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refactor(rrc): rename corpus250→allFixtures/emitManifold, generic n-dimensional modules, Authentik deploy

Browse source 
- Rename python/build_corpus250.py → python/build_manifold.py
- Rename emitCorpus250 → emitManifold, corpus250 → allFixtures
- Schema: avm_rrc_corpus250_v1 → avm_rrc_manifold_v1
- Classify.lean now delegates to ClassifyN (generic n-dim module)
- ClassifyN.hashTable8: extracted 119-entry hash table from old Classify
- build_manifold.py now emits ClassifyN.classifyProxy hashTable8 + classifyExact 8
- build_pist_matrices_250.py: added pistMatrixDim constant
- SilverSight docs/AGENTS.md updated for renames
- Research Stack AGENTS.md updated for toolchain references
- Authentik deployed on neon-64gb (port 30001, working)
- cross_domain_significance.py: statistical significance test (all phases <6σ with n=3)
- setup_authentik.sh: fixed image, password, port, key sharing

Build: 3307 jobs, 0 errors (lake build)
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allaun 2026-06-30 02:49:32 -05:00
parent df60316925
commit 670e7617c3
19 changed files with 6097 additions and 215 deletions
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189
AGENTS.md
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@ -135,6 +135,10 @@ Target: `formal/SilverSight/HachimojiN8.lean` — provable by `native_decide` on
| AVMIsa/TypeCheck.lean | Complete | 0 | | AVMIsa/TypeCheck.lean | Complete | 0 |
| AVMIsa/TypeSafety.lean | Complete | 0 | | AVMIsa/TypeSafety.lean | Complete | 0 |
| AVMIsa/Run.lean | Complete | 0 | | AVMIsa/Run.lean | Complete | 0 |
| RRC/Emit.lean | Complete (Q16_16 ncDerived, alignment gate, 6 fixtures) | 0 |
| RRC/Q16_16Manifold.lean | Complete (278 rows, Q16_16 manifold fields) | 0 |
| RRC/ReceiptDensity.lean | Complete | 0 |
| RRCLogogramProjection.lean | Complete | 0 |
† Layer 3 sorries are geometric conjectures (Kähler on ℂℙ⁷, Cartan connection, † Layer 3 sorries are geometric conjectures (Kähler on ℂℙ⁷, Cartan connection,
holonomy SO⁰(1,6)) deferred pending Mathlib infrastructure. Layer 1 (4 holonomy SO⁰(1,6)) deferred pending Mathlib infrastructure. Layer 1 (4
@ -248,3 +252,188 @@ The VCN-FAMM-Sidon system is a Baker-style transcendental framework where:
- Collapse functional Λ = ∑ wᵢⱼₖₗ log(aᵢ + aⱼ) - Collapse functional Λ = ∑ wᵢⱼₖₗ log(aᵢ + aⱼ)
- Scar energy Ω = ∑ scar.pressure - Scar energy Ω = ∑ scar.pressure
- Theorem: |Λ| ≥ ε(X) ∨ Ω > 0 (rigidity OR scar emission) - Theorem: |Λ| ≥ ε(X) ∨ Ω > 0 (rigidity OR scar emission)
## ncDerived Architecture (2026-06-29)
### Negative Control Witness
```
CSV axioms (ncObserved, residualRisk, scaleBandDeclared, weakAxesNames)
│
▼
ncDerived = Q16_16.mul residualRisk scaleBandDeclared
│
├── ncDerived_mul (simp)
├── ncDerived_independence_justification (CRT product principle link)
└── Output: nc_derived in JSON (via .toFloat at I/O boundary)
```
### Q16_16 Values (Fixture Corpus)
| Row | residualRisk | scaleBandDeclared | ncDerived (raw) | ncDerived (float) |
|-----|-------------|-------------------|-----------------|-------------------|
| Clf/Ssrc | 47/100 | 2/5 | 12320 | 0.187988 |
| Stamp_Code | 11/25 | 1/5 | 5766 | 0.087982 |
| Weak control | 27/50 | 1/5 | 7077 | 0.107986 |
### FFS Physical Analog (Pending Validation)
- arXiv:2602.17656 fractional Fermi sea occupancy ϑ(λ) ≤ 1/(2W+1)
- Maps to ncDerived scale-band: scaleBandDeclared(W) = 1/(2W+1)
- If validated: modulus 128 must change (no odd divisors; see `docs/math/arxiv_2602_17656_model_notes.md`)
- Validation: KS test of ncDerived vs 1/(2W+1) quantization (Step 5, Milestone 7b)
### Files Ported (Research Stack → SilverSight)
| File | Status | Notes |
|------|--------|-------|
| `formal/SilverSight/RRC/Emit.lean` | ✅ Q16_16 ncDerived | Float-free compute path |
| `formal/SilverSight/RRC/Q16_16Manifold.lean` | ✅ 278 rows | Q16_16 manifold fields |
| `python/build_manifold.py` | ✅ Q16_16 emission | `lean_q16_16()` helper |
## Beyond Rigorous — Anti-Smuggle Protocol
LLMs produce coherent-looking outputs that are subtly wrong in non-obvious ways. Every step must be assumed flawed until independently verified by a non-LLM mechanism. This section defines the 5-layer anti-smuggle protocol that enforces dual-sided proof structure across the entire SilverSight pipeline.
### Layer 0: Deterministic Reproducibility Chain
Every artifact must be independently reproducible from source. Non-determinism is the primary vector for smuggled assumptions [5].
```
Source inputs (equations, QUBO params, seeds)
→ SHA-256 hash
→ Python shim (deterministic, seed-locked)
→ Lean build (deterministic)
→ Output JSON
→ SHA-256 receipt (pinned in CITATION.cff)
Independent re-run on different hardware must produce identical hash chain.
If not → non-determinism detected → assumption smuggling possible.
```
**Enforcement:**
- All Python shims must accept `--seed` parameter (default 0)
- All random number generators must be seeded explicitly
- Lean `#eval` outputs must be cached and hashed
- Receipt JSON includes `content_sha256` field for all generated artifacts
### Layer 1: Multi-Model Cross-Validation
No single LLM output stream is trusted. Every formal claim must be independently generated by at least two models and checked for formal equivalence [2][12].
```
LLM A → generates Lean theorem
LLM B → generates Lean theorem (same problem, blind)
↓
Lean compiler verifies both independently
↓
Formal equivalence checker confirms both prove same statement
↓
If one passes and the other fails → BOTH are suspect
```
**Enforcement:**
- Critical theorems (Chentsov, FSR, ncDerived) must have dual provenance
- Cross-validation receipt records both source models + Lean build hash
- Surface-form similarity is NOT equivalence — Lean proofs can be cosmetically identical while logically different
### Layer 2: Adversarial Mutation Testing
The verifier itself must be tested. For every theorem, deliberately introduce errors and verify the system catches them [8].
```bash
# Mutation suite for every theorem in the build surface
mutations/
Emit.lean/
001_flip_ncDerived_mul.lean # expected: FAIL
002_swap_residual_scale.lean # expected: FAIL
003_zero_ncObserved.lean # expected: FAIL
004_float_instead_of_q16.lean # expected: FAIL
```
**Enforcement:**
- `python3 scripts/qc-flag/` must pass on clean build AND fail on each mutation
- Mutation coverage = `#mutations_that_cause_build_failure / #total_mutations`
- If a mutation passes the build → the theorem is not specific enough
### Layer 3: Symbolic Oracle Grounding (CAS/SMT)
Lean proofs can be vacuously true or circular. Every numeric claim must be independently verified by a non-LLM symbolic engine [15][17].
```
Lean computes:
ncDerived = Q16_16.mul (Q16_16.ofRatio 47 100) (Q16_16.ofRatio 2 5)
↓
SymPy computes:
ncDerived = Rational(47,100) * Rational(2,5) = 47/250 = 0.188
↓
Z3 checks:
Assert(lean_output == sympy_output ± epsilon)
```
**Enforcement:**
- All `Q16_16.ofRatio` values must have a corresponding SymPy `Rational` verification
- All `native_decide` blocks must have a Z3 SMT-LIB2 equivalent
- CAS verification receipt stored alongside Lean receipt
### Layer 4: Dual-Sided Proof Structure (Domain-Specific)
For the Hachimoji/QUBO pipeline, the quantum encoding must be verified against a classical ground truth. This is the "clear-box middleware" architecture.
```
Classical Path (ground truth):
DNA sequence → Biopython → expected state vector → SHA-256
Quantum Path (execution):
DNA sequence → Qiskit/PennyLane circuit → measured state → SHA-256
Assertion Layer (every gate):
├── Unitarity preserved? (‖U†U - I‖ < ε)
├── Probability distribution consistent with DNA input?
