical_audit_state": "classic_only_intermediate", "composite_state": "stable_graph_bridge+classic_only_intermediate", "cut_edge_frequency": 0.0, "domain": "zeta_zeros", "domain_window": "zeta_zeros:cycle_4", "graph_bridge_frequency": 0.888889, "graph_bridge_hits": 24, "mean_cross_neighbor_fraction": 0.383921, "mean_margin": 0.115799, "source_domain_type": "GUE", "stability_state": "stable_graph_bridge" } ], "runs": [ { "cross_edges": 6, "k": 2, "n_gaps": 512, "seed": 20260515, "third_included_candidates": [ "brownian_motion:cycle_12", "logistica_biforcazione:cycle_5", "logistica_biforcazione_var_3.5699:cycle_13", "numeri_primi:cycle_3", "percolation:cycle_9", "random_matrix:cycle_7", "reaction_diffusion:cycle_11", "zeta_zeros:cycle_4" ] }, { "cross_edges": 6, exec /bin/bash -lc 'git status --short' in /opt/MM_D-ND succeeded in 0ms: M applications/INDEX.draft.json M docs/guides/lab_current_state_logic_2026-05-08.md M tools/LAB_AGENT_CONTEXT.md M tools/build_agent_field.py M tools/build_lab_graph.py M tools/data/agent_field_live.md M tools/data/b2_apply_log.jsonl M tools/data/ciclo_memoria.json M tools/data/consecutio.json M tools/data/consecutio_processata.json M tools/data/domandatore_pre_cycle.json M tools/data/domande_fondamentali.json M tools/data/g1_log.jsonl M tools/data/g2_log.jsonl M tools/data/graph_completion/latest.json M tools/data/incrocio_risultato.json M tools/data/knowledge_state.json M tools/data/lab_bridge_issues.jsonl M tools/data/lab_data.json M tools/data/lab_graph.json M tools/data/lab_health.json M tools/data/lab_session_log.jsonl M tools/data/pipeline_state.json M tools/data/ponti_evoluti.json M tools/data/repairs/repair_run_log.jsonl M tools/data/reports/latest.md M tools/data/seme.json D tools/data/seme_archive/piano_37.json D tools/data/seme_archive/piano_38.json D tools/data/seme_archive/piano_4.json D tools/data/seme_archive/piano_5.json D tools/data/seme_archive/piano_6.json D tools/data/seme_archive/piano_7.json D tools/data/seme_archive/piano_8.json D tools/data/seme_archive/piano_9.json M tools/data/seme_backup_pre_run.json M tools/data/tm1_figures/tensions.json M tools/data/tm1_figures/tensions_raw.json M tools/data/valutatore_log.jsonl M tools/evolution_report.md M tools/graph_completion_compiler.py M tools/lab_agent.sh M tools/lab_falsifier.py ?? applications/scoperte/20260513_0330_prime-vs-mod6-sr-boundary_auto/ ?? applications/scoperte/20260514_1330_sr-residual-width-audit_auto/ ?? applications/scoperte/20260514_1631_chiusura-tester-rimbalzo-fisico-w6_auto/ ?? applications/scoperte/20260514_1640_rafforzamento-tester-fisico-goegue-n-curve_auto/ ?? applications/scoperte/20260515_1712_primemod6-generative-null-w2048_auto/ ?? applications/scoperte/20260515_1816_v2-generator-scaling-gate_auto/ ?? applications/scoperte/20260515_1904_boundary-classical-crossover-audit_auto/ ?? applications/soluzioni/20260513_0330_prime-vs-mod6-sr-boundary/ ?? applications/soluzioni/20260514_1330_sr-residual-width-audit/ ?? applications/soluzioni/20260514_1631_chiusura-tester-rimbalzo-fisico-w6/ ?? applications/soluzioni/20260514_1640_rafforzamento-tester-fisico-goegue-n-curve/ ?? applications/soluzioni/20260515_1712_primemod6-generative-null-w2048/ ?? applications/soluzioni/20260515_1816_v2-generator-scaling-gate/ ?? applications/soluzioni/20260515_1904_boundary-classical-crossover-audit/ ?? docs/guides/lab_preflight_agent_2026-05-14.md ?? docs/operations/ ?? tools/build_safe_agent_field_preview.py ?? tools/compose_filtered_field_preview.py ?? tools/compose_supervised_entry_preview.py ?? tools/data/aeternitas/aeternitas_20260512_033539.json ?? tools/data/aeternitas/aeternitas_20260513_033605.json ?? tools/data/aeternitas/aeternitas_20260514_033420.json ?? tools/data/aeternitas/aeternitas_20260514_133424.json ?? tools/data/aeternitas/aeternitas_20260514_150454.json ?? tools/data/aeternitas/aeternitas_20260514_161058.json ?? tools/data/aeternitas/aeternitas_20260514_161719.json ?? tools/data/aeternitas/aeternitas_20260514_163527.json ?? tools/data/aeternitas/aeternitas_20260514_164509.json ?? tools/data/aeternitas/aeternitas_20260514_165437.json ?? tools/data/aeternitas/aeternitas_20260514_170109.json ?? tools/data/aeternitas/aeternitas_20260514_171152.json ?? tools/data/aeternitas/aeternitas_20260514_185450.json ?? tools/data/aeternitas/aeternitas_20260515_162727.json ?? tools/data/aeternitas/aeternitas_20260515_165116.json ?? tools/data/aeternitas/aeternitas_20260515_170328.json ?? tools/data/aeternitas/aeternitas_20260515_171005.json ?? tools/data/aeternitas/aeternitas_20260515_171725.json ?? tools/data/aeternitas/aeternitas_20260515_172913.json ?? tools/data/aeternitas/aeternitas_20260515_174023.json ?? tools/data/aeternitas/aeternitas_20260515_175045.json ?? tools/data/aeternitas/aeternitas_20260515_180306.json ?? tools/data/aeternitas/aeternitas_20260515_181257.json ?? tools/data/aeternitas/aeternitas_20260515_182126.json ?? tools/data/aeternitas/aeternitas_20260515_183111.json ?? tools/data/aeternitas/aeternitas_20260515_190118.json ?? tools/data/aeternitas/aeternitas_20260515_191018.json ?? tools/data/agent_field_entry_supervised.md ?? tools/data/anderson3d_component_state_interface_input_20260514_1850.json ?? tools/data/aubry_binary_grammar_surrogate_gate_20260515_1807.json ?? tools/data/aubry_boundary_phase_transport_gate_20260515_1745.json ?? tools/data/aubry_cosine_boundary_counter_gate_20260515_1758.json ?? tools/data/aubry_v2_generator_scaling_gate_20260515_1816.json ?? tools/data/biconi/bicono_20260512_0330.json ?? tools/data/biconi/bicono_20260513_0330.json ?? tools/data/biconi/bicono_20260514_0330.json ?? tools/data/biconi/bicono_20260514_1330.json ?? tools/data/biconi/bicono_20260514_1458.json ?? tools/data/biconi/bicono_20260514_1605.json ?? tools/data/biconi/bicono_20260514_1612.json ?? tools/data/biconi/bicono_20260514_1631.json ?? tools/data/biconi/bicono_20260514_1640.json ?? tools/data/biconi/bicono_20260514_1649.json ?? tools/data/biconi/bicono_20260514_1656.json ?? tools/data/biconi/bicono_20260514_1701.json ?? tools/data/biconi/bicono_20260514_1850.json ?? tools/data/biconi/bicono_20260515_1623.json ?? tools/data/biconi/bicono_20260515_1647.json ?? tools/data/biconi/bicono_20260515_1659.json ?? tools/data/biconi/bicono_20260515_1705.json ?? tools/data/biconi/bicono_20260515_1712.json ?? tools/data/biconi/bicono_20260515_1724.json ?? tools/data/biconi/bicono_20260515_1734.json ?? tools/data/biconi/bicono_20260515_1745.json ?? tools/data/biconi/bicono_20260515_1758.json ?? tools/data/biconi/bicono_20260515_1807.json ?? tools/data/biconi/bicono_20260515_1816.json ?? tools/data/biconi/bicono_20260515_1826.json ?? tools/data/biconi/bicono_20260515_1855.json ?? tools/data/biconi/bicono_20260515_1904.json ?? tools/data/boundary_bridge_stability_audit_20260515_1915.json ?? tools/data/boundary_classical_crossover_audit_20260515_1904.json ?? tools/data/boundary_graph_curvature_gate_20260515_1855.json ?? tools/data/component_state_anderson3d_interface_20260514_1850.json ?? tools/data/component_state_anderson3d_interface_20260514_1850.trace.jsonl ?? tools/data/component_state_fit_ready_20260514_1649.json ?? tools/data/component_state_interface_smoke_20260514_1649.json ?? tools/data/component_state_interface_smoke_20260514_1649.trace.jsonl ?? tools/data/component_state_interface_smoke_input_20260514_1649.json ?? tools/data/domandatore/domandatore_20260512_0330.json ?? tools/data/domandatore/domandatore_20260512_0345.json ?? tools/data/domandatore/domandatore_20260513_0330.json ?? tools/data/domandatore/domandatore_20260513_0345.json ?? tools/data/domandatore/domandatore_20260514_0330.json ?? tools/data/domandatore/domandatore_20260514_0345.json ?? tools/data/domandatore/domandatore_20260514_1330.json ?? tools/data/domandatore/domandatore_20260514_1458.json ?? tools/data/domandatore/domandatore_20260515_0345.json ?? tools/data/domandatore/domandatore_20260515_1623.json ?? tools/data/domandatore/domandatore_20260515_1647.json ?? tools/data/domandatore/domandatore_20260515_1659.json ?? tools/data/evolution/evolution_20260512_0330.md ?? tools/data/evolution/evolution_20260513_0330.md ?? tools/data/evolution/evolution_20260514_0330.md ?? tools/data/evolution/evolution_20260514_1330.md ?? tools/data/evolution/evolution_20260514_1458.md ?? tools/data/evolution/evolution_20260514_1605.md ?? tools/data/evolution/evolution_20260514_1612.md ?? tools/data/evolution/evolution_20260514_1631.md ?? tools/data/evolution/evolution_20260514_1640.md ?? tools/data/evolution/evolution_20260514_1649.md ?? tools/data/evolution/evolution_20260514_1656.md ?? tools/data/evolution/evolution_20260514_1701.md ?? tools/data/evolution/evolution_20260514_1850.md ?? tools/data/evolution/evolution_20260515_1623.md ?? tools/data/evolution/evolution_20260515_1647.md ?? tools/data/evolution/evolution_20260515_1659.md ?? tools/data/evolution/evolution_20260515_1705.md ?? tools/data/evolution/evolution_20260515_1712.md ?? tools/data/evolution/evolution_20260515_1724.md ?? tools/data/evolution/evolution_20260515_1734.md ?? tools/data/evolution/evolution_20260515_1745.md ?? tools/data/evolution/evolution_20260515_1758.md ?? tools/data/evolution/evolution_20260515_1807.md ?? tools/data/evolution/evolution_20260515_1816.md ?? tools/data/evolution/evolution_20260515_1826.md ?? tools/data/evolution/evolution_20260515_1855.md ?? tools/data/evolution/evolution_20260515_1904.md ?? tools/data/graph_completion/graph_completion_20260512_0330.json ?? tools/data/graph_completion/graph_completion_20260513_0330.json ?? tools/data/graph_completion/graph_completion_20260514_0330.json ?? tools/data/graph_completion/graph_completion_20260514_1330.json ?? tools/data/graph_completion/graph_completion_20260514_1458.json ?? tools/data/graph_completion/graph_completion_20260514_1605.json ?? tools/data/graph_completion/graph_completion_20260514_1612.json ?? tools/data/graph_completion/graph_completion_20260514_1631.json ?? tools/data/graph_completion/graph_completion_20260514_1640.json ?? tools/data/graph_completion/graph_completion_20260514_1649.json ?? tools/data/graph_completion/graph_completion_20260514_1656.json ?? tools/data/graph_completion/graph_completion_20260514_1701.json ?? tools/data/graph_completion/graph_completion_20260514_1850.json ?? tools/data/graph_completion/graph_completion_20260515_1623.json ?? tools/data/graph_completion/graph_completion_20260515_1647.json ?? tools/data/graph_completion/graph_completion_20260515_1659.json ?? tools/data/graph_completion/graph_completion_20260515_1705.json ?? tools/data/graph_completion/graph_completion_20260515_1712.json ?? tools/data/graph_completion/graph_completion_20260515_1724.json ?? tools/data/graph_completion/graph_completion_20260515_1734.json ?? tools/data/graph_completion/graph_completion_20260515_1745.json ?? tools/data/graph_completion/graph_completion_20260515_1758.json ?? tools/data/graph_completion/graph_completion_20260515_1807.json ?? tools/data/graph_completion/graph_completion_20260515_1816.json ?? tools/data/graph_completion/graph_completion_20260515_1904.json ?? tools/data/incrocio_20260512_0330.json ?? tools/data/incrocio_20260513_0330.json ?? tools/data/incrocio_20260514_0330.json ?? tools/data/incrocio_20260514_1330.json ?? tools/data/incrocio_20260514_1458.json ?? tools/data/incrocio_20260514_1605.json ?? tools/data/incrocio_20260514_1612.json ?? tools/data/incrocio_20260514_1631.json ?? tools/data/incrocio_20260514_1640.json ?? tools/data/incrocio_20260514_1649.json ?? tools/data/incrocio_20260514_1656.json ?? tools/data/incrocio_20260514_1701.json ?? tools/data/incrocio_20260514_1850.json ?? tools/data/incrocio_20260515_1623.json ?? tools/data/incrocio_20260515_1647.json ?? tools/data/incrocio_20260515_1659.json ?? tools/data/incrocio_20260515_1705.json ?? tools/data/incrocio_20260515_1712.json ?? tools/data/incrocio_20260515_1724.json ?? tools/data/incrocio_20260515_1734.json ?? tools/data/incrocio_20260515_1745.json ?? tools/data/incrocio_20260515_1758.json ?? tools/data/incrocio_20260515_1807.json ?? tools/data/incrocio_20260515_1816.json ?? tools/data/incrocio_20260515_1826.json ?? tools/data/incrocio_20260515_1855.json ?? tools/data/incrocio_20260515_1904.json ?? tools/data/incrocio_20260515_1915.json ?? tools/data/operator_directives_consumed/operator_directive_20260514_1612.md ?? tools/data/operator_directives_consumed/operator_directive_20260514_1631.md ?? tools/data/operator_directives_consumed/operator_directive_20260514_1640.md ?? tools/data/operator_directives_consumed/operator_directive_20260514_1649.md ?? tools/data/operator_directives_consumed/operator_directive_20260514_1656.md ?? tools/data/operator_directives_consumed/operator_directive_20260514_1701.md ?? tools/data/operator_directives_consumed/operator_directive_20260514_1850.md ?? tools/data/photonic_boundary_third_included_gate_20260515_1734.json ?? tools/data/physical_sr_residue_bounce_20260514_1612.json ?? tools/data/physical_sr_residue_bounce_20260514_1612.trace.jsonl ?? tools/data/physical_sr_residue_bounce_20260514_1631_w6.json ?? tools/data/physical_sr_residue_bounce_20260514_1631_w6.trace.jsonl ?? tools/data/physical_sr_residue_bounce_20260514_1640_goe_gue_ncurve.json ?? tools/data/physical_sr_residue_bounce_20260514_1640_goe_gue_ncurve.trace.jsonl ?? tools/data/preflight/ ?? tools/data/prime_sr_persistent_boundary_20260512_0330.json ?? tools/data/prime_sr_persistent_boundary_20260512_0330_seedcheck.json ?? tools/data/prime_vs_mod6_sr_boundary_20260513_0330.json ?? tools/data/prime_vs_mod6_sr_boundary_20260513_0330_seedcheck.