└── State vector fidelity ≥ threshold?
Cross-Validation:
├── Classical expected == Quantum measured (within noise)
├── If mismatch → LogicViolation exception → data quarantined
└── Log: every state transformation serialized to JSONL for audit
```
**Enforcement:**
- Every circuit gate has an assertion wrapper checking unitarity
- Every measurement logs: `{timestamp, gate, input_state, output_state, fidelity}`
- Third-party observer can reconstruct exact state at any time t from logs alone
- Full audit trail = "traceable proof"
### Layer 5: Claim-State Ladder with Non-LLM Gate
Every claim in the system must occupy one of these states. Promotion requires non-LLM evidence at every rung.
| State | Requirement | LLM Role | Non-LLM Gate |
|-------|------------|----------|-------------|
| **BEAUTIFUL_PROVISIONAL** | Coherent hypothesis | Primary author | None |
| **CALIBRATED_ENGINEERING_DELTA** | CAS/SMT verification | Provide code | SymPy/Z3 check |
| **REVIEWED** | Multi-model cross-validation | Dual provenance | Lean compiler |
| **VERIFIED** | Full reproducibility + adversarial tests | Audited | Mutation suite + hash chain |
**Rule:** No claim may promote from PROVISIONAL to DELTA without a non-LLM symbolic verification. No claim may promote to VERIFIED without a passing mutation suite.
### Entry Gate for Every Commit
Before any formal work is accepted:
```bash
1. Deterministic check: python3 scripts/check_determinism.py # seed-locked, hash-verified
2. Cross-validation: python3 scripts/cross_validate.py # dual LLM provenance check
3. Mutation suite: python3 scripts/qc-flag/ # verify verifier catches errors
4. CAS grounding: python3 scripts/verify_with_sympy.py # numeric ground truth
5. Build gate: lake build SilverSight # Lean compiler
```
All five must pass. If any fails, the commit is quarantined and flagged for human review.
### Summary Table
| Layer | What It Prevents | Tool | Current Status |
|-------|-----------------|------|----------------|
| 0: Determinism | Non-reproducible artifacts | SHA-256, seed-lock | ⚠️ Partial (corpus hashes exist) |
| 1: Cross-validation | Single-LLM blind spots | Multi-model Lean | ❌ Missing |
| 2: Mutation testing | Verifier that passes bad proofs | `scripts/qc-flag/` | ❌ Missing |
| 3: CAS/SMT grounding | Vacuous/tautological proofs | SymPy, Z3 | ❌ Missing |
| 4: Dual-sided proof | Smuggled quantum assumptions | PennyLane, Biopython | ⚠️ Partial (QUBO exists) |
| 5: Claim-state ladder | Unvalidated promotion | Review protocol | ⚠️ Partial (AGENTS.md framework)

19
PORTING_MAP.md
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@ -48,7 +48,7 @@ The source tree is large (~9,600 objects, ~1,300 Lean files). Most of it is expl
| Area | What matters | | Area | What matters |
|------|--------------| |------|--------------|
| `0-Core-Formalism/lean/Semantics/Semantics/` | Proven Lean modules: FixedPoint, SidonSets, SieveLemmas, InteractionGraphSidon, BraidEigensolid, BraidSpherionBridge, AVMIsa.*, RRC.Emit/Corpus250, TransportQUBOBridge, ChentsovBridge. | | `0-Core-Formalism/lean/Semantics/Semantics/` | Proven Lean modules: FixedPoint, SidonSets, SieveLemmas, InteractionGraphSidon, BraidEigensolid, BraidSpherionBridge, AVMIsa.*, RRC.Emit/Q16_16Manifold, TransportQUBOBridge, ChentsovBridge. |
| `4-Infrastructure/shim/` | Python shims: qaoa_adapter.py, qubo_highs.py, benchmark_finsler_qap.py, chaos_game_16d.py, sidon_generation_kernel.py, geometric_entropy_explorer.py, candidate_certification_bridge.py, stack_solidification_audit.py. | | `4-Infrastructure/shim/` | Python shims: qaoa_adapter.py, qubo_highs.py, benchmark_finsler_qap.py, chaos_game_16d.py, sidon_generation_kernel.py, geometric_entropy_explorer.py, candidate_certification_bridge.py, stack_solidification_audit.py. |
| `6-Documentation/docs/` | AGENTS.md strict rules, architecture specs, distilled notes, specs (DP-RRC, Virtio-Net compute, etc.). | | `6-Documentation/docs/` | AGENTS.md strict rules, architecture specs, distilled notes, specs (DP-RRC, Virtio-Net compute, etc.). |
| `5-Applications/text-to-cad/` | CAD/URDF harness and skills. | | `5-Applications/text-to-cad/` | CAD/URDF harness and skills. |
@ -143,7 +143,7 @@ The source tree is large (~9,600 objects, ~1,300 Lean files). Most of it is expl
| `4-Infrastructure/shim/qaoa_adapter.py` | `qubo/qaoa_circuit.py` / `qubo/qubo_builder.py` | 🟠 ADAPT | Split: QUBO builder stays in QUBOLib; Finsler metric moves to MetricLib. | | `4-Infrastructure/shim/qaoa_adapter.py` | `qubo/qaoa_circuit.py` / `qubo/qubo_builder.py` | 🟠 ADAPT | Split: QUBO builder stays in QUBOLib; Finsler metric moves to MetricLib. |
| `4-Infrastructure/shim/qubo_highs.py` | `qubo/classical_solver.py` | 🟠 ADAPT | HiGHS MIP bridge and TSP assignment relaxation. Merge into `classical_solver.py`. | | `4-Infrastructure/shim/qubo_highs.py` | `qubo/classical_solver.py` | 🟠 ADAPT | HiGHS MIP bridge and TSP assignment relaxation. Merge into `classical_solver.py`. |
| `4-Infrastructure/shim/pist_matrix_builder.py` | `python/` | 🟡 PORT | 250-equation PIST matrix builder; produces deterministic 8×8 strand adjacency. | | `4-Infrastructure/shim/pist_matrix_builder.py` | `python/` | 🟡 PORT | 250-equation PIST matrix builder; produces deterministic 8×8 strand adjacency. |
| `4-Infrastructure/shim/build_corpus250.py` | `python/` | 🟠 ADAPT | Generates RRC corpus rows. Refactor to emit SilverSight `LexLib` inputs. | | `4-Infrastructure/shim/build_corpus250.py` | `python/build_manifold.py` | 🟠 ADAPT | Generates RRC manifold rows. Refactored from `build_corpus250.py`; emits `allFixtures`. |
--- ---
@ -181,13 +181,16 @@ The source tree is large (~9,600 objects, ~1,300 Lean files). Most of it is expl
| Research-Stack | SilverSight Target | Status | Notes | | Research-Stack | SilverSight Target | Status | Notes |
|----------------|-------------------|--------|-------| |----------------|-------------------|--------|-------|
| `Semantics.RRC.Emit.lean` | `RRCLib/` | 🟡 PORT | Alignment classifier; emits RRC verdicts. | | `Semantics.RRC.Emit.lean` (ncDerived) | `formal/SilverSight/RRC/Emit.lean` | ✅ PORTED | Q16_16 ncDerived with alignment gate; Float-free compute path (2026-06-29) |
| `Semantics.RRC.Corpus250.lean` | `RRCLib/` | 🟡 PORT | 250-equation raw-feature corpus. | | `Semantics.RRC.Q16_16Manifold.lean` (Q16_16) | `formal/SilverSight/RRC/Q16_16Manifold.lean` | ✅ PORTED | 278 rows with Q16_16 manifold fields; regenerated by `python/build_manifold.py` |
| `Semantics.AVMIsa.Emit.lean` | `RRCLib/` | 🟡 PORT | **Sole output boundary** for top-level receipt JSON. | | `Semantics.AVMIsa.Emit.lean` | `RRCLib/` | 🟡 PORT | **Sole output boundary** for top-level receipt JSON. |
| `Semantics.AVMIsa.Run.lean` | `Core/SilverSightCore.lean` | 🟠 ADAPT | AVM transition/run semantics; SilverSight Core defines its own `δ` transition function. | | `Semantics.RRC.ReceiptDensity.lean` | `formal/SilverSight/RRC/ReceiptDensity.lean` | ✅ PORTED | Receipt density scoring (already existed) |
| `Semantics.RRC.ReceiptDensity.lean` | `RRCLib/` | 🟡 PORT | Receipt density scoring. | | `Semantics.RRCLogogramProjection.lean` | `formal/SilverSight/RRCLogogramProjection.lean` | ✅ PORTED | Logogram receipt types + admission gates |
| `Semantics.RRCLogogramProjection.lean` | `RRCLib/` | 🟡 PORT | Logogram receipt types + admission gates. | | `4-Infrastructure/shim/validate_rrc_predictions.py` | `python/` | 🟠 ADAPT | Validation harness; refactor to SilverSight receipt format |
| `4-Infrastructure/shim/validate_rrc_predictions.py` | `python/` | 🟠 ADAPT | Validation harness; refactor to SilverSight receipt format. | | — | `formal/SilverSight/FFS/Validation.lean` | 🔴 NEW | FFS validation protocol (KS test in Lean) — future SilverSight |
| — | `formal/SilverSight/FFS/ManifoldWitness.lean` | 🔴 NEW | FFS equivalence theorem — future SilverSight |
| — | `formal/SilverSight/FeasibleSet/Theorem.lean` | 🔴 NEW | Feasible-Set Relaxation Theorem (Set.sInter, IsMinimizer) — future SilverSight |
| — | `formal/SilverSight/FeasibleSet/QUBORelaxation.lean` | 🔴 NEW | k-hot QUBO instantiation — future SilverSight |
--- ---

2
docs/PROJECT_MAP.md
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@ -102,7 +102,7 @@
| File | Module | Build Target | Status | Receipt Boundary | Research-Stack Source | Role | | File | Module | Build Target | Status | Receipt Boundary | Research-Stack Source | Role |
|------|--------|--------------|--------|------------------|----------------------|------| |------|--------|--------------|--------|------------------|----------------------|------|
| `python/build_corpus250.py` | — | — | active | — | — | — | | `python/build_manifold.py` | — | — | active | — | — | — |
| `python/build_pist_matrices_250.py` | — | — | active | — | — | — | | `python/build_pist_matrices_250.py` | — | — | active | — | — | — |
| `python/chaos_game.py` | — | — | active | — | `4-Infrastructure/shim/chaos_game_16d.py` | 16D chaos-game basin sampler. | | `python/chaos_game.py` | — | — | active | — | `4-Infrastructure/shim/chaos_game_16d.py` | 16D chaos-game basin sampler. |
| `python/expr_tree.py` | — | — | active | — | — | — | | `python/expr_tree.py` | — | — | active | — | — | — |

4
docs/RRC_REFACTOR_READINESS.md
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@ -89,8 +89,8 @@ python3 python/validate_rrc_predictions.py /tmp/rrc_fixture_emitted.json
## Out of scope (future work) ## Out of scope (future work)
- Full 250-equation `Corpus250` (requires `PIST.Classify`, `PIST.Matrices250`, source JSON). - Full 250-equation `Q16_16Manifold` (requires `PIST.Classify`, `PIST.Matrices250`, source JSON).
- `python/build_corpus250.py` generator for the full corpus. - `python/build_manifold.py` generator for the full corpus.
- PIST classifier surface to populate `pistProxyLabel` / `pistExactLabel` from real matrices. - PIST classifier surface to populate `pistProxyLabel` / `pistExactLabel` from real matrices.
- Concrete `WireFormat`/`LayoutBridge` instances for multi-field Core types such as `BraidState`. - Concrete `WireFormat`/`LayoutBridge` instances for multi-field Core types such as `BraidState`.

4
docs/adversarial_review/ADVERSARIAL_REVIEW_CRYPTO.md
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@ -264,7 +264,7 @@ r = {"sha256": "TBD", ...}
- Fork loops without termination: NOT FOUND - Fork loops without termination: NOT FOUND
- Quine structures: NOT FOUND - Quine structures: NOT FOUND
## 4.2 Finding: Code Generation in build_corpus250.py [LOW] ## 4.2 Finding: Code Generation in build_manifold.py [LOW]
**Description:** The script generates Lean source code from JSON data using string interpolation: **Description:** The script generates Lean source code from JSON data using string interpolation:
```python ```python
@ -619,7 +619,7 @@ U&'\0041' -- Unicode escape
| # | Finding | File | Exploitability | | # | Finding | File | Exploitability |
|---|---------|------|----------------| |---|---------|------|----------------|
| L1 | WebGPU fingerprinting for tracking | dna_webgpu.js | Trivial | | L1 | WebGPU fingerprinting for tracking | dna_webgpu.js | Trivial |
| L2 | Code generation uses string interpolation | build_corpus250.py | Low | | L2 | Code generation uses string interpolation | build_manifold.py | Low |
| L3 | No self-replication bounds needed (none found) | N/A | N/A | | L3 | No self-replication bounds needed (none found) | N/A | N/A |
| L4 | phi_corkscrew roundtrip may fail due to Q16_16 quantization | pist_braid_bridge.py | Moderate | | L4 | phi_corkscrew roundtrip may fail due to Q16_16 quantization | pist_braid_bridge.py | Moderate |
| L5 | Formal proofs limited to 8 canonical states | HachimojiLUT.lean | Theoretical | | L5 | Formal proofs limited to 8 canonical states | HachimojiLUT.lean | Theoretical |

2
docs/generate_research_stack_usage_map.py
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@ -56,7 +56,7 @@ MATH_KINDS = {
"fixedpoint": ["fix16","q16","fixedpoint","saturate","phasemodulus"], "fixedpoint": ["fix16","q16","fixedpoint","saturate","phasemodulus"],
"routing": ["route","cfd","navier","burgers","canal","flow","pressure"], "routing": ["route","cfd","navier","burgers","canal","flow","pressure"],
"avm": ["avmisa","avm","instruction","receipt","emit"], "avm": ["avmisa","avm","instruction","receipt","emit"],
"rrc": ["rrc","corpus250","pist","classif","receipt"], "rrc": ["rrc","manifold","pist","classif","receipt"],
} }
def dominant_kind(text: str) -> str: def dominant_kind(text: str) -> str:

4
docs/research_stack_porting_candidates.md
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@ -211,8 +211,8 @@ Modules with 0 sorries that are imported by at least 3 other modules:
- `braid_mutation_optimizer.py` → `ene` - `braid_mutation_optimizer.py` → `ene`
- `braid_search.py` → `ene` - `braid_search.py` → `ene`
- `braid_vcn_encoder.py` → `ene` - `braid_vcn_encoder.py` → `ene`
- `build_corpus250.py` → `arxiv` - `build_manifold.py` → `arxiv`
- `build_corpus250.py` → `ene` - `build_manifold.py` → `ene`
- `build_math_symbols_db.py` → `ene` - `build_math_symbols_db.py` → `ene`
- `build_pist_matrices_250.py` → `ene` - `build_pist_matrices_250.py` → `ene`
- `burgers_0d_braid_exact.py` → `ene` - `burgers_0d_braid_exact.py` → `ene`

2
exe/RrcEmitFixture.lean
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@ -1,5 +1,5 @@
import SilverSight.AVMIsa.Emit import SilverSight.AVMIsa.Emit
def main : IO UInt32 := do def main : IO UInt32 := do
IO.println SilverSight.AVMIsa.Emit.emitCorpus250 IO.println SilverSight.AVMIsa.Emit.emitManifold
return 0 return 0

14
formal/SilverSight/AVMIsa/Emit.lean
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@ -14,7 +14,7 @@ import SilverSight.AVMIsa.Run
import SilverSight.ReceiptCore import SilverSight.ReceiptCore
import SilverSight.RRCLogogramProjection import SilverSight.RRCLogogramProjection
import SilverSight.RRC.Emit import SilverSight.RRC.Emit
import SilverSight.RRC.Corpus250 import SilverSight.RRC.Q16_16Manifold
namespace SilverSight.AVMIsa.Emit namespace SilverSight.AVMIsa.Emit
@ -226,23 +226,23 @@ def emitFixtureCorpus : String :=
s!"\"summary\":{summaryStr}," ++ s!"\"summary\":{summaryStr}," ++
s!"\"rows\":{classified.rowsJson}}" s!"\"rows\":{classified.rowsJson}}"
open SilverSight.RRC.Corpus250 in open SilverSight.RRC.Q16_16Manifold in
/-- Stamp the full 250-equation corpus: run the alignment gate (RRC.Emit), then /-- Stamp the full manifold: run the alignment gate (RRC.Emit), then
mint an AVM-authority receipt for the whole bundle, and emit JSON. mint an AVM-authority receipt for the whole bundle, and emit JSON.
The AVM canary suite must pass for the bundle receipt to be valid. The AVM canary suite must pass for the bundle receipt to be valid.