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_0330.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_0330.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_0330_seedcheck.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_0330_seedcheck.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1330_w1024.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1330_w1024.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1330_w2048.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1330_w2048.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1330_w512.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1330_w512.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1458_w4096.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1458_w4096.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1458_w4096_dense.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1458_w4096_dense.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1458_w8192_dense.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1458_w8192_dense.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1605_w16384.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1605_w16384.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1605_w4096.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1605_w4096.trace.jsonl ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1605_w8192.json ?? tools/data/prime_vs_mod6_sr_boundary_20260514_1605_w8192.trace.jsonl ?? tools/data/promotions/promotion_20260513_0330.json ?? tools/data/promotions/promotion_20260514_1330.json ?? tools/data/promotions/promotion_20260514_1631.json ?? tools/data/promotions/promotion_20260514_1640.json ?? tools/data/promotions/promotion_20260514_1656.json ?? tools/data/promotions/promotion_20260515_1712.json ?? tools/data/promotions/promotion_20260515_1758.json ?? tools/data/promotions/promotion_20260515_1816.json ?? tools/data/promotions/promotion_20260515_1904.json ?? tools/data/quasiperiodic_grammar_scale_gate_20260514_1701.json ?? tools/data/quasiperiodic_vc_lattice_gate_20260515_1724.json ?? tools/data/repairs/repair_20260512_0330_decision.json ?? tools/data/repairs/repair_20260513_0330_decision.json ?? tools/data/repairs/repair_20260514_0330_decision.json ?? tools/data/repairs/repair_20260514_1330_decision.json ?? tools/data/repairs/repair_20260514_1458_decision.json ?? tools/data/repairs/repair_20260514_1605_decision.json ?? tools/data/repairs/repair_20260514_1612_decision.json ?? tools/data/repairs/repair_20260514_1631_decision.json ?? tools/data/repairs/repair_20260514_1640_decision.json ?? tools/data/repairs/repair_20260514_1649_decision.json ?? tools/data/repairs/repair_20260514_1656.json ?? tools/data/repairs/repair_20260514_1656.md ?? tools/data/repairs/repair_20260514_1656_decision.json ?? tools/data/repairs/repair_20260514_1850_decision.json ?? tools/data/reports/agent_20260512_0330.md ?? tools/data/reports/agent_20260513_0330.md ?? tools/data/reports/agent_20260514_0330.md ?? tools/data/reports/agent_20260514_1330.md ?? tools/data/reports/agent_20260514_1458.md ?? tools/data/reports/agent_20260514_1605.md ?? tools/data/reports/agent_20260514_1612.md ?? tools/data/reports/agent_20260514_1631.md ?? tools/data/reports/agent_20260514_1640.md ?? tools/data/reports/agent_20260514_1649.md ?? tools/data/reports/agent_20260514_1656.md ?? tools/data/reports/agent_20260514_1701.md ?? tools/data/reports/agent_20260514_1850.md ?? tools/data/reports/agent_20260515_1623.md ?? tools/data/reports/agent_20260515_1647.md ?? tools/data/reports/agent_20260515_1659.md ?? tools/data/reports/agent_20260515_1705.md ?? tools/data/reports/agent_20260515_1712.md ?? tools/data/reports/agent_20260515_1724.md ?? tools/data/reports/agent_20260515_1734.md ?? tools/data/reports/agent_20260515_1745.md ?? tools/data/reports/agent_20260515_1758.md ?? tools/data/reports/agent_20260515_1807.md ?? tools/data/reports/agent_20260515_1816.md ?? tools/data/reports/agent_20260515_1826.md ?? tools/data/reports/agent_20260515_1855.md ?? tools/data/reports/agent_20260515_1904.md ?? tools/data/reports/ddf_20260512_0405.json ?? tools/data/reports/ddf_20260513_0405.json ?? tools/data/reports/ddf_20260514_0405.json ?? tools/data/reports/ddf_20260515_0405.json ?? tools/data/reports/falsifier_20260512_0330.json ?? tools/data/reports/falsifier_20260513_0330.json ?? tools/data/reports/falsifier_20260514_0330.json ?? tools/data/reports/falsifier_20260514_1330.json ?? tools/data/reports/falsifier_20260514_1458.json ?? tools/data/reports/falsifier_20260514_1605.json ?? tools/data/reports/falsifier_20260514_1612.json ?? tools/data/reports/falsifier_20260514_1631.json ?? tools/data/reports/falsifier_20260514_1640.json ?? tools/data/reports/falsifier_20260514_1649.json ?? tools/data/reports/falsifier_20260514_1656.json ?? tools/data/reports/falsifier_20260514_1701.json ?? tools/data/reports/falsifier_20260514_1850.json ?? tools/data/reports/falsifier_20260515_1623.json ?? tools/data/reports/falsifier_20260515_1647.json ?? tools/data/reports/falsifier_20260515_1659.json ?? tools/data/reports/falsifier_20260515_1705.json ?? tools/data/reports/falsifier_20260515_1712.json ?? tools/data/reports/falsifier_20260515_1712.raw.txt ?? tools/data/reports/falsifier_20260515_1724.json ?? tools/data/reports/falsifier_20260515_1734.json ?? tools/data/reports/falsifier_20260515_1745.json ?? tools/data/reports/falsifier_20260515_1758.json ?? tools/data/reports/falsifier_20260515_1807.json ?? tools/data/reports/falsifier_20260515_1816.json ?? tools/data/reports/falsifier_20260515_1826.json ?? tools/data/reports/falsifier_20260515_1855.json ?? tools/data/reports/falsifier_20260515_1904.json ?? tools/data/reports/loop_guard_20260512_0330.json ?? tools/data/reports/loop_guard_20260513_0330.json ?? tools/data/reports/loop_guard_20260514_0330.json ?? tools/data/reports/loop_guard_20260514_1330.json ?? tools/data/reports/loop_guard_20260514_1458.json ?? tools/data/reports/loop_guard_20260514_1605.json ?? tools/data/reports/loop_guard_20260514_1612.json ?? tools/data/reports/loop_guard_20260514_1631.json ?? tools/data/reports/loop_guard_20260514_1640.json ?? tools/data/reports/loop_guard_20260514_1649.json ?? tools/data/reports/loop_guard_20260514_1656.json ?? tools/data/reports/loop_guard_20260514_1701.json ?? tools/data/reports/loop_guard_20260514_1850.json ?? tools/data/reports/loop_guard_20260515_1623.json ?? tools/data/reports/loop_guard_20260515_1647.json ?? tools/data/reports/loop_guard_20260515_1659.json ?? tools/data/reports/loop_guard_20260515_1705.json ?? tools/data/reports/loop_guard_20260515_1712.json ?? tools/data/reports/loop_guard_20260515_1724.json ?? tools/data/reports/loop_guard_20260515_1734.json ?? tools/data/reports/loop_guard_20260515_1745.json ?? tools/data/reports/loop_guard_20260515_1758.json ?? tools/data/reports/loop_guard_20260515_1807.json ?? tools/data/reports/loop_guard_20260515_1816.json ?? tools/data/reports/loop_guard_20260515_1826.json ?? tools/data/reports/loop_guard_20260515_1855.json ?? tools/data/reports/loop_guard_20260515_1904.json ?? tools/data/reports/quarantine_manifest.json ?? tools/data/restore_backups/ ?? tools/data/seme_backup_b2_20260512_033557.json ?? tools/data/seme_backup_b2_20260513_033622.json ?? tools/data/seme_backup_b2_20260514_150530.json ?? tools/data/seme_backup_b2_20260514_161119.json ?? tools/data/seme_backup_b2_20260515_180327.json ?? tools/data/sturmian_denominator_alignment_gate_20260515_1826.json ?? tools/data/tool_contracts/ ?? tools/data/veritas/veritas_20260512_033539.json ?? tools/data/veritas/veritas_20260513_033605.json ?? tools/data/veritas/veritas_20260514_033420.json ?? tools/data/veritas/veritas_20260514_133424.json ?? tools/data/veritas/veritas_20260514_150454.json ?? tools/data/veritas/veritas_20260514_161058.json ?? tools/data/veritas/veritas_20260514_161719.json ?? tools/data/veritas/veritas_20260514_163527.json ?? tools/data/veritas/veritas_20260514_164509.json ?? tools/data/veritas/veritas_20260514_165437.json ?? tools/data/veritas/veritas_20260514_170109.json ?? tools/data/veritas/veritas_20260514_171152.json ?? tools/data/veritas/veritas_20260514_185450.json ?? tools/data/veritas/veritas_20260515_162727.json ?? tools/data/veritas/veritas_20260515_165116.json ?? tools/data/veritas/veritas_20260515_170328.json ?? tools/data/veritas/veritas_20260515_171005.json ?? tools/data/veritas/veritas_20260515_171725.json ?? tools/data/veritas/veritas_20260515_172913.json ?? tools/data/veritas/veritas_20260515_174023.json ?? tools/data/veritas/veritas_20260515_175045.json ?? tools/data/veritas/veritas_20260515_180306.json ?? tools/data/veritas/veritas_20260515_181257.json ?? tools/data/veritas/veritas_20260515_182126.json ?? tools/data/veritas/veritas_20260515_183111.json ?? tools/data/veritas/veritas_20260515_190118.json ?? tools/data/veritas/veritas_20260515_191018.json ?? tools/exp_aubry_binary_grammar_surrogate_gate.py ?? tools/exp_aubry_boundary_phase_transport_gate.py ?? tools/exp_aubry_cosine_boundary_counter_gate.py ?? tools/exp_aubry_v2_generator_scaling_gate.py ?? tools/exp_boundary_bridge_stability_audit.py ?? tools/exp_boundary_classical_crossover_audit.py ?? tools/exp_boundary_graph_curvature_gate.py ?? tools/exp_photonic_boundary_third_included_gate.py ?? tools/exp_physical_sr_residue_bounce.py ?? tools/exp_prime_sr_persistent_boundary.py ?? tools/exp_prime_vs_mod6_sr_boundary.py ?? tools/exp_quasiperiodic_grammar_scale_gate.py ?? tools/exp_sturmian_denominator_alignment_gate.py ?? tools/field_coherence_preflight.py ?? tools/field_rebuild_risk_map.py ?? tools/lab_preflight_agent.py ?? tools/lab_tool_contract.py ?? tools/prime_mod6_counter_null_audit.py ?? tools/prime_mod6_generative_null_audit.py ?? tools/prime_mod6_null_fairness_audit.py ?? tools/prime_mod6_pipeline_closeout.py ?? tools/selector_authority_matrix.py ?? tools/stale_field_source_map.py diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() codex I risultati dicono che il gate non è una lista fissa di quattro righe: i tre `graph_only` del 19:04 restano stabili 27/27, ma `zeta_zeros` e `random_matrix` entrano come bridge stabili quando si perturba il lettore. Scrivo il report come vincolo sul gate, non come conferma della soglia precedente. succeeded in 374594ms: observables_registry=1.0.0-2026-05-06 observables_used=['SR', 'SR2', 'L1', 'L2', 'triple_var', 'SR_local_rigidity', 'z_SR', 'z_SR2', 'z_L1', 'z_L2', 'z_triple_var'] rows_analyzed=13 errors=0 label_counts={'GUE': 8, 'Poisson': 5} edge_counts={'total': 18, 'cross_label': 4, 'same_label': 14} curvature={'cross_edge_mean': -1.5, 'same_edge_mean': -2.0} third_included_candidates=['numeri_primi:cycle_3', 'zeta_zeros:cycle_4', 'percolation:cycle_9', 'logistica_biforcazione_var_3.5699:cycle_13'] ising_2d:cycle_1 GUE margin=0.356 cross=0.000 state=class_interior pendolo_doppio:cycle_2 Poisson margin=0.264 cross=0.333 state=cut_edge numeri_primi:cycle_3 GUE margin=0.042 cross=0.333 state=third_included_candidate zeta_zeros:cycle_4 GUE margin=0.058 cross=0.250 state=third_included_candidate logistica_biforcazione:cycle_5 GUE margin=0.097 cross=0.000 state=class_interior string_vibration:cycle_6 Poisson margin=0.581 cross=0.250 state=cut_edge random_matrix:cycle_7 GUE margin=0.113 cross=0.000 state=class_interior cellular_automata:cycle_8 GUE margin=0.207 cross=0.000 state=class_interior percolation:cycle_9 Poisson margin=0.171 cross=1.000 state=third_included_candidate coupled_oscillators:cycle_10 Poisson margin=0.316 cross=0.000 state=class_interior reaction_diffusion:cycle_11 GUE margin=0.088 cross=0.000 state=class_interior brownian_motion:cycle_12 Poisson margin=0.283 cross=0.000 state=class_interior logistica_biforcazione_var_3.5699:cycle_13 GUE margin=0.044 cross=1.000 state=third_included_candidate saved=/tmp/boundary_bridge_stability_tmp.json observables_registry=1.0.0-2026-05-06 observables_used=['SR', 'SR2', 'L1', 'L2', 'triple_var', 'SR_local_rigidity', 'z_SR', 'z_SR2', 'z_L1', 'z_L2', 'z_triple_var'] rows_analyzed=13 errors=0 label_counts={'GUE': 8, 'Poisson': 5} edge_counts={'total': 19, 'cross_label': 5, 'same_label': 14} curvature={'cross_edge_mean': -1.8, 'same_edge_mean': -2.357143} third_included_candidates=['numeri_primi:cycle_3', 'reaction_diffusion:cycle_11', 'logistica_biforcazione_var_3.5699:cycle_13'] ising_2d:cycle_1 GUE margin=0.314 cross=0.000 state=class_interior pendolo_doppio:cycle_2 Poisson margin=0.252 cross=0.333 state=cut_edge numeri_primi:cycle_3 GUE margin=0.076 cross=0.333 state=third_included_candidate zeta_zeros:cycle_4 GUE margin=0.044 cross=0.000 state=class_interior logistica_biforcazione:cycle_5 GUE margin=0.071 cross=0.000 state=class_interior string_vibration:cycle_6 Poisson margin=0.531 cross=0.250 state=cut_edge random_matrix:cycle_7 GUE margin=0.013 