Individual row receipts reflect alignment-gate pass/fail independently. -/ Individual row receipts reflect alignment-gate pass/fail independently. -/
def emitCorpus250 : String := def emitManifold : String :=
let classified := SilverSight.RRC.Emit.emitCorpus "rrc_emit_corpus250_v1" corpus250 let classified := SilverSight.RRC.Emit.emitCorpus "rrc_emit_manifold_v1" allFixtures
let avmOk := canaryReceipts.all (·.valid) let avmOk := canaryReceipts.all (·.valid)
let bundleReceipt := leanBuildReceipt "avm.rrc_corpus250.bundle" avmOk let bundleReceipt := leanBuildReceipt "avm.rrc.manifold.bundle" avmOk
let total := classified.totalRows let total := classified.totalRows
let passed := classified.candidateRows let passed := classified.candidateRows
let held := total - passed let held := total - passed
let summaryStr := let summaryStr :=
s!"\{\"total\":{total},\"passed_alignment\":{passed},\"held\":{held}," ++ s!"\{\"total\":{total},\"passed_alignment\":{passed},\"held\":{held}," ++
s!"\"not_promoted\":{total}}" s!"\"not_promoted\":{total}}"
s!"\{\"schema\":\"avm_rrc_corpus250_v1\"," ++ s!"\{\"schema\":\"avm_rrc_manifold_v1\"," ++
s!"\"claim_boundary\":\"admissibility-and-routing-pass-only;not-promoted\"," ++ s!"\"claim_boundary\":\"admissibility-and-routing-pass-only;not-promoted\"," ++
s!"\"avm_canaries_passed\":{jsonBool avmOk}," ++ s!"\"avm_canaries_passed\":{jsonBool avmOk}," ++
s!"\"bundle_receipt_valid\":{jsonBool bundleReceipt.valid}," ++ s!"\"bundle_receipt_valid\":{jsonBool bundleReceipt.valid}," ++

200
formal/SilverSight/PIST/Classify.lean
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@ -1,70 +1,21 @@
-- SilverSight.PIST.Classify — minimal RRC shape classifier over 8×8 matrices -- SilverSight.PIST.Classify — backward-compat shim for 8×8 matrices.
-- --
-- Ports only the classifier surface needed for Corpus250: -- All classification logic now lives in SilverSight.PIST.ClassifyN.
-- • 8×8 braid adjacency matrix type -- This module re-exports the old API surface under the same names.
-- • spectral-radius → RGB color → shape-name gate
-- • matrix-hash lookup table (proxy classifier)
-- • spectral-radius exact classifier
-- • deterministic blending rules for shared equation_ids
-- --
-- Photonic/Kubelka-Munk/Quandela extensions from Research Stack are omitted. -- Blending rules (§4) remain here since they are not yet generalized.
import SilverSight.PIST.Spectral import SilverSight.PIST.ClassifyN
import SilverSight.FixedPoint
namespace SilverSight.PIST.Classify namespace SilverSight.PIST.Classify
open SilverSight.FixedPoint open SilverSight.PIST.ClassifyN
open SilverSight.FixedPoint.Q16_16
open SilverSight.PIST.Spectral
-- ───────────────────────────────────────────────────────────────────────────── -- ── §1 Matrix type ────────────────────────────────────────────────────
-- §1 Matrix type
-- ─────────────────────────────────────────────────────────────────────────────
abbrev Matrix8 : Type := Array (Array Int) abbrev Matrix8 : Type := Array (Array Int)
-- ───────────────────────────────────────────────────────────────────────────── -- ── §2 Blending rules (not yet generalized) ───────────────────────────
-- §2 Spectral-radius thresholds
-- ─────────────────────────────────────────────────────────────────────────────
/-- High amplification threshold: λ ≥ 4.0 (Q16.16 raw). -/
def oberthHighThreshold : Int := 262144
/-- Moderate amplification threshold: λ ≥ 2.0 (Q16.16 raw). -/
def signalThreshold : Int := 131072
-- ─────────────────────────────────────────────────────────────────────────────
-- §3 Spectral color gate
-- ─────────────────────────────────────────────────────────────────────────────
structure SpectralColor where
red : Q16_16
green : Q16_16
blue : Q16_16
deriving Repr
/-- Convert a raw spectral radius (Int) to an RGB SpectralColor. -/
def spectralRadiusToColor (lam : Int) : SpectralColor :=
let max_raw := oberthHighThreshold
let r := if lam ≥ max_raw then one else zero
let g := if lam ≥ signalThreshold then
ofRawInt ((lam - signalThreshold) * 65536 / (max_raw - signalThreshold))
else zero
let b := if lam < signalThreshold then
ofRawInt (lam * 65536 / signalThreshold)
else zero
{ red := r, green := g, blue := b }
/-- Extract the shape-name string from a SpectralColor. -/
def colorToShapeName (c : SpectralColor) : Option String :=
if c.red.toInt > 0 then some "CognitiveLoadField"
else if c.green.toInt > 0 then some "SignalShapedRouteCompiler"
else none
-- ─────────────────────────────────────────────────────────────────────────────
-- §4 Blending rules for shared equation_ids
-- ─────────────────────────────────────────────────────────────────────────────
inductive BlendType where inductive BlendType where
| additive | additive
@ -72,8 +23,7 @@ inductive BlendType where
| vortex | vortex
deriving Repr deriving Repr
def blend_additive (lam1 lam2 : Int) : Int := def blend_additive (lam1 lam2 : Int) : Int := max lam1 lam2
max lam1 lam2
def blend_rms (lam1 lam2 : Int) : Int := def blend_rms (lam1 lam2 : Int) : Int :=
Int.ofNat (Nat.sqrt (((lam1 * lam1 + lam2 * lam2) / 2).toNat)) Int.ofNat (Nat.sqrt (((lam1 * lam1 + lam2 * lam2) / 2).toNat))
@ -81,7 +31,6 @@ def blend_rms (lam1 lam2 : Int) : Int :=
def blend_vortex (lam1 lam2 : Int) : Int := def blend_vortex (lam1 lam2 : Int) : Int :=
(lam1 * lam2) / (lam1 + lam2 + 1) (lam1 * lam2) / (lam1 + lam2 + 1)
/-- Blend a list of spectral radii under a given topology. -/
def blendRadii (blendType : BlendType) (lams : List Int) : Int := def blendRadii (blendType : BlendType) (lams : List Int) : Int :=
match lams with match lams with
| [] => 0 | [] => 0
@ -93,137 +42,12 @@ def blendRadii (blendType : BlendType) (lams : List Int) : Int :=
| .vortex => (acc * lam2) / (acc + lam2 + 1) | .vortex => (acc * lam2) / (acc + lam2 + 1)
) lam ) lam
-- ───────────────────────────────────────────────────────────────────────────── -- ── §3 Classifier surface (delegates to ClassifyN) ────────────────────
-- §5 Classifier surface
-- ─────────────────────────────────────────────────────────────────────────────
def hashMatrix (m : Matrix8) : Int :=
let rec loop (i j : Nat) (pow_5 : Int) (acc : Int) : Int :=
if i ≥ 8 then acc
else if j ≥ 8 then loop (i + 1) 0 pow_5 acc
else
let val := m.getD i #[] |>.getD j 0
loop i (j + 1) (pow_5 * 5) (acc + val * pow_5)
loop 0 0 1 0
/-- Advisory shape proxy via matrix-hash lookup. -/
def classifyProxy (m : Matrix8) : Option String := def classifyProxy (m : Matrix8) : Option String :=
match hashMatrix m with ClassifyN.classifyProxy ClassifyN.hashTable8 m
| 0 => some "CognitiveLoadField"
| 25 => some "CognitiveLoadField"
| 125 => some "CognitiveLoadField"
| 625 => some "CognitiveLoadField"
| 78125 => some "SignalShapedRouteCompiler"
| 390625 => some "CognitiveLoadField"
| 1953125 => some "SignalShapedRouteCompiler"
| 9765625 => some "ProjectableGeometryTopology"
| 48828125 => some "ProjectableGeometryTopology"
| 244140625 => some "SignalShapedRouteCompiler"
| 30517578125 => some "ProjectableGeometryTopology"
| 152587890625 => some "ProjectableGeometryTopology"
| 152587968750 => some "ProjectableGeometryTopology"
| 3814697265625 => some "SignalShapedRouteCompiler"
| 19073496093750 => some "CognitiveLoadField"
| 476837158203150 => some "CadForceProbeReceipt"
| 2384185791015625 => some "ProjectableGeometryTopology"
| 11920928955078125 => some "ProjectableGeometryTopology"
| 59604644775390626 => some "ProjectableGeometryTopology"
| 59604644824218750 => some "CognitiveLoadField"
| 298023223876953125 => some "ProjectableGeometryTopology"
| 1490116119384765625 => some "ProjectableGeometryTopology"
| 1490211486816406250 => some "ProjectableGeometryTopology"
| 1502037048339843750 => some "CognitiveLoadField"
| 7450580596923828125 => some "ProjectableGeometryTopology"
| 7510185241699218875 => some "ProjectableGeometryTopology"
| 37252902984619140625 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 186264514923095703125 => some "ProjectableGeometryTopology"
| 931322574615478515625 => some "ProjectableGeometryTopology"
| 4656612873077392578125 => some "CognitiveLoadField"
| 4656612873077441406250 => some "CognitiveLoadField"
| 23283064365386962890625 => some "ProjectableGeometryTopology"
| 23283064365386962890626 => some "ProjectableGeometryTopology"
| 23283064365386962890630 => some "CognitiveLoadField"
| 23283064365386962890750 => some "SignalShapedRouteCompiler"
| 23320317268371582031250 => some "SignalShapedRouteCompiler"
| 116415321826934814453125 => some "SignalShapedRouteCompiler"
| 116415321826965576171875 => some "SignalShapedRouteCompiler"
| 582076609135443115234375 => some "CognitiveLoadField"
| 582076621055603027343750 => some "CognitiveLoadField"
| 2910383343696594482421875 => some "CognitiveLoadField"
| 2910420298576354980468750 => some "CognitiveLoadField"
| 14575198292732238769531250 => some "SignalShapedRouteCompiler"
| 17462298274040222167968750 => some "SignalShapedRouteCompiler"
| 72759576141929626464843750 => some "CognitiveLoadField"
| 363797917962074279785156250 => some "CognitiveLoadField"
| 9094947017729282379150390625 => some "CognitiveLoadField"
| 9094947017729759216308593750 => some "ProjectableGeometryTopology"
| 9094947203993797302246093750 => some "SignalShapedRouteCompiler"
| 45474735088646411895751953125 => some "ProjectableGeometryTopology"
| 45474735088646412048339846876 => some "CognitiveLoadField"
| 45547494664788246155029687500 => some "CognitiveLoadField"
| 227373675443232059478759765625 => some "SignalShapedRouteCompiler"
| 227373675443232060241699609375 => some "ProjectableGeometryTopology"
| 227373675443232063293457031250 => some "ProjectableGeometryTopology"
| 227373675443234443664550781250 => some "CognitiveLoadField"
| 227446435019376277923828125000 => some "CognitiveLoadField"
| 5684341886080801486968994140625 => some "ProjectableGeometryTopology"
| 5684414668940007686615234375000 => some "CognitiveLoadField"
| 28421709430404007911682128906250 => some "CognitiveLoadField"
| 28421709430405498027801513671875 => some "CognitiveLoadField"
| 56843418860808014869689941406250 => some "CognitiveLoadField"
| 56843491620384156703949218750000 => some "CognitiveLoadField"
| 142108547152020037174226074218750 => some "ProjectableGeometryTopology"
| 142108547152021527767181396484375 => some "CognitiveLoadField"
| 170530256582424044609069824218750 => some "CognitiveLoadField"
| 710542735760100185871124267578125 => some "ProjectableGeometryTopology"
| 3552713678800500929355621337890750 => some "CognitiveLoadField"
| 3552713678800500929355621337893750 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 3694822225952520966529846191409375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 17763568394002504646778106689453125 => some "ProjectableGeometryTopology"
| 17763568394002504646778106689468750 => some "ProjectableGeometryTopology"
| 17763568394002504646778106933593750 => some "ProjectableGeometryTopology"
| 17763568394002504646778107910156250 => some "ProjectableGeometryTopology"
| 17905676941154524683952331542971875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 17905677013914100825786590820312500 => some "SignalShapedRouteCompiler"
| 88817841970012523233890533447265625 => some "ProjectableGeometryTopology"
| 88817841970594599845409393554687500 => some "SignalShapedRouteCompiler"
| 88817842333810441195964813232421875 => some "SignalShapedRouteCompiler"
| 88959950517164543271064758300784375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 444089209850062616169452667236328125 => some "CognitiveLoadField"
| 444231318397214636206626892089846875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 2220446049250313080847263336181640625 => some "ProjectableGeometryTopology"
| 2220446049250313080849647521972656250 => some "SignalShapedRouteCompiler"
| 2220588157797465100884437561035159375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 11102372354798717424273490905761721875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 55511151231257827021183967590341796875 => some "CognitiveLoadField"
| 55511293339804979041218757629394534375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 277555756156289135105907917022705078125 => some "CognitiveLoadField"
| 277555898264836287125945091247558596875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 1387778780781445675529539585113525391250 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 1387778780781445680186152458190917968750 => some "CognitiveLoadField"
| 1387778780781446257606160640716552734375 => some "CognitiveLoadField"
| 1387778780783264664933085441589355468750 => some "CognitiveLoadField"
| 1387779491324181435629725456237792968750 => some "CognitiveLoadField"
| 6938893903907228377647697925567628906250 => some "SignalShapedRouteCompiler"
| 173472347597680709441192448139190673828125 => some "ProjectableGeometryTopology"
| 173472347597680709441229701042175292968750 => some "ProjectableGeometryTopology"
| 867361737988403547205963742733001708984375 => some "CognitiveLoadField"
| 867361737988405366195403039455413818359375 => some "CognitiveLoadField"
| 867361738698946282966062426567077636718750 => some "CognitiveLoadField"
| 4336808689947702077915892004966735839843750 => some "SignalShapedRouteCompiler"
| 4337086245698174025164917111396789550781250 => some "ProjectableGeometryTopology"
| 4337086245698174025164917113780975341796875 => some "ProjectableGeometryTopology"
| 8673617380594578207819722592830657958984375 => some "ProjectableGeometryTopology"
| 21684321005466244969284161925315856933593750 => some "SignalShapedRouteCompiler"
| 108420217248550443400745280086994171142578125 => some "ProjectableGeometryTopology"
| 108420217248550443400745280086994201660156250 => some "CognitiveLoadField"
| 108420217248550443400745280098915100097656250 => some "CognitiveLoadField"
| _ => none
/-- Attested shape exact match via spectral-radius color gate. -/
def classifyExact (m : Matrix8) : Option String := def classifyExact (m : Matrix8) : Option String :=
let profile := computeSpectral m ClassifyN.classifyExact 8 m
let lam := profile.adjacency_eigenvalue_max.toInt
colorToShapeName (spectralRadiusToColor lam)
end SilverSight.PIST.Classify end SilverSight.PIST.Classify

224
formal/SilverSight/PIST/ClassifyN.lean Normal file
View file

@ -0,0 +1,224 @@
/-
Copyright (c) 2026 SilverSight Contributors. All rights reserved.
Released under Apache 2.0 license.
Generic n-dimensional RRC shape classifier.
Unlike Classify.lean (which fixes n=8), this version is parameterized
by matrix dimension (n : Nat).
The proxy classifier uses an externally-provided hash table, since
matrix hashes are dimension-dependent.
-/
import SilverSight.FixedPoint
import SilverSight.PIST.MatrixN
import SilverSight.PIST.SpectralN
namespace SilverSight.PIST.ClassifyN
open SilverSight.FixedPoint
open SilverSight.FixedPoint.Q16_16
open SilverSight.PIST.MatrixN
open SilverSight.PIST.SpectralN
-- ── Spectral-radius thresholds (dimension-independent) ───────────────────
/-- High amplification: λ ≥ 4.0 (Q16.16 raw 262144). -/
def oberthHighThreshold : Int := 262144
/-- Moderate amplification: λ ≥ 2.0 (Q16.16 raw 131072). -/
def signalThreshold : Int := 131072
-- ── Spectral color gate (dimension-independent) ─────────────────────────
structure SpectralColor where
red : Q16_16
green : Q16_16
blue : Q16_16
deriving Repr
def spectralRadiusToColor (lam : Int) : SpectralColor :=
let max_raw := oberthHighThreshold
let r := if lam ≥ max_raw then one else zero
let g := if lam ≥ signalThreshold then
ofRawInt ((lam - signalThreshold) * 65536 / (max_raw - signalThreshold))
else zero
let b := if lam < signalThreshold then
ofRawInt (lam * 65536 / signalThreshold)
else zero
{ red := r, green := g, blue := b }
def colorToShapeName (c : SpectralColor) : Option String :=
if c.red.toInt > 0 then some "CognitiveLoadField"
else if c.green.toInt > 0 then some "SignalShapedRouteCompiler"
else none
-- ── Blending rules (dimension-independent) ──────────────────────────────
inductive BlendType where
| additive
| rms
| vortex
deriving Repr
def blend_additive (lam1 lam2 : Int) : Int := max lam1 lam2
def blend_rms (lam1 lam2 : Int) : Int :=
Int.ofNat (Nat.sqrt (((lam1 * lam1 + lam2 * lam2) / 2).toNat))
def blend_vortex (lam1 lam2 : Int) : Int :=
(lam1 * lam2) / (lam1 + lam2 + 1)
def blendRadii (blendType : BlendType) (lams : List Int) : Int :=
match lams with
| [] => 0
| lam :: rest =>
rest.foldl (fun acc lam2 =>
match blendType with
| .additive => if acc ≥ lam2 then acc else lam2
| .rms => isqrt ((acc * acc + lam2 * lam2) / 2)
| .vortex => (acc * lam2) / (acc + lam2 + 1)
) lam
-- ── Generic hash for n×n matrices ───────────────────────────────────────
def hashMatrix (n : Nat) (mat : Array (Array Int)) : Int :=
let rec loop (i j : Nat) (pow_5 : Int) (acc : Int) : Int :=
if i ≥ n then acc
else if j ≥ n then loop (i + 1) 0 pow_5 acc
else
let val := mat.getD i #[] |>.getD j 0
loop i (j + 1) (pow_5 * 5) (acc + val * pow_5)
loop 0 0 1 0
-- ── Proxy classifier (external hash table) ──────────────────────────────
/-- Proxy classify using an externally-provided hash-to-shape table.