cross=0.000 state=class_interior cellular_automata:cycle_8 GUE margin=0.212 cross=0.000 state=class_interior percolation:cycle_9 Poisson margin=0.282 cross=0.667 state=cut_edge coupled_oscillators:cycle_10 Poisson margin=0.604 cross=0.000 state=class_interior reaction_diffusion:cycle_11 GUE margin=0.123 cross=0.667 state=third_included_candidate brownian_motion:cycle_12 Poisson margin=0.431 cross=0.333 state=cut_edge logistica_biforcazione_var_3.5699:cycle_13 GUE margin=0.024 cross=1.000 state=third_included_candidate saved=/tmp/boundary_bridge_stability_tmp.json observables_registry=1.0.0-2026-05-06 observables_used=['SR', 'SR2', 'L1', 'L2', 'triple_var', 'SR_local_rigidity', 'z_SR', 'z_SR2', 'z_L1', 'z_L2', 'z_triple_var'] rows_analyzed=13 errors=0 label_counts={'GUE': 8, 'Poisson': 5} edge_counts={'total': 31, 'cross_label': 13, 'same_label': 18} curvature={'cross_edge_mean': -7.153846, 'same_edge_mean': -6.722222} third_included_candidates=['pendolo_doppio:cycle_2', 'numeri_primi:cycle_3', 'zeta_zeros:cycle_4', 'logistica_biforcazione:cycle_5', 'random_matrix:cycle_7', 'percolation:cycle_9', 'coupled_oscillators:cycle_10', 'reaction_diffusion:cycle_11', 'brownian_motion:cycle_12', 'logistica_biforcazione_var_3.5699:cycle_13'] ising_2d:cycle_1 GUE margin=0.321 cross=0.000 state=class_interior pendolo_doppio:cycle_2 Poisson margin=0.232 cross=0.250 state=third_included_candidate numeri_primi:cycle_3 GUE margin=0.038 cross=0.333 state=third_included_candidate zeta_zeros:cycle_4 GUE margin=0.072 cross=0.429 state=third_included_candidate logistica_biforcazione:cycle_5 GUE margin=0.072 cross=0.333 state=third_included_candidate string_vibration:cycle_6 Poisson margin=0.722 cross=0.500 state=cut_edge random_matrix:cycle_7 GUE margin=0.062 cross=0.429 state=third_included_candidate cellular_automata:cycle_8 GUE margin=0.233 cross=0.000 state=class_interior percolation:cycle_9 Poisson margin=0.152 cross=0.571 state=third_included_candidate coupled_oscillators:cycle_10 Poisson margin=0.248 cross=0.400 state=third_included_candidate reaction_diffusion:cycle_11 GUE margin=0.159 cross=0.500 state=third_included_candidate brownian_motion:cycle_12 Poisson margin=0.138 cross=0.667 state=third_included_candidate logistica_biforcazione_var_3.5699:cycle_13 GUE margin=0.044 cross=1.000 state=third_included_candidate saved=/tmp/boundary_bridge_stability_tmp.json observables_registry=1.0.0-2026-05-06 observables_used=['SR', 'SR2', 'L1', 'L2', 'triple_var', 'SR_local_rigidity', 'z_SR', 'z_SR2', 'z_L1', 'z_L2', 'z_triple_var'] rows_analyzed=13 errors=0 label_counts={'GUE': 8, 'Poisson': 5} edge_counts={'total': 28, 'cross_label': 11, 'same_label': 17} curvature={'cross_edge_mean': -5.454545, 'same_edge_mean': -5.294118} third_included_candidates=['pendolo_doppio:cycle_2', 'numeri_primi:cycle_3', 'zeta_zeros:cycle_4', 'logistica_biforcazione:cycle_5', 'random_matrix:cycle_7', 'percolation:cycle_9', 'reaction_diffusion:cycle_11', 'brownian_motion:cycle_12', 'logistica_biforcazione_var_3.5699:cycle_13'] ising_2d:cycle_1 GUE margin=0.302 cross=0.000 state=class_interior pendolo_doppio:cycle_2 Poisson margin=0.238 cross=0.250 state=third_included_candidate numeri_primi:cycle_3 GUE margin=0.090 cross=0.333 state=third_included_candidate zeta_zeros:cycle_4 GUE margin=0.011 cross=0.200 state=third_included_candidate logistica_biforcazione:cycle_5 GUE margin=0.078 cross=0.333 state=third_included_candidate string_vibration:cycle_6 Poisson margin=0.567 cross=0.500 state=cut_edge random_matrix:cycle_7 GUE margin=0.036 cross=0.429 state=third_included_candidate cellular_automata:cycle_8 GUE margin=0.184 cross=0.000 state=class_interior percolation:cycle_9 Poisson margin=0.237 cross=0.800 state=third_included_candidate coupled_oscillators:cycle_10 Poisson margin=0.492 cross=0.200 state=cut_edge reaction_diffusion:cycle_11 GUE margin=0.118 cross=0.667 state=third_included_candidate brownian_motion:cycle_12 Poisson margin=0.172 cross=0.400 state=third_included_candidate logistica_biforcazione_var_3.5699:cycle_13 GUE margin=0.025 cross=1.000 state=third_included_candidate saved=/tmp/boundary_bridge_stability_tmp.json observables_registry=1.0.0-2026-05-06 observables_used=['SR', 'SR2', 'L1', 'L2', 'triple_var', 'SR_local_rigidity', 'z_SR', 'z_SR2', 'z_L1', 'z_L2', 'z_triple_var'] rows_analyzed=13 errors=0 label_counts={'GUE': 8, 'Poisson': 5} edge_counts={'total': 37, 'cross_label': 13, 'same_label': 24} curvature={'cross_edge_mean': -8.0, 'same_edge_mean': -7.916667} third_included_candidates=['numeri_primi:cycle_3', 'zeta_zeros:cycle_4', 'logistica_biforcazione:cycle_5', 'random_matrix:cycle_7', 'percolation:cycle_9', 'reaction_diffusion:cycle_11', 'brownian_motion:cycle_12', 'logistica_biforcazione_var_3.5699:cycle_13'] ising_2d:cycle_1 GUE margin=0.352 cross=0.000 state=class_interior pendolo_doppio:cycle_2 Poisson margin=0.266 cross=0.333 state=cut_edge numeri_primi:cycle_3 GUE margin=0.005 cross=0.167 state=third_included_candidate zeta_zeros:cycle_4 GUE margin=0.102 cross=0.333 state=third_included_candidate logistica_biforcazione:cycle_5 GUE margin=0.065 cross=0.500 state=third_included_candidate string_vibration:cycle_6 Poisson margin=0.607 cross=0.429 state=cut_edge random_matrix:cycle_7 GUE margin=0.173 cross=0.429 state=third_included_candidate cellular_automata:cycle_8 GUE margin=0.235 cross=0.000 state=class_interior percolation:cycle_9 Poisson margin=0.185 cross=0.500 state=third_included_candidate coupled_oscillators:cycle_10 Poisson margin=0.365 cross=0.333 state=cut_edge reaction_diffusion:cycle_11 GUE margin=0.080 cross=0.500 state=third_included_candidate brownian_motion:cycle_12 Poisson margin=0.214 cross=0.333 state=third_included_candidate logistica_biforcazione_var_3.5699:cycle_13 GUE margin=0.047 cross=0.750 state=third_included_candidate saved=/tmp/boundary_bridge_stability_tmp.json observables_registry=1.0.0-2026-05-06 observables_used=['SR', 'SR2', 'L1', 'L2', 'triple_var', 'SR_local_rigidity', 'z_SR', 'z_SR2', 'z_L1', 'z_L2', 'z_triple_var'] rows_analyzed=13 errors=0 label_counts={'GUE': 8, 'Poisson': 5} edge_counts={'total': 38, 'cross_label': 16, 'same_label': 22} curvature={'cross_edge_mean': -8.6875, 'same_edge_mean': -8.227273} third_included_candidates=['numeri_primi:cycle_3', 'zeta_zeros:cycle_4', 'logistica_biforcazione:cycle_5', 'random_matrix:cycle_7', 'percolation:cycle_9', 'reaction_diffusion:cycle_11', 'brownian_motion:cycle_12', 'logistica_biforcazione_var_3.5699:cycle_13'] ising_2d:cycle_1 GUE margin=0.312 cross=0.000 state=class_interior pendolo_doppio:cycle_2 Poisson margin=0.256 cross=0.429 state=cut_edge numeri_primi:cycle_3 GUE margin=0.062 cross=0.400 state=third_included_candidate zeta_zeros:cycle_4 GUE margin=0.036 cross=0.500 state=third_included_candidate logistica_biforcazione:cycle_5 GUE margin=0.066 cross=0.500 state=third_included_candidate string_vibration:cycle_6 Poisson margin=0.661 cross=0.500 state=cut_edge random_matrix:cycle_7 GUE margin=0.040 cross=0.286 state=third_included_candidate cellular_automata:cycle_8 GUE margin=0.213 cross=0.000 state=class_interior percolation:cycle_9 Poisson margin=0.127 cross=0.571 state=third_included_candidate coupled_oscillators:cycle_10 Poisson margin=0.380 cross=0.429 state=cut_edge reaction_diffusion:cycle_11 GUE margin=0.174 cross=0.600 state=third_included_candidate brownian_motion:cycle_12 Poisson margin=0.117 cross=0.400 state=third_included_candidate logistica_biforcazione_var_3.5699:cycle_13 GUE margin=0.035 cross=0.750 state=third_included_candidate saved=/tmp/boundary_bridge_stability_tmp.json { "classic_only_stable_graph_absent": [ "cellular_automata:cycle_8" ], "composite_counts": { "parameter_sensitive_bridge+classic_only_intermediate": 2, "parameter_sensitive_bridge+endpoint_like": 2, "stable_graph_bridge+classic_and_graph_bridge": 1, "stable_graph_bridge+classic_only_intermediate": 1, "stable_graph_bridge+graph_only_bridge": 3, "unstable_non_bridge+classic_only_intermediate": 1, "unstable_non_bridge+endpoint_like": 3 }, "graph_reader_runs": 6, "lab_residue_after_stability": true, "rows_analyzed": 13, "stable_classic_and_graph": [ "numeri_primi:cycle_3" ], "stable_graph_only": [ "logistica_biforcazione_var_3.5699:cycle_13", "percolation:cycle_9", "reaction_diffusion:cycle_11" ] } apply patch patch: completed /opt/MM_D-ND/tools/data/reports/agent_20260515_1915.md diff --git a/tools/data/reports/agent_20260515_1915.md b/tools/data/reports/agent_20260515_1915.md new file mode 100644 index 0000000000000000000000000000000000000000..62c085a93c5f830f9f42ef73309544982f4693f3 --- /dev/null +++ b/tools/data/reports/agent_20260515_1915.md @@ -0,0 +1,131 @@ +# Agent Report - Boundary Bridge Stability Audit +**Date**: 2026-05-15 19:15 +**Piano**: 121 +**Tension explored**: BOUNDARY (0.8) +**verdict**: CONSTRAINT - il boundary a due lettori sopravvive come frequenza composita, non come lista fissa di righe del gate 18:55. +observables_registry: 1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined +observables_used: [graph_bridge_frequency, cut_edge_frequency, mean_centroid_margin, mean_cross_neighbor_fraction, classical_audit_state, brody_q, berry_robnick_like_gue_weight] +**observable_contract**: claim=una riga boundary a due lettori e' operativa solo se lo stato graph bridge sopravvive a perturbazioni del lettore e resta auditato dal baseline classico; observable=frequenza graph bridge unita a stato Brody/Berry-Robnik-like; operator=perturbazione parametrica del grafo kNN con join classico row-aligned; generator=boundary_graph_curvature_gate sul denominatore BOUNDARY 13 righe; denominator=13 righe, 8 GUE e 5 Poisson, ripetute su griglia di 27 run; non_possible=stable Lab bridge se la frequenza bridge collassa sotto perturbazione k/n_gaps/seed; not_tested=Hamiltoniane fisiche nuove, unfolding alternativo, scaling asintotico. + +## Respiro fuori-tempo +- **Combo**: A9 terzo incluso + QxG continuo/discreto + grafo/crossover spettrale + tensione BOUNDARY "8 domini GUE, 5 Poisson". +- **Dipolo / punto-zero**: riga ponte stabile / riga ponte parametrica. Punto-zero: la riga row-aligned prima della soglia singola. +- **Piano superiore**: topologia del grafo come lettore perturbabile; il confine e' invariante se resta frequenza, non se resta una soglia. +- **Proto-ipotesi**: il terzo incluso operativo non e' la lista dei nodi `third_included_candidate` di un run. E' la classe composita che resta dopo perturbazione del lettore grafico e audit classico. +- **Possibile/non-possibile**: possibile = usare la frequenza del bridge come gate per finestre fisiche finite; non-possibile = promuovere il set 18:55 come confine canonico. +- **Proiezione**: ripeto il lettore grafico su `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}` e unisco ogni riga allo stato classico del report 19:04. + +### Contaminazione cognitiva +- **CE-0019 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0019 - Respiro fuori-tempo`, letta il 2026-05-15. Enzima usato: combo obbligatoria prima della misura; qui impedisce di aggiungere una metrica locale e forza il passaggio a frequenza topologica. +- **CE-0022 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0022 - Palette operatoria espansa del Lab`, letta il 2026-05-15. Enzima usato: gli operatori grafo/curvatura e controllo non restano temi, diventano denominatore perturbato. +- **YSN DeltaLink**: `lista fissa / frequenza stabile`. La sorpresa cercata e' il disaccordo tra riga ponte singola e ponte persistente. +- **Cornelius gene**: `Bridge_Frequency_Gate`: RIPETI lettore, ALLINEA righe, CLASSIFICA frequenza, UNISCI baseline. +- **KSAR step**: perturbazione = k, lunghezza spacing, seed shuffle; focalizzazione = stessa unita' row-aligned; proiezione = composito graph-frequency + classical-state. + +## Aderenza alla direzione +- `relation`: `follows_direction` +- `why`: il ciclo resta sul perimetro vivo 8 GUE / 5 Poisson e misura se il confine come terzo incluso resta operativo quando il lettore viene perturbato. +- `not_drift`: non usa il report Sturmian bloccato, non misura V_c, non usa phi/silver/bronze; il gate 18:55 e il baseline 19:04 sono usati come denominatore row-aligned da stressare, non come autorita' finale. + +## Re-discovery audit +- **Baseline noto piu' vicino**: Brody distribution, Berry-Robnik-like mixture e famiglia Rosenzweig-Porter come riferimento di crossover Hamiltoniano non eseguito. +- **Cosa viene assorbito dal baseline**: `numeri_primi:cycle_3` resta stabile graph bridge 27/27 ed e' anche intermedio classico (`q=0.465`, `w_GUE=0.275`): qui il Lab non separa un fenomeno nuovo dal crossover classico. +- **Cosa resta Lab-specific**: `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13` sono `stable_graph_bridge+graph_only_bridge`, tutte 27/27. Il baseline classico le legge endpoint-like, il grafo le legge confine stabile. +- **Cosa corregge il report 18:55**: `zeta_zeros:cycle_4` e `random_matrix:cycle_7` erano classic-only/intermediate nel 19:04, ma diventano stable graph bridge nella perturbazione. La soglia singola k=3 sottostima parte del confine. +- **Cosa limita il claim Lab**: `pendolo_doppio:cycle_2` e' stable graph bridge ma endpoint-like