The table must be generated per-dimension (the Python rebuild script
handles this for n=8 via rrc_pist_predictions_250_v1.json). -/
def classifyProxy (hashTable : Int → Option String) (mat : Array (Array Int)) : Option String :=
hashTable (hashMatrix 8 mat)
/- Exact classifier via spectral radius. Dimension-independent. -/
def classifyExact (n : Nat) (mat : Array (Array Int)) : Option String :=
let profile := computeSpectral n mat
let lam := profile.adjacency_eigenvalue_max.toInt
colorToShapeName (spectralRadiusToColor lam)
/-- Canonical 8×8 hash-to-shape table.
Generated from the hardcoded lookup table in SilverSight.PIST.Classify.
Maps `hashMatrix 8` values to PIST shape names. -/
def hashTable8 : Int → Option String :=
fun h => match h with
| 0 => some "CognitiveLoadField"
| 25 => some "CognitiveLoadField"
| 125 => some "CognitiveLoadField"
| 625 => some "CognitiveLoadField"
| 78125 => some "SignalShapedRouteCompiler"
| 390625 => some "CognitiveLoadField"
| 1953125 => some "SignalShapedRouteCompiler"
| 9765625 => some "ProjectableGeometryTopology"
| 48828125 => some "ProjectableGeometryTopology"
| 244140625 => some "SignalShapedRouteCompiler"
| 30517578125 => some "ProjectableGeometryTopology"
| 152587890625 => some "ProjectableGeometryTopology"
| 152587968750 => some "ProjectableGeometryTopology"
| 3814697265625 => some "SignalShapedRouteCompiler"
| 19073496093750 => some "CognitiveLoadField"
| 476837158203150 => some "CadForceProbeReceipt"
| 2384185791015625 => some "ProjectableGeometryTopology"
| 11920928955078125 => some "ProjectableGeometryTopology"
| 59604644775390626 => some "ProjectableGeometryTopology"
| 59604644824218750 => some "CognitiveLoadField"
| 298023223876953125 => some "ProjectableGeometryTopology"
| 1490116119384765625 => some "ProjectableGeometryTopology"
| 1490211486816406250 => some "ProjectableGeometryTopology"
| 1502037048339843750 => some "CognitiveLoadField"
| 7450580596923828125 => some "ProjectableGeometryTopology"
| 7510185241699218875 => some "ProjectableGeometryTopology"
| 37252902984619140625 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 186264514923095703125 => some "ProjectableGeometryTopology"
| 931322574615478515625 => some "ProjectableGeometryTopology"
| 4656612873077392578125 => some "CognitiveLoadField"
| 4656612873077441406250 => some "CognitiveLoadField"
| 23283064365386962890625 => some "ProjectableGeometryTopology"
| 23283064365386962890626 => some "ProjectableGeometryTopology"
| 23283064365386962890630 => some "CognitiveLoadField"
| 23283064365386962890750 => some "SignalShapedRouteCompiler"
| 23320317268371582031250 => some "SignalShapedRouteCompiler"
| 116415321826934814453125 => some "SignalShapedRouteCompiler"
| 116415321826965576171875 => some "SignalShapedRouteCompiler"
| 582076609135443115234375 => some "CognitiveLoadField"
| 582076621055603027343750 => some "CognitiveLoadField"
| 2910383343696594482421875 => some "CognitiveLoadField"
| 2910420298576354980468750 => some "CognitiveLoadField"
| 14575198292732238769531250 => some "SignalShapedRouteCompiler"
| 17462298274040222167968750 => some "SignalShapedRouteCompiler"
| 72759576141929626464843750 => some "CognitiveLoadField"
| 363797917962074279785156250 => some "CognitiveLoadField"
| 9094947017729282379150390625 => some "CognitiveLoadField"
| 9094947017729759216308593750 => some "ProjectableGeometryTopology"
| 9094947203993797302246093750 => some "SignalShapedRouteCompiler"
| 45474735088646411895751953125 => some "ProjectableGeometryTopology"
| 45474735088646412048339846876 => some "CognitiveLoadField"
| 45547494664788246155029687500 => some "CognitiveLoadField"
| 227373675443232059478759765625 => some "SignalShapedRouteCompiler"
| 227373675443232060241699609375 => some "ProjectableGeometryTopology"
| 227373675443232063293457031250 => some "ProjectableGeometryTopology"
| 227373675443234443664550781250 => some "CognitiveLoadField"
| 227446435019376277923828125000 => some "CognitiveLoadField"
| 5684341886080801486968994140625 => some "ProjectableGeometryTopology"
| 5684414668940007686615234375000 => some "CognitiveLoadField"
| 28421709430404007911682128906250 => some "CognitiveLoadField"
| 28421709430405498027801513671875 => some "CognitiveLoadField"
| 56843418860808014869689941406250 => some "CognitiveLoadField"
| 56843491620384156703949218750000 => some "CognitiveLoadField"
| 142108547152020037174226074218750 => some "ProjectableGeometryTopology"
| 142108547152021527767181396484375 => some "CognitiveLoadField"
| 170530256582424044609069824218750 => some "CognitiveLoadField"
| 710542735760100185871124267578125 => some "ProjectableGeometryTopology"
| 3552713678800500929355621337890750 => some "CognitiveLoadField"
| 3552713678800500929355621337893750 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 3694822225952520966529846191409375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 17763568394002504646778106689453125 => some "ProjectableGeometryTopology"
| 17763568394002504646778106689468750 => some "ProjectableGeometryTopology"
| 17763568394002504646778106933593750 => some "ProjectableGeometryTopology"
| 17763568394002504646778107910156250 => some "ProjectableGeometryTopology"
| 17905676941154524683952331542971875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 17905677013914100825786590820312500 => some "SignalShapedRouteCompiler"
| 88817841970012523233890533447265625 => some "ProjectableGeometryTopology"
| 88817841970594599845409393554687500 => some "SignalShapedRouteCompiler"
| 88817842333810441195964813232421875 => some "SignalShapedRouteCompiler"
| 88959950517164543271064758300784375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 444089209850062616169452667236328125 => some "CognitiveLoadField"
| 444231318397214636206626892089846875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 2220446049250313080847263336181640625 => some "ProjectableGeometryTopology"
| 2220446049250313080849647521972656250 => some "SignalShapedRouteCompiler"
| 2220588157797465100884437561035159375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 11102372354798717424273490905761721875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 55511151231257827021183967590341796875 => some "CognitiveLoadField"
| 55511293339804979041218757629394534375 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 277555756156289135105907917022705078125 => some "CognitiveLoadField"
| 277555898264836287125945091247558596875 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 1387778780781445675529539585113525391250 => some "HoldForUnlawfulOrUnderspecifiedShape"
| 1387778780781445680186152458190917968750 => some "CognitiveLoadField"
| 1387778780781446257606160640716552734375 => some "CognitiveLoadField"
| 1387778780783264664933085441589355468750 => some "CognitiveLoadField"
| 1387779491324181435629725456237792968750 => some "CognitiveLoadField"
| 6938893903907228377647697925567628906250 => some "SignalShapedRouteCompiler"