classico; senza sistema fisico controllato resta warning di grafo sensibile, non scoperta. + +## Claim Under Test +> Nel perimetro 8/5, il terzo incluso operativo e' una frequenza composita tra ponte grafico perturbato e audit classico; una singola esecuzione del grafo non basta a nominare il boundary. + +## Question +I nodi ponte GUE/Poisson sopravvivono a perturbazioni del lettore, oppure il boundary del 18:55 era una soglia locale? + +## Ritorno fisico +- **Punto fisico sorgente**: transizione spettrale tra repulsione da caos quantistico e indipendenza/localizzazione Poisson. +- **Attraversamento matematico**: frequenza di ponte nel grafo kNN multi-osservabile sotto perturbazione di lettore, unita a Brody/Berry-Robnik-like. +- **Punto fisico di ritorno**: in finestre sperimentali finite, chiamare boundary solo le finestre che hanno stabilita' grafica e audit classico dichiarato; le righe endpoint-stable del grafo diventano candidate da falsificare con Hamiltoniane fisiche. +- **Osservabile/test fisico possibile**: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre con finestre energetiche; misurare `graph_bridge_frequency` e stato Brody/Berry-Robnik sulla stessa riga. +- **Se fallisce**: se le frequenze graph-only spariscono in un sistema controllato, il residuo Lab era composizione del perimetro 13 righe, non boundary fisico. + +## Experiment Design +- **Script**: `tools/exp_boundary_bridge_stability_audit.py`. +- **Input graph/classic**: `tools/data/boundary_denominator_prescan_full_20260509_1500.json` + `tools/data/boundary_classical_crossover_audit_20260515_1904.json`. +- **Run**: `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json`. +- **Denominatore**: 13 righe row-aligned, 8 GUE e 5 Poisson. +- **Griglia**: 27 letture grafiche, `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}`, `n_shuffle=32`. +- **Classi**: `stable_graph_bridge` se frequenza >= 0.75; `parameter_sensitive_bridge` se 0.25 <= frequenza < 0.75; `unstable_non_bridge` se frequenza < 0.25. +- **Contratto osservabile-operatore**: il ciclo testa stabilita' del lettore grafico unita al baseline classico; non testa V_c, denominatori Sturmian, Hamiltoniane Rosenzweig-Porter reali o unfolding fisico alternativo. + +## Results +| summary | value | +|---|---:| +| rows analyzed | 13 | +| graph reader runs | 27 | +| lab residue after stability | true | +| stable graph-only bridges | 3 | +| stable classic+graph bridges | 1 | +| classic-only with stable graph absent | 1 | + +| composite state | count | +|---|---:| +| stable_graph_bridge+graph_only_bridge | 3 | +| stable_graph_bridge+classic_and_graph_bridge | 1 | +| stable_graph_bridge+classic_only_intermediate | 2 | +| stable_graph_bridge+endpoint_like | 1 | +| parameter_sensitive_bridge+classic_only_intermediate | 1 | +| parameter_sensitive_bridge+endpoint_like | 1 | +| unstable_non_bridge+classic_only_intermediate | 1 | +| unstable_non_bridge+endpoint_like | 3 | + +| row | classical state | graph frequency | composite | +|---|---|---:|---| +| numeri_primi:cycle_3 | classic_and_graph_bridge | 1.000 | stable_graph_bridge+classic_and_graph_bridge | +| percolation:cycle_9 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| reaction_diffusion:cycle_11 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| logistica_biforcazione_var_3.5699:cycle_13 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| zeta_zeros:cycle_4 | classic_only_intermediate | 0.889 | stable_graph_bridge+classic_only_intermediate | +| random_matrix:cycle_7 | classic_only_intermediate | 0.778 | stable_graph_bridge+classic_only_intermediate | +| pendolo_doppio:cycle_2 | endpoint_like | 0.889 | stable_graph_bridge+endpoint_like | +| brownian_motion:cycle_12 | classic_only_intermediate | 0.667 | parameter_sensitive_bridge+classic_only_intermediate | +| logistica_biforcazione:cycle_5 | endpoint_like | 0.667 | parameter_sensitive_bridge+endpoint_like | +| cellular_automata:cycle_8 | classic_only_intermediate | 0.000 | unstable_non_bridge+classic_only_intermediate | + +## Key Findings +1. Verificato: il denominatore resta quello richiesto, 13 righe con 8 GUE e 5 Poisson, ripetute in 27 letture. +2. Verificato: i tre `graph_only_bridge` del 19:04 restano stabili 27/27: `percolation`, `reaction_diffusion`, `logistica_biforcazione_var_3.5699`. +3. Verificato: `numeri_primi` resta ponte sia classico sia grafico, 27/27. +4. Verificato: `zeta_zeros` e `random_matrix` migrano da classic-only a stable graph bridge quando il lettore e' perturbato. Il gate 18:55 era una sezione, non il boundary intero. +5. Verificato: `cellular_automata` resta classic-only senza supporto grafico stabile; il baseline classico contiene informazione che il grafo non deve assorbire. +6. Inferito: il terzo incluso operativo e' il composito `graph_bridge_frequency + classical_audit_state`; una soglia kNN singola perde informazione. + +## Verdict +CONSTRAINT + +Il boundary trasferisce come gate a frequenza composita. La parte Lab-specific sopravvive nei tre stable graph-only bridge; il confine non si chiude nella lista 18:55 e non si riduce a Brody/Berry-Robnik. + +## Bicono della scoperta +- **Due radici**: ponte grafico perturbato; crossover classico. +- **Singolare**: riga row-aligned prima della soglia. +- **Invariante di passaggio**: frequenza graph bridge con stato classico esplicito. +- **Campo di possibilita**: possibile = portare il gate su sistemi fisici controllati; non-possibile = usare una singola soglia kNN o un singolo parametro Brody come terzo incluso. + +## Consecutio +Il prossimo ciclo utile porta il gate composito su un sistema fisico controllato: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre. Il target non e' aumentare metriche; e' chiedere se `stable_graph_bridge+graph_only_bridge` sopravvive fuori dal perimetro composito del Lab. + +## Ricadute pratiche +ssp_value: yes. Lo script crea un audit riusabile per stressare ogni gate GUE/Poisson row-aligned e separare ponte stabile, ponte parametrico, re-discovery classica ed endpoint-like. + +## Telemetria +- No API paid run: `ANTHROPIC_API_KEY` e `OPENAI_API_KEY` non presenti nell'ambiente. +- `python tools/dnd_scenario.py --best` eseguito: massimo discriminante locale `TENS_SCALE_TRASCENDENZA_LIMITE`; la direzione viva del campo ha prevalso per il perimetro BOUNDARY 8/5. +- Primo run dello script con ricostruzione ripetuta dello spacing troppo lento; interrotto con `pkill`. Riparazione regressiva: cache delle righe in `tools/exp_boundary_bridge_stability_audit.py`, poi run completo 27/27. +- `python -m py_compile tools/exp_boundary_bridge_stability_audit.py` completato. +- `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json` completato. +- Worktree gia dirty prima del ciclo; ignorate modifiche non correlate. +- Nessun update del seme. +- Nessuna promozione e nessun public sync. + +## Files +- Script: `tools/exp_boundary_bridge_stability_audit.py` +- Data: `tools/data/boundary_bridge_stability_audit_20260515_1915.json` +- Report: `tools/data/reports/agent_20260515_1915.md` diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() diff --git a/tools/data/reports/agent_20260515_1915.md b/tools/data/reports/agent_20260515_1915.md new file mode 100644 index 0000000000000000000000000000000000000000..62c085a93c5f830f9f42ef73309544982f4693f3 --- /dev/null +++ b/tools/data/reports/agent_20260515_1915.md @@ -0,0 +1,131 @@ +# Agent Report - Boundary Bridge Stability Audit +**Date**: 2026-05-15 19:15 +**Piano**: 121 +**Tension explored**: BOUNDARY (0.8) +**verdict**: CONSTRAINT - il boundary a due lettori sopravvive come frequenza composita, non come lista fissa di righe del gate 18:55. +observables_registry: 1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined +observables_used: [graph_bridge_frequency, cut_edge_frequency, mean_centroid_margin, mean_cross_neighbor_fraction, classical_audit_state, brody_q, berry_robnick_like_gue_weight] +**observable_contract**: claim=una riga boundary a due lettori e' operativa solo se lo stato graph bridge sopravvive a perturbazioni del lettore e resta auditato dal baseline classico; observable=frequenza graph bridge unita a stato Brody/Berry-Robnik-like; operator=perturbazione parametrica del grafo kNN con join classico row-aligned; generator=boundary_graph_curvature_gate sul denominatore BOUNDARY 13 righe; denominator=13 righe, 8 GUE e 5 Poisson, ripetute su griglia di 27 run; non_possible=stable Lab bridge se la frequenza bridge collassa sotto perturbazione k/n_gaps/seed; not_tested=Hamiltoniane fisiche nuove, unfolding alternativo, scaling asintotico. + +## Respiro fuori-tempo +- **Combo**: A9 terzo incluso + QxG continuo/discreto + grafo/crossover spettrale + tensione BOUNDARY "8 domini GUE, 5 Poisson". +- **Dipolo / punto-zero**: riga ponte stabile / riga ponte parametrica. Punto-zero: la riga row-aligned prima della soglia singola. +- **Piano superiore**: topologia del grafo come lettore perturbabile; il confine e' invariante se resta frequenza, non se resta una soglia. +- **Proto-ipotesi**: il terzo incluso operativo non e' la lista dei nodi `third_included_candidate` di un run. E' la classe composita che resta dopo perturbazione del lettore grafico e audit classico. +- **Possibile/non-possibile**: possibile = usare la frequenza del bridge come gate per finestre fisiche finite; non-possibile = promuovere il set 18:55 come confine canonico. +- **Proiezione**: ripeto il lettore grafico su `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}` e unisco ogni riga allo stato classico del report 19:04. + +### Contaminazione cognitiva +- **CE-0019 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0019 - Respiro fuori-tempo`, letta il 2026-05-15. Enzima usato: combo obbligatoria prima della misura; qui impedisce di aggiungere una metrica locale e forza il passaggio a frequenza topologica. +- **CE-0022 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0022 - Palette operatoria espansa del Lab`, letta il 2026-05-15. Enzima usato: gli operatori grafo/curvatura e controllo non restano temi, diventano denominatore perturbato. +- **YSN DeltaLink**: `lista fissa / frequenza stabile`. La sorpresa cercata e' il disaccordo tra riga ponte singola e ponte persistente. +- **Cornelius gene**: `Bridge_Frequency_Gate`: RIPETI lettore, ALLINEA righe, CLASSIFICA frequenza, UNISCI baseline. +- **KSAR step**: perturbazione = k, lunghezza spacing, seed shuffle; focalizzazione = stessa unita' row-aligned; proiezione = composito graph-frequency + classical-state. + +## Aderenza alla direzione +- `relation`: `follows_direction` +- `why`: il ciclo resta sul perimetro vivo 8 GUE / 5 Poisson e misura se il confine come terzo incluso resta operativo quando il lettore viene perturbato. +- `not_drift`: non usa il report Sturmian bloccato, non misura V_c, non usa phi/silver/bronze; il gate 18:55 e il baseline 19:04 sono usati come denominatore row-aligned da stressare, non come autorita' finale. + +## Re-discovery audit +- **Baseline noto piu' vicino**: Brody distribution, Berry-Robnik-like mixture e famiglia Rosenzweig-Porter come riferimento di crossover Hamiltoniano non eseguito. +- **Cosa viene assorbito dal baseline**: `numeri_primi:cycle_3` resta stabile graph bridge 27/27 ed e' anche intermedio classico (`q=0.465`, `w_GUE=0.275`): qui il Lab non separa un fenomeno nuovo dal crossover classico. +- **Cosa resta Lab-specific**: `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13` sono `stable_graph_bridge+graph_only_bridge`, tutte 27/27. Il baseline classico le legge endpoint-like, il grafo le legge confine stabile. +- **Cosa corregge il report 18:55**: `zeta_zeros:cycle_4` e `random_matrix:cycle_7` erano classic-only/intermediate nel 19:04, ma diventano stable graph bridge nella perturbazione. La soglia singola k=3 sottostima parte del confine. +- **Cosa limita il claim Lab**: `pendolo_doppio:cycle_2` e' stable graph bridge ma endpoint-like classico; senza sistema fisico controllato resta warning di grafo sensibile, non scoperta. + +## Claim Under Test +> Nel perimetro 8/5, il terzo incluso operativo e' una frequenza composita tra ponte grafico perturbato e audit classico; una singola esecuzione del grafo non basta a nominare il boundary. + +## Question +I nodi ponte GUE/Poisson sopravvivono a perturbazioni del lettore, oppure il boundary del 18:55 era una soglia locale? + +## Ritorno fisico +- **Punto fisico sorgente**: transizione spettrale tra repulsione da caos quantistico e indipendenza/localizzazione Poisson. +- **Attraversamento matematico**: frequenza di ponte nel grafo kNN multi-osservabile sotto perturbazione di lettore, unita a Brody/Berry-Robnik-like. +- **Punto fisico di ritorno**: in finestre sperimentali finite, chiamare boundary solo le finestre che hanno stabilita' grafica e audit classico dichiarato; le righe endpoint-stable del grafo diventano candidate da falsificare con Hamiltoniane fisiche. +- **Osservabile/test fisico possibile**: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre con finestre energetiche; misurare `graph_bridge_frequency` e stato Brody/Berry-Robnik sulla stessa riga. +- **Se fallisce**: se le frequenze graph-only spariscono in un sistema controllato, il residuo Lab era composizione del perimetro 13 righe, non boundary fisico. + +## Experiment Design +- **Script**: `tools/exp_boundary_bridge_stability_audit.py`. +- **Input graph/classic**: `tools/data/boundary_denominator_prescan_full_20260509_1500.json` + `tools/data/boundary_classical_crossover_audit_20260515_1904.json`. +- **Run**: `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json`. +- **Denominatore**: 13 righe row-aligned, 8 GUE e 5 Poisson. +- **Griglia**: 27 letture grafiche, `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}`, `n_shuffle=32`. +- **Classi**: `stable_graph_bridge` se frequenza >= 0.75; `parameter_sensitive_bridge` se 0.25 <= frequenza < 0.75; `unstable_non_bridge` se frequenza < 0.25. +- **Contratto osservabile-operatore**: il ciclo testa stabilita' del lettore grafico unita al baseline classico; non testa V_c, denominatori Sturmian, Hamiltoniane Rosenzweig-Porter reali o unfolding fisico alternativo. + +## Results +| summary | value | +|---|---:| +| rows analyzed | 13 | +| graph reader runs | 27 | +| lab residue after stability | true | +| stable graph-only bridges | 3 | +| stable classic+graph bridges | 1 | +| classic-only with stable graph absent | 1 | + +| composite state | count | +|---|---:| +| stable_graph_bridge+graph_only_bridge | 3 | +| stable_graph_bridge+classic_and_graph_bridge | 1 | +| stable_graph_bridge+classic_only_intermediate | 2 | +| stable_graph_bridge+endpoint_like | 1 | +| parameter_sensitive_bridge+classic_only_intermediate | 1 | +| parameter_sensitive_bridge+endpoint_like | 1 | +| unstable_non_bridge+classic_only_intermediate | 1 | +| unstable_non_bridge+endpoint_like | 3 | + +| row | classical state | graph frequency | composite | +|---|---|---:|---| +| numeri_primi:cycle_3 | classic_and_graph_bridge | 1.000 | stable_graph_bridge+classic_and_graph_bridge | +| percolation:cycle_9 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| reaction_diffusion:cycle_11 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| logistica_biforcazione_var_3.5699:cycle_13 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| zeta_zeros:cycle_4 | classic_only_intermediate | 0.889 | stable_graph_bridge+classic_only_intermediate | +| random_matrix:cycle_7 | classic_only_intermediate | 0.778 | stable_graph_bridge+classic_only_intermediate | +| pendolo_doppio:cycle_2 | endpoint_like | 0.889 | stable_graph_bridge+endpoint_like | +| brownian_motion:cycle_12 | classic_only_intermediate | 0.667 | parameter_sensitive_bridge+classic_only_intermediate | +| logistica_biforcazione:cycle_5 | endpoint_like | 0.667 | parameter_sensitive_bridge+endpoint_like | +| cellular_automata:cycle_8 | classic_only_intermediate | 0.000 | unstable_non_bridge+classic_only_intermediate | + +## Key Findings +1. Verificato: il denominatore resta quello richiesto, 13 righe con 8 GUE e 5 Poisson, ripetute in 27 letture. +2. Verificato: i tre `graph_only_bridge` del 19:04 restano stabili 27/27: `percolation`, `reaction_diffusion`, `logistica_biforcazione_var_3.5699`. +3. Verificato: `numeri_primi` resta ponte sia classico sia grafico, 27/27. +4. Verificato: `zeta_zeros` e `random_matrix` migrano da classic-only a stable graph bridge quando il lettore e' perturbato. Il gate 18:55 era una sezione, non il boundary intero. +5. Verificato: `cellular_automata` resta classic-only senza supporto grafico stabile; il baseline classico contiene informazione che il grafo non deve assorbire. +6. Inferito: il terzo incluso operativo e' il composito `graph_bridge_frequency + classical_audit_state`; una soglia kNN singola perde informazione. + +## Verdict +CONSTRAINT + +Il boundary trasferisce come gate a frequenza composita. La parte Lab-specific sopravvive nei tre stable graph-only bridge; il confine non si chiude nella lista 18:55 e non si riduce a Brody/Berry-Robnik. + +## Bicono della scoperta +- **Due radici**: ponte grafico perturbato; crossover classico. +- **Singolare**: riga row-aligned prima della soglia. +- **Invariante di passaggio**: frequenza graph bridge con stato classico esplicito. +- **Campo di possibilita**: possibile = portare il gate su sistemi fisici controllati; non-possibile = usare una singola soglia kNN o un singolo parametro Brody come terzo incluso. + +## Consecutio +Il prossimo ciclo utile porta il gate composito su un sistema fisico controllato: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre. Il target non e' aumentare metriche; e' chiedere se `stable_graph_bridge+graph_only_bridge` sopravvive fuori dal perimetro composito del Lab. + +## Ricadute pratiche +ssp_value: yes. Lo script crea un audit riusabile per stressare ogni gate GUE/Poisson row-aligned e separare ponte stabile, ponte parametrico, re-discovery classica ed endpoint-like. + +## Telemetria +- No API paid run: `ANTHROPIC_API_KEY` e `OPENAI_API_KEY` non presenti nell'ambiente. +- `python tools/dnd_scenario.py --best` eseguito: massimo discriminante locale `TENS_SCALE_TRASCENDENZA_LIMITE`; la direzione viva del campo ha prevalso per il perimetro BOUNDARY 8/5. +- Primo run dello script con ricostruzione ripetuta dello spacing troppo lento; interrotto con `pkill`. Riparazione regressiva: cache delle righe in `tools/exp_boundary_bridge_stability_audit.py`, poi run completo 27/27. +- `python -m py_compile tools/exp_boundary_bridge_stability_audit.py` completato. +- `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json` completato. +- Worktree gia dirty prima del ciclo; ignorate modifiche non correlate. +- Nessun update del seme. +- Nessuna promozione e nessun public sync. + +## Files +- Script: `tools/exp_boundary_bridge_stability_audit.py` +- Data: `tools/data/boundary_bridge_stability_audit_20260515_1915.json` +- Report: `tools/data/reports/agent_20260515_1915.md` diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() exec /bin/bash -lc 'rg -n "CE-none|forse|potrebbe|probabilmente|attualmente|per ora" tools/data/reports/agent_20260515_1915.md || true' in /opt/MM_D-ND succeeded in 0ms: exec /bin/bash -lc 'test -s tools/data/reports/agent_20260515_1915.md && test -s tools/data/boundary_bridge_stability_audit_20260515_1915.json && echo ok' in /opt/MM_D-ND succeeded in 0ms: ok exec /bin/bash -lc "ps -ef | rg 'exp_boundary_bridge_stability|python tools/exp_boundary'" in /opt/MM_D-ND succeeded in 0ms: root 1 0 25 19:27 ? 00:00:00 /root/.codex-lab/tmp/arg0/codex-arg06amPnY/codex-linux-sandbox --sandbox-policy-cwd /opt/MM_D-ND --command-cwd /opt/MM_D-ND --sandbox-policy {"type":"workspace-write","writable_roots":["/root/.codex-lab/memories"],"network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false} --file-system-sandbox-policy {"kind":"restricted","entries":[{"path":{"type":"special","value":{"kind":"root"}},"access":"read"},{"path":{"type":"special","value":{"kind":"current_working_directory"}},"access":"write"},{"path":{"type":"special","value":{"kind":"slash_tmp"}},"access":"write"},{"path":{"type":"special","value":{"kind":"tmpdir"}},"access":"write"},{"path":{"type":"path","path":"/root/.codex-lab/memories"},"access":"write"},{"path":{"type":"path","path":"/opt/MM_D-ND/.git"},"access":"read"},{"path":{"type":"path","path":"/opt/MM_D-ND/.codex"},"access":"read"}]} --network-sandbox-policy "restricted" -- /bin/bash -c __CODEX_SNAPSHOT_OVERRIDE_SET_0="${CODEX_THREAD_ID+x}" __CODEX_SNAPSHOT_OVERRIDE_0="${CODEX_THREAD_ID-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_0="${ALL_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_0="${ALL_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_1="${BUNDLE_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_1="${BUNDLE_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_2="${BUNDLE_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_2="${BUNDLE_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_3="${BUNDLE_NO_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_3="${BUNDLE_NO_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_4="${CODEX_NETWORK_ALLOW_LOCAL_BINDING+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_4="${CODEX_NETWORK_ALLOW_LOCAL_BINDING-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_5="${CODEX_NETWORK_PROXY_ACTIVE+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_5="${CODEX_NETWORK_PROXY_ACTIVE-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_6="${DOCKER_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_6="${DOCKER_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_7="${DOCKER_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_7="${DOCKER_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_8="${ELECTRON_GET_USE_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_8="${ELECTRON_GET_USE_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_9="${FTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_9="${FTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_10="${HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_10="${HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_11="${HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_11="${HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_12="${NO_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_12="${NO_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_13="${NPM_CONFIG_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_13="${NPM_CONFIG_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_14="${NPM_CONFIG_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_14="${NPM_CONFIG_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_15="${NPM_CONFIG_NOPROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_15="${NPM_CONFIG_NOPROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_16="${NPM_CONFIG_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_16="${NPM_CONFIG_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_17="${PIP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_17="${PIP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_18="${WSS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_18="${WSS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_19="${WS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_19="${WS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_20="${YARN_HTTPS_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_20="${YARN_HTTPS_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_21="${YARN_HTTP_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_21="${YARN_HTTP_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_22="${YARN_NO_PROXY+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_22="${YARN_NO_PROXY-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_23="${all_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_23="${all_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_24="${ftp_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_24="${ftp_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_25="${http_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_25="${http_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_26="${https_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_26="${https_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_27="${no_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_27="${no_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_28="${npm_config_http_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_28="${npm_config_http_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_29="${npm_config_https_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_29="${npm_config_https_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_30="${npm_config_noproxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_30="${npm_config_noproxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_31="${npm_config_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_31="${npm_config_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_32="${ws_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_32="${ws_proxy-}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_33="${wss_proxy+x}" __CODEX_SNAPSHOT_PROXY_OVERRIDE_33="${wss_proxy-}" __CODEX_SNAPSHOT_PROXY_ENV_SET="${CODEX_NETWORK_PROXY_ACTIVE+x}" if . '/root/.codex-lab/shell_snapshots/019e2d10-653e-7d33-b352-8b91a1bbf4f2.1778872509769133379.sh' >/dev/null 2>&1; then :; fi if [ -n "${__CODEX_SNAPSHOT_OVERRIDE_SET_0}" ]; then export CODEX_THREAD_ID="${__CODEX_SNAPSHOT_OVERRIDE_0}"; else unset CODEX_THREAD_ID; fi if [ -n "$__CODEX_SNAPSHOT_PROXY_ENV_SET" ] || [ -n "${CODEX_NETWORK_PROXY_ACTIVE+x}" ]; then if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_0}" ]; then export ALL_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_0}"; else unset ALL_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_1}" ]; then export BUNDLE_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_1}"; else unset BUNDLE_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_2}" ]; then export BUNDLE_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_2}"; else unset BUNDLE_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_3}" ]; then export BUNDLE_NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_3}"; else unset BUNDLE_NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_4}" ]; then export