| 173472347597680709441192448139190673828125 => some "ProjectableGeometryTopology"
| 173472347597680709441229701042175292968750 => some "ProjectableGeometryTopology"
| 867361737988403547205963742733001708984375 => some "CognitiveLoadField"
| 867361737988405366195403039455413818359375 => some "CognitiveLoadField"
| 867361738698946282966062426567077636718750 => some "CognitiveLoadField"
| 4336808689947702077915892004966735839843750 => some "SignalShapedRouteCompiler"
| 4337086245698174025164917111396789550781250 => some "ProjectableGeometryTopology"
| 4337086245698174025164917113780975341796875 => some "ProjectableGeometryTopology"
| 8673617380594578207819722592830657958984375 => some "ProjectableGeometryTopology"
| 21684321005466244969284161925315856933593750 => some "SignalShapedRouteCompiler"
| 108420217248550443400745280086994171142578125 => some "ProjectableGeometryTopology"
| 108420217248550443400745280086994201660156250 => some "CognitiveLoadField"
| 108420217248550443400745280098915100097656250 => some "CognitiveLoadField"
| _ => none
end SilverSight.PIST.ClassifyN

5040
formal/SilverSight/RRC/Q16_16Manifold.lean Normal file
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11
lakefile.lean
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@ -19,6 +19,7 @@ lean_lib «SilverSightFormal» where
srcDir := "formal" srcDir := "formal"
roots := #[ roots := #[
`CoreFormalism.FixedPoint, `CoreFormalism.FixedPoint,
`SilverSight.FixedPointBridge,
`CoreFormalism.Tactics, `CoreFormalism.Tactics,
`CoreFormalism.Q16_16Numerics, `CoreFormalism.Q16_16Numerics,
`CoreFormalism.DynamicCanal, `CoreFormalism.DynamicCanal,
@ -27,6 +28,7 @@ lean_lib «SilverSightFormal» where
`CoreFormalism.BraidStrand, `CoreFormalism.BraidStrand,
`CoreFormalism.BraidCross, `CoreFormalism.BraidCross,
`CoreFormalism.BraidField, `CoreFormalism.BraidField,
`CoreFormalism.BraidStateN,
`CoreFormalism.SidonSets, `CoreFormalism.SidonSets,
`CoreFormalism.SieveLemmas, `CoreFormalism.SieveLemmas,
`CoreFormalism.InteractionGraphSidon, `CoreFormalism.InteractionGraphSidon,
@ -59,8 +61,12 @@ lean_lib «SilverSightRRC» where
`SilverSight.PhiConsistency, `SilverSight.PhiConsistency,
`SilverSight.PhiPipelineReceipt, `SilverSight.PhiPipelineReceipt,
`SilverSight.PIST.Spectral, `SilverSight.PIST.Spectral,
`SilverSight.PIST.SpectralN,
`SilverSight.PIST.MatrixN,
`SilverSight.PIST.FisherRigidity, `SilverSight.PIST.FisherRigidity,
`SilverSight.PIST.FisherRigidityN,
`SilverSight.PIST.Classify, `SilverSight.PIST.Classify,
`SilverSight.PIST.ClassifyN,
`SilverSight.PIST.Matrices250, `SilverSight.PIST.Matrices250,
`SilverSight.PIST.UnifiedCovariant, `SilverSight.PIST.UnifiedCovariant,
`SilverSight.PIST.CartanConnection, `SilverSight.PIST.CartanConnection,
@ -74,7 +80,7 @@ lean_lib «SilverSightRRC» where
`SilverSight.RRC.ReceiptDensity, `SilverSight.RRC.ReceiptDensity,
`SilverSight.RRC.PolyFactorIdentity, `SilverSight.RRC.PolyFactorIdentity,
`SilverSight.RRC.EntropyCandidates, `SilverSight.RRC.EntropyCandidates,
`SilverSight.RRC.Corpus250, `SilverSight.RRC.Q16_16Manifold,
`SilverSight.AVMIsa.Types, `SilverSight.AVMIsa.Types,
`SilverSight.AVMIsa.Value, `SilverSight.AVMIsa.Value,
`SilverSight.AVMIsa.Instr, `SilverSight.AVMIsa.Instr,
@ -87,6 +93,9 @@ lean_lib «SilverSightRRC» where
`SilverSight.AdjugateMatrix, `SilverSight.AdjugateMatrix,
`SilverSight.ColdReviewer, `SilverSight.ColdReviewer,
`SilverSight.Rollup, `SilverSight.Rollup,
`SilverSight.FeasibleSet.Theorem,
`SilverSight.FeasibleSet.QUBORelaxation,
`SilverSight.CollectiveIntelligence.CostTransparency,
`RRCLib.RRCEmit `RRCLib.RRCEmit
] ]

258
python/build_manifold.py Normal file
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@ -0,0 +1,258 @@
#!/usr/bin/env python3
# /// script
# requires-python = ">=3.10"
# dependencies = []
# ///
"""
Build formal/SilverSight/RRC/Q16_16Manifold.lean from
archive/experimental-shim-probes/rrc_equation_classifier_receipt.json,
merged with 8×8 braid adjacency matrices from
shared-data/rrc_pist_predictions_250_v1.json.
Python's role:
- read raw features from the classifier receipt
- merge matrices by invariant_receipt.object_id
- emit deterministic Lean source
Lean's role:
- PIST classification (classifyProxy/classifyExact) from the matrix
- alignment gate via determineAlignment
- receipt stamping and all admissibility/promotion decisions
Usage:
python3 python/build_manifold.py
python3 python/build_manifold.py \
--receipt /path/to/rrc_equation_classifier_receipt.json \
--predictions /path/to/rrc_pist_predictions_250_v1.json \
--out-lean formal/SilverSight/RRC/Q16_16Manifold.lean
"""
from __future__ import annotations
import argparse, hashlib, json, sys
from pathlib import Path
# classifier JSON shape name → SilverSight.RRCLogogramProjection.RRCShape constructor
SHAPE_MAP = {
"CognitiveLoadField": ".cognitiveLoadField",
"SignalShapedRouteCompiler": ".signalShapedRouteCompiler",
"ProjectableGeometryTopology": ".projectableGeometryTopology",
"CadForceProbeReceipt": ".cadForceProbeReceipt",
"LogogramProjection": ".logogramProjection",
"HoldForUnlawfulOrUnderspecifiedShape": ".holdForUnlawfulOrUnderspecifiedShape",
}
def template_key(rrc_kind: str, status: str) -> str:
"""Map rrc_kind + classifier status to a page-generator template key."""
if status == "HOLD":
return "hold"
kind_map = {
"cognitive_field_receipt": "definition",
"compression_route_prior": "master_equation",
"geometry_topology_receipt": "definition",
"cad_force_receipt": "gate",
"logogram_projection": "receipt",
"negative_control": "hold",
}
return kind_map.get(rrc_kind, "definition")
def operator_tokens(er: dict) -> list[str]:
"""Derive operator/domain tokens from route_hint, rrc_kind, and equation text."""
tokens = []
rh = (er.get("route_hint_non_authoritative") or "").strip()
rk = (er.get("rrc_kind") or "").strip()
if rh and rh != "unclassified_equation":
tokens.append(rh)
if rk:
tokens.append(rk)
eq_text = (er.get("equation") or "").lower()
for op in ["exp(", "log(", "max(", "min(", "sum(", "integral", "derivative",
"laplacian", "nabla", "div(", "curl(", "sigmoid", "softmax",
"tanh(", "relu(", "norm(", "dot(", "cross("]:
if op in eq_text:
tokens.append(op.rstrip("("))
return list(dict.fromkeys(tokens))
def lean_str(s: str) -> str:
s = s.replace("\\", "\\\\").replace('"', '\\"')
return f'"{s}"'
def lean_opt(s: str | None) -> str:
return "none" if s is None else f"some {lean_str(s)}"
def lean_q16_16(val: float) -> str:
"""Convert a float in [0,1] to a Q16_16 Lean literal via exact rational."""
if val == 0.0:
return "Q16_16.zero"
from fractions import Fraction
f = Fraction(val).limit_denominator(100)
return f"Q16_16.ofRatio {f.numerator} {f.denominator}"
def lean_str_list(xs: list[str]) -> str:
return "[" + ", ".join(lean_str(x) for x in xs) + "]"
def load_matrices(path: Path) -> dict[str, list[list[int]]]:
"""Load predictions JSON into equation_id → matrix lookup."""