CODEX_NETWORK_ALLOW_LOCAL_BINDING="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_4}"; else unset CODEX_NETWORK_ALLOW_LOCAL_BINDING; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_5}" ]; then export CODEX_NETWORK_PROXY_ACTIVE="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_5}"; else unset CODEX_NETWORK_PROXY_ACTIVE; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_6}" ]; then export DOCKER_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_6}"; else unset DOCKER_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_7}" ]; then export DOCKER_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_7}"; else unset DOCKER_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_8}" ]; then export ELECTRON_GET_USE_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_8}"; else unset ELECTRON_GET_USE_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_9}" ]; then export FTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_9}"; else unset FTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_10}" ]; then export HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_10}"; else unset HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_11}" ]; then export HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_11}"; else unset HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_12}" ]; then export NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_12}"; else unset NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_13}" ]; then export NPM_CONFIG_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_13}"; else unset NPM_CONFIG_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_14}" ]; then export NPM_CONFIG_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_14}"; else unset NPM_CONFIG_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_15}" ]; then export NPM_CONFIG_NOPROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_15}"; else unset NPM_CONFIG_NOPROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_16}" ]; then export NPM_CONFIG_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_16}"; else unset NPM_CONFIG_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_17}" ]; then export PIP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_17}"; else unset PIP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_18}" ]; then export WSS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_18}"; else unset WSS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_19}" ]; then export WS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_19}"; else unset WS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_20}" ]; then export YARN_HTTPS_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_20}"; else unset YARN_HTTPS_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_21}" ]; then export YARN_HTTP_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_21}"; else unset YARN_HTTP_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_22}" ]; then export YARN_NO_PROXY="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_22}"; else unset YARN_NO_PROXY; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_23}" ]; then export all_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_23}"; else unset all_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_24}" ]; then export ftp_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_24}"; else unset ftp_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_25}" ]; then export http_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_25}"; else unset http_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_26}" ]; then export https_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_26}"; else unset https_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_27}" ]; then export no_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_27}"; else unset no_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_28}" ]; then export npm_config_http_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_28}"; else unset npm_config_http_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_29}" ]; then export npm_config_https_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_29}"; else unset npm_config_https_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_30}" ]; then export npm_config_noproxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_30}"; else unset npm_config_noproxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_31}" ]; then export npm_config_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_31}"; else unset npm_config_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_32}" ]; then export ws_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_32}"; else unset ws_proxy; fi if [ -n "${__CODEX_SNAPSHOT_PROXY_OVERRIDE_SET_33}" ]; then export wss_proxy="${__CODEX_SNAPSHOT_PROXY_OVERRIDE_33}"; else unset wss_proxy; fi fi exec '/bin/bash' -c 'ps -ef | rg '"'"'exp_boundary_bridge_stability|python tools/exp_boundary'"'"'' root 2 1 50 19:27 ? 00:00:00 /bin/bash -c ps -ef | rg 'exp_boundary_bridge_stability|python tools/exp_boundary' root 4 2 0 19:27 ? 00:00:00 rg exp_boundary_bridge_stability|python tools/exp_boundary exec /bin/bash -lc "python - <<'PY' from pathlib import Path p=Path('tools/data/reports/agent_20260515_1915.md') text=p.read_text() print('chars', len(text), 'lines', text.count('\\n')+1) print('non_ascii', sorted({c for c in text if ord(c)>127})[:20]) PY" in /opt/MM_D-ND succeeded in 0ms: chars 11770 lines 132 non_ascii [] diff --git a/tools/data/reports/agent_20260515_1915.md b/tools/data/reports/agent_20260515_1915.md new file mode 100644 index 0000000000000000000000000000000000000000..62c085a93c5f830f9f42ef73309544982f4693f3 --- /dev/null +++ b/tools/data/reports/agent_20260515_1915.md @@ -0,0 +1,131 @@ +# Agent Report - Boundary Bridge Stability Audit +**Date**: 2026-05-15 19:15 +**Piano**: 121 +**Tension explored**: BOUNDARY (0.8) +**verdict**: CONSTRAINT - il boundary a due lettori sopravvive come frequenza composita, non come lista fissa di righe del gate 18:55. +observables_registry: 1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined +observables_used: [graph_bridge_frequency, cut_edge_frequency, mean_centroid_margin, mean_cross_neighbor_fraction, classical_audit_state, brody_q, berry_robnick_like_gue_weight] +**observable_contract**: claim=una riga boundary a due lettori e' operativa solo se lo stato graph bridge sopravvive a perturbazioni del lettore e resta auditato dal baseline classico; observable=frequenza graph bridge unita a stato Brody/Berry-Robnik-like; operator=perturbazione parametrica del grafo kNN con join classico row-aligned; generator=boundary_graph_curvature_gate sul denominatore BOUNDARY 13 righe; denominator=13 righe, 8 GUE e 5 Poisson, ripetute su griglia di 27 run; non_possible=stable Lab bridge se la frequenza bridge collassa sotto perturbazione k/n_gaps/seed; not_tested=Hamiltoniane fisiche nuove, unfolding alternativo, scaling asintotico. + +## Respiro fuori-tempo +- **Combo**: A9 terzo incluso + QxG continuo/discreto + grafo/crossover spettrale + tensione BOUNDARY "8 domini GUE, 5 Poisson". +- **Dipolo / punto-zero**: riga ponte stabile / riga ponte parametrica. Punto-zero: la riga row-aligned prima della soglia singola. +- **Piano superiore**: topologia del grafo come lettore perturbabile; il confine e' invariante se resta frequenza, non se resta una soglia. +- **Proto-ipotesi**: il terzo incluso operativo non e' la lista dei nodi `third_included_candidate` di un run. E' la classe composita che resta dopo perturbazione del lettore grafico e audit classico. +- **Possibile/non-possibile**: possibile = usare la frequenza del bridge come gate per finestre fisiche finite; non-possibile = promuovere il set 18:55 come confine canonico. +- **Proiezione**: ripeto il lettore grafico su `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}` e unisco ogni riga allo stato classico del report 19:04. + +### Contaminazione cognitiva +- **CE-0019 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0019 - Respiro fuori-tempo`, letta il 2026-05-15. Enzima usato: combo obbligatoria prima della misura; qui impedisce di aggiungere una metrica locale e forza il passaggio a frequenza topologica. +- **CE-0022 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0022 - Palette operatoria espansa del Lab`, letta il 2026-05-15. Enzima usato: gli operatori grafo/curvatura e controllo non restano temi, diventano denominatore perturbato. +- **YSN DeltaLink**: `lista fissa / frequenza stabile`. La sorpresa cercata e' il disaccordo tra riga ponte singola e ponte persistente. +- **Cornelius gene**: `Bridge_Frequency_Gate`: RIPETI lettore, ALLINEA righe, CLASSIFICA frequenza, UNISCI baseline. +- **KSAR step**: perturbazione = k, lunghezza spacing, seed shuffle; focalizzazione = stessa unita' row-aligned; proiezione = composito graph-frequency + classical-state. + +## Aderenza alla direzione +- `relation`: `follows_direction` +- `why`: il ciclo resta sul perimetro vivo 8 GUE / 5 Poisson e misura se il confine come terzo incluso resta operativo quando il lettore viene perturbato. +- `not_drift`: non usa il report Sturmian bloccato, non misura V_c, non usa phi/silver/bronze; il gate 18:55 e il baseline 19:04 sono usati come denominatore row-aligned da stressare, non come autorita' finale. + +## Re-discovery audit +- **Baseline noto piu' vicino**: Brody distribution, Berry-Robnik-like mixture e famiglia Rosenzweig-Porter come riferimento di crossover Hamiltoniano non eseguito. +- **Cosa viene assorbito dal baseline**: `numeri_primi:cycle_3` resta stabile graph bridge 27/27 ed e' anche intermedio classico (`q=0.465`, `w_GUE=0.275`): qui il Lab non separa un fenomeno nuovo dal crossover classico. +- **Cosa resta Lab-specific**: `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13` sono `stable_graph_bridge+graph_only_bridge`, tutte 27/27. Il baseline classico le legge endpoint-like, il grafo le legge confine stabile. +- **Cosa corregge il report 18:55**: `zeta_zeros:cycle_4` e `random_matrix:cycle_7` erano classic-only/intermediate nel 19:04, ma diventano stable graph bridge nella perturbazione. La soglia singola k=3 sottostima parte del confine. +- **Cosa limita il claim Lab**: `pendolo_doppio:cycle_2` e' stable graph bridge ma endpoint-like classico; senza sistema fisico controllato resta warning di grafo sensibile, non scoperta. + +## Claim Under Test +> Nel perimetro 8/5, il terzo incluso operativo e' una frequenza composita tra ponte grafico perturbato e audit classico; una singola esecuzione del grafo non basta a nominare il boundary. + +## Question +I nodi ponte GUE/Poisson sopravvivono a perturbazioni del lettore, oppure il boundary del 18:55 era una soglia locale? + +## Ritorno fisico +- **Punto fisico sorgente**: transizione spettrale tra repulsione da caos quantistico e indipendenza/localizzazione Poisson. +- **Attraversamento matematico**: frequenza di ponte nel grafo kNN multi-osservabile sotto perturbazione di lettore, unita a Brody/Berry-Robnik-like. +- **Punto fisico di ritorno**: in finestre sperimentali finite, chiamare boundary solo le finestre che hanno stabilita' grafica e audit classico dichiarato; le righe endpoint-stable del grafo diventano candidate da falsificare con Hamiltoniane fisiche. +- **Osservabile/test fisico possibile**: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre con finestre energetiche; misurare `graph_bridge_frequency` e stato Brody/Berry-Robnik sulla stessa riga. +- **Se fallisce**: se le frequenze graph-only spariscono in un sistema controllato, il residuo Lab era composizione del perimetro 13 righe, non boundary fisico. + +## Experiment Design +- **Script**: `tools/exp_boundary_bridge_stability_audit.py`. +- **Input graph/classic**: `tools/data/boundary_denominator_prescan_full_20260509_1500.json` + `tools/data/boundary_classical_crossover_audit_20260515_1904.json`. +- **Run**: `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json`. +- **Denominatore**: 13 righe row-aligned, 8 GUE e 5 Poisson. +- **Griglia**: 27 letture grafiche, `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}`, `n_shuffle=32`. +- **Classi**: `stable_graph_bridge` se frequenza >= 0.75; `parameter_sensitive_bridge` se 0.25 <= frequenza < 0.75; `unstable_non_bridge` se frequenza < 0.25. +- **Contratto osservabile-operatore**: il ciclo testa stabilita' del lettore grafico unita al baseline classico; non testa V_c, denominatori Sturmian, Hamiltoniane Rosenzweig-Porter reali o unfolding fisico alternativo. + +## Results +| summary | value | +|---|---:| +| rows analyzed | 13 | +| graph reader runs | 27 | +| lab residue after stability | true | +| stable graph-only bridges | 3 | +| stable classic+graph bridges | 1 | +| classic-only with stable graph absent | 1 | + +| composite state | count | +|---|---:| +| stable_graph_bridge+graph_only_bridge | 3 | +| stable_graph_bridge+classic_and_graph_bridge | 1 | +| stable_graph_bridge+classic_only_intermediate | 2 | +| stable_graph_bridge+endpoint_like | 1 | +| parameter_sensitive_bridge+classic_only_intermediate | 1 | +| parameter_sensitive_bridge+endpoint_like | 1 | +| unstable_non_bridge+classic_only_intermediate | 1 | +| unstable_non_bridge+endpoint_like | 3 | + +| row | classical state | graph frequency | composite | +|---|---|---:|---| +| numeri_primi:cycle_3 | classic_and_graph_bridge | 1.000 | stable_graph_bridge+classic_and_graph_bridge | +| percolation:cycle_9 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| reaction_diffusion:cycle_11 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| logistica_biforcazione_var_3.5699:cycle_13 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| zeta_zeros:cycle_4 | classic_only_intermediate | 0.889 | stable_graph_bridge+classic_only_intermediate | +| random_matrix:cycle_7 | classic_only_intermediate | 0.778 | stable_graph_bridge+classic_only_intermediate | +| pendolo_doppio:cycle_2 | endpoint_like | 0.889 | stable_graph_bridge+endpoint_like | +| brownian_motion:cycle_12 | classic_only_intermediate | 0.667 | parameter_sensitive_bridge+classic_only_intermediate | +| logistica_biforcazione:cycle_5 | endpoint_like | 0.667 | parameter_sensitive_bridge+endpoint_like | +| cellular_automata:cycle_8 | classic_only_intermediate | 0.000 | unstable_non_bridge+classic_only_intermediate | + +## Key Findings +1. Verificato: il denominatore resta quello richiesto, 13 righe con 8 GUE e 5 Poisson, ripetute in 27 letture. +2. Verificato: i tre `graph_only_bridge` del 19:04 restano stabili 27/27: `percolation`, `reaction_diffusion`, `logistica_biforcazione_var_3.5699`. +3. Verificato: `numeri_primi` resta ponte sia classico sia grafico, 27/27. +4. Verificato: `zeta_zeros` e `random_matrix` migrano da classic-only a stable graph bridge quando il lettore e' perturbato. Il gate 18:55 era una sezione, non il boundary intero. +5. Verificato: `cellular_automata` resta classic-only senza supporto grafico stabile; il baseline classico contiene informazione che il grafo non deve assorbire. +6. Inferito: il terzo incluso operativo e' il composito `graph_bridge_frequency + classical_audit_state`; una soglia kNN singola perde informazione. + +## Verdict +CONSTRAINT + +Il boundary trasferisce come gate a frequenza composita. La parte Lab-specific sopravvive nei tre stable graph-only bridge; il confine non si chiude nella lista 18:55 e non si riduce a Brody/Berry-Robnik. + +## Bicono della scoperta +- **Due radici**: ponte grafico perturbato; crossover classico. +- **Singolare**: riga row-aligned prima della soglia. +- **Invariante di passaggio**: frequenza graph bridge con stato classico esplicito. +- **Campo di possibilita**: possibile = portare il gate su sistemi fisici controllati; non-possibile = usare una singola soglia kNN o un singolo parametro Brody come terzo incluso. + +## Consecutio +Il prossimo ciclo utile porta il gate composito su un sistema fisico controllato: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre. Il target non e' aumentare metriche; e' chiedere se `stable_graph_bridge+graph_only_bridge` sopravvive fuori dal perimetro composito del Lab. + +## Ricadute pratiche +ssp_value: yes. Lo script crea un audit riusabile per stressare ogni gate GUE/Poisson row-aligned e separare ponte stabile, ponte parametrico, re-discovery classica ed endpoint-like. + +## Telemetria +- No API paid run: `ANTHROPIC_API_KEY` e `OPENAI_API_KEY` non presenti nell'ambiente. +- `python tools/dnd_scenario.py --best` eseguito: massimo discriminante locale `TENS_SCALE_TRASCENDENZA_LIMITE`; la direzione viva del campo ha prevalso per il perimetro BOUNDARY 8/5. +- Primo run dello script con ricostruzione ripetuta dello spacing troppo lento; interrotto con `pkill`. Riparazione regressiva: cache delle righe in `tools/exp_boundary_bridge_stability_audit.py`, poi run completo 27/27. +- `python -m py_compile tools/exp_boundary_bridge_stability_audit.py` completato. +- `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json` completato. +- Worktree gia dirty prima del ciclo; ignorate modifiche non correlate. +- Nessun update del seme. +- Nessuna promozione e nessun public sync. + +## Files +- Script: `tools/exp_boundary_bridge_stability_audit.py` +- Data: `tools/data/boundary_bridge_stability_audit_20260515_1915.json` +- Report: `tools/data/reports/agent_20260515_1915.md` diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() codex Eseguito il cycle e scritto il report richiesto: - Report: [agent_20260515_1915.md](/opt/MM_D-ND/tools/data/reports/agent_20260515_1915.md) - Script nuovo: [exp_boundary_bridge_stability_audit.py](/opt/MM_D-ND/tools/exp_boundary_bridge_stability_audit.py) - Dati: [boundary_bridge_stability_audit_20260515_1915.json](/opt/MM_D-ND/tools/data/boundary_bridge_stability_audit_20260515_1915.json) Verifiche completate: `py_compile`, run esperimento 27/27, controllo report presente/non vuoto, nessuna API key paid nell’ambiente. Risultante: il boundary 8 GUE / 5 Poisson regge come gate a frequenza composita, non come lista fissa di nodi del run 18:55. diff --git a/tools/data/reports/agent_20260515_1915.md b/tools/data/reports/agent_20260515_1915.md new file mode 100644 index 0000000000000000000000000000000000000000..62c085a93c5f830f9f42ef73309544982f4693f3 --- /dev/null +++ b/tools/data/reports/agent_20260515_1915.md @@ -0,0 +1,131 @@ +# Agent Report - Boundary Bridge Stability Audit +**Date**: 2026-05-15 19:15 +**Piano**: 121 +**Tension explored**: BOUNDARY (0.8) +**verdict**: CONSTRAINT - il boundary a due lettori sopravvive come frequenza composita, non come lista fissa di righe del gate 18:55. +observables_registry: 1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined +observables_used: [graph_bridge_frequency, cut_edge_frequency, mean_centroid_margin, mean_cross_neighbor_fraction, classical_audit_state, brody_q, berry_robnick_like_gue_weight] +**observable_contract**: claim=una riga boundary a due lettori e' operativa solo se lo stato graph bridge sopravvive a perturbazioni del lettore e resta auditato dal baseline classico; observable=frequenza graph bridge unita a stato Brody/Berry-Robnik-like; operator=perturbazione parametrica del grafo kNN con join classico row-aligned; generator=boundary_graph_curvature_gate sul denominatore BOUNDARY 13 righe; denominator=13 righe, 8 GUE e 5 Poisson, ripetute su griglia di 27 run; non_possible=stable Lab bridge se la frequenza bridge collassa sotto perturbazione k/n_gaps/seed; not_tested=Hamiltoniane fisiche nuove, unfolding alternativo, scaling asintotico. + +## Respiro fuori-tempo +- **Combo**: A9 terzo incluso + QxG continuo/discreto + grafo/crossover spettrale + tensione BOUNDARY "8 domini GUE, 5 Poisson". +- **Dipolo / punto-zero**: riga ponte stabile / riga ponte parametrica. Punto-zero: la riga row-aligned prima della soglia singola. +- **Piano superiore**: topologia del grafo come lettore perturbabile; il confine e' invariante se resta frequenza, non se resta una soglia. +- **Proto-ipotesi**: il terzo incluso operativo non e' la lista dei nodi `third_included_candidate` di un run. E' la classe composita che resta dopo perturbazione del lettore grafico e audit classico. +- **Possibile/non-possibile**: possibile = usare la frequenza del bridge come gate per finestre fisiche finite; non-possibile = promuovere il set 18:55 come confine canonico. +- **Proiezione**: ripeto il lettore grafico su `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}` e unisco ogni riga allo stato classico del report 19:04. + +### Contaminazione cognitiva +- **CE-0019 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0019 - Respiro fuori-tempo`, letta il 2026-05-15. Enzima usato: combo obbligatoria prima della misura; qui impedisce di aggiungere una metrica locale e forza il passaggio a frequenza topologica. +- **CE-0022 metabolizzata**: `tools/data/cognitive_enzymes_archive.md`, voce `CE-0022 - Palette operatoria espansa del Lab`, letta il 2026-05-15. Enzima usato: gli operatori grafo/curvatura e controllo non restano temi, diventano denominatore perturbato. +- **YSN DeltaLink**: `lista fissa / frequenza stabile`. La sorpresa cercata e' il disaccordo tra riga ponte singola e ponte persistente. +- **Cornelius gene**: `Bridge_Frequency_Gate`: RIPETI lettore, ALLINEA righe, CLASSIFICA frequenza, UNISCI baseline. +- **KSAR step**: perturbazione = k, lunghezza spacing, seed shuffle; focalizzazione = stessa unita' row-aligned; proiezione = composito graph-frequency + classical-state. + +## Aderenza alla direzione +- `relation`: `follows_direction` +- `why`: il ciclo resta sul perimetro vivo 8 GUE / 5 Poisson e misura se il confine come terzo incluso resta operativo quando il lettore viene perturbato. +- `not_drift`: non usa il report Sturmian bloccato, non misura V_c, non usa phi/silver/bronze; il gate 18:55 e il baseline 19:04 sono usati come denominatore row-aligned da stressare, non come autorita' finale. + +## Re-discovery audit +- **Baseline noto piu' vicino**: Brody distribution, Berry-Robnik-like mixture e famiglia Rosenzweig-Porter come riferimento di crossover Hamiltoniano non eseguito. +- **Cosa viene assorbito dal baseline**: `numeri_primi:cycle_3` resta stabile graph bridge 27/27 ed e' anche intermedio classico (`q=0.465`, `w_GUE=0.275`): qui il Lab non separa un fenomeno nuovo dal crossover classico. +- **Cosa resta Lab-specific**: `percolation:cycle_9`, `reaction_diffusion:cycle_11`, `logistica_biforcazione_var_3.5699:cycle_13` sono `stable_graph_bridge+graph_only_bridge`, tutte 27/27. Il baseline classico le legge endpoint-like, il grafo le legge confine stabile. +- **Cosa corregge il report 18:55**: `zeta_zeros:cycle_4` e `random_matrix:cycle_7` erano classic-only/intermediate nel 19:04, ma diventano stable graph bridge nella perturbazione. La soglia singola k=3 sottostima parte del confine. +- **Cosa limita il claim Lab**: `pendolo_doppio:cycle_2` e' stable graph bridge ma endpoint-like classico; senza sistema fisico controllato resta warning di grafo sensibile, non scoperta. + +## Claim Under Test +> Nel perimetro 8/5, il terzo incluso operativo e' una frequenza composita tra ponte grafico perturbato e audit classico; una singola esecuzione del grafo non basta a nominare il boundary. + +## Question +I nodi ponte GUE/Poisson sopravvivono a perturbazioni del lettore, oppure il boundary del 18:55 era una soglia locale? + +## Ritorno fisico +- **Punto fisico sorgente**: transizione spettrale tra repulsione da caos quantistico e indipendenza/localizzazione Poisson. +- **Attraversamento matematico**: frequenza di ponte nel grafo kNN multi-osservabile sotto perturbazione di lettore, unita a Brody/Berry-Robnik-like. +- **Punto fisico di ritorno**: in finestre sperimentali finite, chiamare boundary solo le finestre che hanno stabilita' grafica e audit classico dichiarato; le righe endpoint-stable del grafo diventano candidate da falsificare con Hamiltoniane fisiche. +- **Osservabile/test fisico possibile**: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre con finestre energetiche; misurare `graph_bridge_frequency` e stato Brody/Berry-Robnik sulla stessa riga. +- **Se fallisce**: se le frequenze graph-only spariscono in un sistema controllato, il residuo Lab era composizione del perimetro 13 righe, non boundary fisico. + +## Experiment Design +- **Script**: `tools/exp_boundary_bridge_stability_audit.py`. +- **Input graph/classic**: `tools/data/boundary_denominator_prescan_full_20260509_1500.json` + `tools/data/boundary_classical_crossover_audit_20260515_1904.json`. +- **Run**: `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json`. +- **Denominatore**: 13 righe row-aligned, 8 GUE e 5 Poisson. +- **Griglia**: 27 letture grafiche, `k={2,3,4}`, `n_gaps={512,1024,2048}`, `seed={20260515,20260516,20260517}`, `n_shuffle=32`. +- **Classi**: `stable_graph_bridge` se frequenza >= 0.75; `parameter_sensitive_bridge` se 0.25 <= frequenza < 0.75; `unstable_non_bridge` se frequenza < 0.25. +- **Contratto osservabile-operatore**: il ciclo testa stabilita' del lettore grafico unita al baseline classico; non testa V_c, denominatori Sturmian, Hamiltoniane Rosenzweig-Porter reali o unfolding fisico alternativo. + +## Results +| summary | value | +|---|---:| +| rows analyzed | 13 | +| graph reader runs | 27 | +| lab residue after stability | true | +| stable graph-only bridges | 3 | +| stable classic+graph bridges | 1 | +| classic-only with stable graph absent | 1 | + +| composite state | count | +|---|---:| +| stable_graph_bridge+graph_only_bridge | 3 | +| stable_graph_bridge+classic_and_graph_bridge | 1 | +| stable_graph_bridge+classic_only_intermediate | 2 | +| stable_graph_bridge+endpoint_like | 1 | +| parameter_sensitive_bridge+classic_only_intermediate | 1 | +| parameter_sensitive_bridge+endpoint_like | 1 | +| unstable_non_bridge+classic_only_intermediate | 1 | +| unstable_non_bridge+endpoint_like | 3 | + +| row | classical state | graph frequency | composite | +|---|---|---:|---| +| numeri_primi:cycle_3 | classic_and_graph_bridge | 1.000 | stable_graph_bridge+classic_and_graph_bridge | +| percolation:cycle_9 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| reaction_diffusion:cycle_11 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| logistica_biforcazione_var_3.5699:cycle_13 | graph_only_bridge | 1.000 | stable_graph_bridge+graph_only_bridge | +| zeta_zeros:cycle_4 | classic_only_intermediate | 0.889 | stable_graph_bridge+classic_only_intermediate | +| random_matrix:cycle_7 | classic_only_intermediate | 0.778 | stable_graph_bridge+classic_only_intermediate | +| pendolo_doppio:cycle_2 | endpoint_like | 0.889 | stable_graph_bridge+endpoint_like | +| brownian_motion:cycle_12 | classic_only_intermediate | 0.667 | parameter_sensitive_bridge+classic_only_intermediate | +| logistica_biforcazione:cycle_5 | endpoint_like | 0.667 | parameter_sensitive_bridge+endpoint_like | +| cellular_automata:cycle_8 | classic_only_intermediate | 0.000 | unstable_non_bridge+classic_only_intermediate | + +## Key Findings +1. Verificato: il denominatore resta quello richiesto, 13 righe con 8 GUE e 5 Poisson, ripetute in 27 letture. +2. Verificato: i tre `graph_only_bridge` del 19:04 restano stabili 27/27: `percolation`, `reaction_diffusion`, `logistica_biforcazione_var_3.5699`. +3. Verificato: `numeri_primi` resta ponte sia classico sia grafico, 27/27. +4. Verificato: `zeta_zeros` e `random_matrix` migrano da classic-only a stable graph bridge quando il lettore e' perturbato. Il gate 18:55 era una sezione, non il boundary intero. +5. Verificato: `cellular_automata` resta classic-only senza supporto grafico stabile; il baseline classico contiene informazione che il grafo non deve assorbire. +6. Inferito: il terzo incluso operativo e' il composito `graph_bridge_frequency + classical_audit_state`; una soglia kNN singola perde informazione. + +## Verdict +CONSTRAINT + +Il boundary trasferisce come gate a frequenza composita. La parte Lab-specific sopravvive nei tre stable graph-only bridge; il confine non si chiude nella lista 18:55 e non si riduce a Brody/Berry-Robnik. + +## Bicono della scoperta +- **Due radici**: ponte grafico perturbato; crossover classico. +- **Singolare**: riga row-aligned prima della soglia. +- **Invariante di passaggio**: frequenza graph bridge con stato classico esplicito. +- **Campo di possibilita**: possibile = portare il gate su sistemi fisici controllati; non-possibile = usare una singola soglia kNN o un singolo parametro Brody come terzo incluso. + +## Consecutio +Il prossimo ciclo utile porta il gate composito su un sistema fisico controllato: Rosenzweig-Porter, Anderson/mobility edge o Aubry-Andre. Il target non e' aumentare metriche; e' chiedere se `stable_graph_bridge+graph_only_bridge` sopravvive fuori dal perimetro composito del Lab. + +## Ricadute pratiche +ssp_value: yes. Lo script crea un audit riusabile per stressare ogni gate GUE/Poisson row-aligned e separare ponte stabile, ponte parametrico, re-discovery classica ed endpoint-like. + +## Telemetria +- No API paid run: `ANTHROPIC_API_KEY` e `OPENAI_API_KEY` non presenti nell'ambiente. +- `python tools/dnd_scenario.py --best` eseguito: massimo discriminante locale `TENS_SCALE_TRASCENDENZA_LIMITE`; la direzione viva del campo ha prevalso per il perimetro BOUNDARY 8/5. +- Primo run dello script con ricostruzione ripetuta dello spacing troppo lento; interrotto con `pkill`. Riparazione regressiva: cache delle righe in `tools/exp_boundary_bridge_stability_audit.py`, poi run completo 27/27. +- `python -m py_compile tools/exp_boundary_bridge_stability_audit.py` completato. +- `python tools/exp_boundary_bridge_stability_audit.py --out tools/data/boundary_bridge_stability_audit_20260515_1915.json` completato. +- Worktree gia dirty prima del ciclo; ignorate modifiche non correlate. +- Nessun update del seme. +- Nessuna promozione e nessun public sync. + +## Files +- Script: `tools/exp_boundary_bridge_stability_audit.py` +- Data: `tools/data/boundary_bridge_stability_audit_20260515_1915.json` +- Report: `tools/data/reports/agent_20260515_1915.md` diff --git a/tools/exp_boundary_bridge_stability_audit.py b/tools/exp_boundary_bridge_stability_audit.py new file mode 100644 index 0000000000000000000000000000000000000000..43e64d485a3703f9220f51b522eab75db3b560c6 --- /dev/null +++ b/tools/exp_boundary_bridge_stability_audit.py @@ -0,0 +1,248 @@ +#!/usr/bin/env python3 +""" +Stability audit for the BOUNDARY two-reader gate. + +The audit keeps the 13 row-aligned GUE/Poisson denominator and reruns the graph +reader across small perturbations of k, spacing length, and shuffle seed. It then +joins those frequencies with the classical crossover audit states. +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path +from typing import Any + +from exp_boundary_graph_curvature_gate import ( + compute_observables, + classify_geometry, + load_scope, + row_spacings, + shuffle_z, + standardized_matrix, +) + + +def load_json(path: Path) -> dict[str, Any]: + with path.open(encoding="utf-8") as f: + data = json.load(f) + if not isinstance(data, dict): + raise ValueError(f"{path} must contain a JSON object") + return data + + +def parse_ints(raw: str) -> list[int]: + values = [int(part.strip()) for part in raw.split(",") if part.strip()] + if not values: + raise ValueError("empty integer list") + return values + + +def classical_map(path: Path) -> dict[str, dict[str, Any]]: + audit = load_json(path) + rows = audit.get("rows", []) + if not isinstance(rows, list): + raise ValueError(f"{path} does not contain rows") + return {row["domain_window"]: row for row in rows} + + +def classify_frequency(freq: float) -> str: + if freq >= 0.75: + return "stable_graph_bridge" + if freq >= 0.25: + return "parameter_sensitive_bridge" + return "unstable_non_bridge" + + +def run(args: argparse.Namespace) -> dict[str, Any]: + ks = parse_ints(args.k_values) + n_gaps_values = parse_ints(args.n_gaps_values) + seeds = parse_ints(args.seeds) + classical = classical_map(Path(args.classical_audit)) + + source_rows = load_scope(Path(args.scope)) + selected = [row for row in source_rows if row.get("source_domain_type") in {"GUE", "Poisson"}] + selected = sorted(selected, key=lambda row: int(row["cycle"])) + gap_cache = {row["domain_window"]: row_spacings(row["domain"]) for row in selected} + + runs = [] + row_hits: dict[str, dict[str, Any]] = {} + total_runs = 0 + + for k in ks: + for n_gaps in n_gaps_values: + for seed in seeds: + total_runs += 1 + import numpy as np + + rng = np.random.default_rng(seed) + graph_rows = [] + for source in selected: + gaps = gap_cache[source["domain_window"]] + if len(gaps) < args.min_gaps: + continue + gaps = gaps[:n_gaps] if len(gaps) > n_gaps else gaps + obs = compute_observables(gaps) + z = shuffle_z(gaps, obs, args.n_shuffle, rng) + graph_rows.append( + { + "domain_window": source["domain_window"], + "domain": source["domain"], + "cycle": source["cycle"], + "source_domain_type": source["source_domain_type"], + "n_gaps": int(len(gaps)), + "observables": {key: round(value, 9) for key, value in obs.items()}, + "shuffle_z": {key: round(value, 6) for key, value in z.items()}, + } + ) + graph = { + "summary": {}, + "geometry": classify_geometry(graph_rows, standardized_matrix(graph_rows), k), + } + graph["summary"]["third_included_candidates"] = graph["geometry"]["third_included_candidates"] + graph["summary"]["edge_counts"] = graph["geometry"]["edge_counts"] + candidates = set(graph["summary"]["third_included_candidates"]) + runs.append( + { + "k": k, + "n_gaps": n_gaps, + "seed": seed, + "third_included_candidates": sorted(candidates), + "cross_edges": graph["summary"]["edge_counts"]["cross_label"], + } + ) + for row in graph["geometry"]["rows"]: + name = row["domain_window"] + if name not in row_hits: + row_hits[name] = { + "domain_window": name, + "domain": row["domain"], + "source_domain_type": row["source_domain_type"], + "hit_count": 0, + "cut_edge_count": 0, + "margin_values": [], + "cross_fraction_values": [], + } + if row["boundary_state"] == "third_included_candidate": + row_hits[name]["hit_count"] += 1 + if row["boundary_state"] == "cut_edge": + row_hits[name]["cut_edge_count"] += 1 + row_hits[name]["margin_values"].append(float(row["centroid_margin"])) + row_hits[name]["cross_fraction_values"].append(float(row["cross_neighbor_fraction"])) + + rows = [] + counts: dict[str, int] = {} + for name in sorted(row_hits): + item = row_hits[name] + hit_frequency = item["hit_count"] / total_runs + cut_frequency = item["cut_edge_count"] / total_runs + classic = classical.get(name, {}) + stability_state = classify_frequency(hit_frequency) + composite_state = f"{stability_state}+{classic.get('audit_state', 'missing_classical_audit')}" + row = { + "domain_window": name, + "domain": item["domain"], + "source_domain_type": item["source_domain_type"], + "graph_bridge_hits": item["hit_count"], + "graph_bridge_frequency": round(hit_frequency, 6), + "cut_edge_frequency": round(cut_frequency, 6), + "mean_margin": round(sum(item["margin_values"]) / len(item["margin_values"]), 6), + "mean_cross_neighbor_fraction": round( + sum(item["cross_fraction_values"]) / len(item["cross_fraction_values"]), 6 + ), + "stability_state": stability_state, + "classical_audit_state": classic.get("audit_state"), + "brody_q": classic.get("brody_q"), + "berry_robnick_like_gue_weight": classic.get("berry_robnick_like_gue_weight"), + "composite_state": composite_state, + } + rows.append(row) + counts[composite_state] = counts.get(composite_state, 0) + 1 + + stable_graph_only = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" and row["classical_audit_state"] == "graph_only_bridge" + ] + stable_classic_and_graph = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "stable_graph_bridge" + and row["classical_audit_state"] == "classic_and_graph_bridge" + ] + classic_only_stable_graph_absent = [ + row["domain_window"] + for row in rows + if row["stability_state"] == "unstable_non_bridge" + and row["classical_audit_state"] == "classic_only_intermediate" + ] + + output = { + "experiment": "boundary_bridge_stability_audit", + "question": "Do BOUNDARY graph bridge rows survive small graph-reader perturbations after the classical audit?", + "observables_registry": "1.0.0-2026-05-06 via boundary_graph_curvature_gate; classical audit coordinates joined", + "observables_used": [ + "graph_bridge_frequency", + "cut_edge_frequency", + "mean_centroid_margin", + "mean_cross_neighbor_fraction", + "classical_audit_state", + "brody_q", + "berry_robnick_like_gue_weight", + ], + "params": { + "scope": args.scope, + "classical_audit": args.classical_audit, + "k_values": ks, + "n_gaps_values": n_gaps_values, + "seeds": seeds, + "n_shuffle": args.n_shuffle, + "min_gaps": args.min_gaps, + "total_runs": total_runs, + }, + "observable_contract": { + "claim": "a two-reader boundary row is operational only if graph bridge status is stable enough to survive reader perturbation and remains classically audited", + "observable": "graph bridge hit frequency joined with Brody/Berry-Robnik-like audit state", + "operator": "parameter perturbation over kNN graph reader with row-aligned classical audit join", + "generator": "boundary_graph_curvature_gate over the 13-row BOUNDARY denominator", + "denominator": "13 rows: 8 GUE and 5 Poisson, repeated across graph-reader parameter grid", + "non_possible": "stable Lab bridge if bridge frequency collapses under k/n_gaps/seed perturbation", + "not_tested": "new physical Hamiltonian flow, alternative unfolding, asymptotic scaling beyond this finite denominator", + }, + "summary": { + "rows_analyzed": len(rows), + "graph_reader_runs": total_runs, + "composite_counts": counts, + "stable_graph_only": stable_graph_only, + "stable_classic_and_graph": stable_classic_and_graph, + "classic_only_stable_graph_absent": classic_only_stable_graph_absent, + "lab_residue_after_stability": bool(stable_graph_only or classic_only_stable_graph_absent), + }, + "rows": rows, + "runs": runs, + } + + out = Path(args.out) + out.parent.mkdir(parents=True, exist_ok=True) + out.write_text(json.dumps(output, indent=2, sort_keys=True) + "\n", encoding="utf-8") + print(json.dumps(output["summary"], indent=2, sort_keys=True)) + return output + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--scope", default="tools/data/boundary_denominator_prescan_full_20260509_1500.json") + parser.add_argument("--classical-audit", default="tools/data/boundary_classical_crossover_audit_20260515_1904.json") + parser.add_argument("--k-values", default="2,3,4") + parser.add_argument("--n-gaps-values", default="512,1024,2048") + parser.add_argument("--seeds", default="20260515,20260516,20260517") + parser.add_argument("--n-shuffle", type=int, default=32) + parser.add_argument("--min-gaps", type=int, default=64) + parser.add_argument("--out", default="tools/data/boundary_bridge_stability_audit_20260515_1915.json") + args = parser.parse_args() + run(args) + + +if __name__ == "__main__": + main() tokens used 191,254 Eseguito il cycle e scritto il report richiesto: - Report: [agent_20260515_1915.md](/opt/MM_D-ND/tools/data/reports/agent_20260515_1915.md) - Script nuovo: [exp_boundary_bridge_stability_audit.py](/opt/MM_D-ND/tools/exp_boundary_bridge_stability_audit.py) - Dati: [boundary_bridge_stability_audit_20260515_1915.json](/opt/MM_D-ND/tools/data/boundary_bridge_stability_audit_20260515_1915.json) Verifiche completate: `py_compile`, run esperimento 27/27, controllo report presente/non vuoto, nessuna API key paid nell’ambiente. Risultante: il boundary 8 GUE / 5 Poisson regge come gate a frequenza composita, non come lista fissa di nodi del run 18:55.