if not path.exists():
return {}
data = json.loads(path.read_text())
return {
p.get("equation_id", ""): p.get("matrix_8x8", [])
for p in data.get("predictions", [])
if p.get("equation_id")
}
def main() -> int:
parser = argparse.ArgumentParser(description="Generate SilverSight RRC Q16_16Manifold.lean")
parser.add_argument(
"--receipt",
type=Path,
default=Path("/home/allaun/Research Stack/archive/experimental-shim-probes/rrc_equation_classifier_receipt.json"),
help="Path to rrc_equation_classifier_receipt.json",
)
parser.add_argument(
"--predictions",
type=Path,
default=Path("/home/allaun/Research Stack/shared-data/rrc_pist_predictions_250_v1.json"),
help="Path to rrc_pist_predictions_250_v1.json",
)
parser.add_argument(
"--out-lean",
type=Path,
default=Path("formal/SilverSight/RRC/Q16_16Manifold.lean"),
help="Output Lean module path",
)
args = parser.parse_args()
receipt = json.loads(args.receipt.read_text())
eqs = receipt.get("compiled_equations", [])
matrices = load_matrices(args.predictions)
print(f"Loaded {len(eqs)} equations and {len(matrices)} matrices", file=sys.stderr)
# Deterministic order by equation_id.
eqs_sorted = sorted(eqs, key=lambda eq: eq.get("invariant_receipt", {}).get("object_id", ""))
# Content hash over the raw corpus data for reproducibility.
content_blob = json.dumps(
[
{
"object_id": eq.get("invariant_receipt", {}).get("object_id"),
"name": eq.get("equation_record", {}).get("name"),
"shape": eq.get("invariant_receipt", {}).get("shape"),
"status": eq.get("invariant_receipt", {}).get("status"),
"matrix": matrices.get(eq.get("invariant_receipt", {}).get("object_id", "")),
}
for eq in eqs_sorted
],
sort_keys=True,
separators=(",", ":"),
).encode("utf-8")
content_hash = hashlib.sha256(content_blob).hexdigest()
rows: list[str] = []
for eq in eqs_sorted:
er = eq["equation_record"]
ir = eq["invariant_receipt"]
tw = eq["type_witness"]
eq_id = ir.get("object_id", "")
name = er.get("name", "")
shape_str = ir.get("shape", "HoldForUnlawfulOrUnderspecifiedShape")
lean_shape = SHAPE_MAP.get(shape_str, ".holdForUnlawfulOrUnderspecifiedShape")
status_str = ir.get("status", "HOLD")
lean_status = ".candidate" if status_str == "CANDIDATE" else ".hold"
rrc_kind = er.get("rrc_kind", "")
weak_cnt = len(tw.get("missing_or_weak_axes") or [])
# Manifold coordinates for negative control witness (Q16_16)
coords = eq.get("manifold_projection", {}).get("coordinates", {})
nc_strength = coords.get("negative_control_strength", 0.0)
residual_risk = coords.get("residual_risk", 0.0)
scale_band = coords.get("scale_band_declared", 0.0)
weak_axes = tw.get("missing_or_weak_axes") or []
op_tokens = operator_tokens(er)
inv_declared = (er.get("domain_type") or "unknown").strip() or "unknown"
bound_conds = (er.get("bind_class") or "unknown").strip() or "unknown"
t_key = template_key(rrc_kind, status_str)
route_hint = er.get("route_hint_non_authoritative") or "unclassified_equation"
t_params = f"route={route_hint};shape={shape_str}"
arxiv_pid = (er.get("arxiv_paper_id") or "").strip() or None
rows.append(
f" {{ equationId := {lean_str(eq_id)}\n"
f" name := {lean_str(name)}\n"
f" shape := {lean_shape}\n"
f" status := {lean_status}\n"
f" rrcKind := {lean_str(rrc_kind)}\n"
f" weakAxesCnt := {weak_cnt}\n"
f" pistProxyLabel := Option.bind (findMatrix {lean_str(eq_id)}) (SilverSight.PIST.ClassifyN.classifyProxy SilverSight.PIST.ClassifyN.hashTable8)\n"
f" pistExactLabel := Option.bind (findMatrix {lean_str(eq_id)}) (SilverSight.PIST.ClassifyN.classifyExact 8)\n"
f" arxivPaperId := {lean_opt(arxiv_pid)}\n"
f" ncObserved := {lean_q16_16(nc_strength)}\n"
f" residualRisk := {lean_q16_16(residual_risk)}\n"
f" scaleBandDeclared := {lean_q16_16(scale_band)}\n"
f" weakAxesNames := {lean_str_list(weak_axes)}\n"
f" operatorTokens := {lean_str_list(op_tokens)}\n"
f" invariantsDeclared := {lean_str(inv_declared)}\n"
f" boundaryConds := {lean_str(bound_conds)}\n"
f" templateKey := {lean_str(t_key)}\n"
f" templateParams := {lean_str(t_params)} }}"
)
lines = [
"-- SilverSight.RRC.Q16_16Manifold — AUTO-GENERATED by python/build_manifold.py",
"-- DO NOT EDIT BY HAND. Regenerate with:",
"-- python3 python/build_manifold.py",
"--",
"-- Python role: raw feature extraction + matrix merge.",
"-- Lean role: PIST classification, alignment gate (determineAlignment),",
"-- receipt stamping, and all admissibility/promotion decisions.",
"--",
"-- Source: rrc_equation_classifier_receipt.json",
"-- Matrices: rrc_pist_predictions_250_v1.json",
f"-- Content hash (SHA-256): {content_hash}",
f"-- Equation count: {len(rows)}",
"--",
"import SilverSight.RRC.Emit",
"import SilverSight.FixedPoint",
"import SilverSight.PIST.Classify",
"import SilverSight.PIST.ClassifyN",
"import SilverSight.PIST.Matrices250",
"",
"namespace SilverSight.RRC.Q16_16Manifold",
"",
"open SilverSight.RRC.Emit",
"open SilverSight.FixedPoint",
"open SilverSight.RRCLogogramProjection",
"open SilverSight.ReceiptCore",
"open SilverSight.PIST.Matrices250",
"",
"/-- Full 250-equation manifold from rrc_equation_classifier_receipt.json,",
" merged with 8×8 braid adjacency matrices from",
" rrc_pist_predictions_250_v1.json.",
" Each row carries raw features only; the alignment gate in",
" SilverSight.RRC.Emit.emitCorpus makes all admissibility decisions. -/",
"def allFixtures : List FixtureRow := [",
",\n".join(rows),
"]",
"",
"end SilverSight.RRC.Q16_16Manifold",
"",
]
args.out_lean.parent.mkdir(parents=True, exist_ok=True)
args.out_lean.write_text("\n".join(lines))
print(f"Wrote {args.out_lean} ({len(rows)} rows)", file=sys.stderr)
return 0
if __name__ == "__main__":
sys.exit(main())

6
python/build_pist_matrices_250.py
View file

@ -96,10 +96,12 @@ def main() -> int:
"", "",
"namespace SilverSight.PIST.Matrices250", "namespace SilverSight.PIST.Matrices250",
"", "",
"/-- 8×8 braid adjacency matrices keyed by invariant equation_id, stored as", "/-- All matrices in this list have dimension 8×8 (the canonical strand count).",
" an association list (key → matrix). Generated from", " Stored as association list (key → matrix). Generated from",
" rrc_pist_predictions_250_v1.json.", " rrc_pist_predictions_250_v1.json.",
f" Entries: {len(entries)}. -/", f" Entries: {len(entries)}. -/",
f"def pistMatrixDim : Nat := 8",
"",
"def pistMatrices250 : List (String × Array (Array Int)) :=", "def pistMatrices250 : List (String × Array (Array Int)) :=",
" [", " [",
",\n".join(entries), ",\n".join(entries),

96
scripts/cross_domain_significance.py Normal file
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@ -0,0 +1,96 @@
#!/usr/bin/env python3
"""
cross_domain_significance.py — Statistical significance test for
RRC cross-domain 1/n residual signatures.
Tests whether observed deviations from predicted 1/n scaling or
1/7 meta-solid threshold are statistically significant at ≥6σ.
"""
import json, math
from pathlib import Path
from datetime import datetime, timezone
ROOT = Path(__file__).resolve().parents[1]
def gaussian_p_value(z: float) -> float:
"""Two-tailed p-value from z-score via complementary error function."""
return math.erfc(abs(z) / math.sqrt(2))
def sigma_from_p(p: float) -> float:
"""Convert p-value to sigma level (two-tailed) via inverse erfc approximation."""
if p <= 0:
return float('inf')
if p >= 1:
return 0.0
t = math.sqrt(-2 * math.log(p if p <= 0.5 else 1 - p))
c = (2.515517, 0.802853, 0.010328)
d = (1.432788, 0.189269, 0.001308)
return t - (c[0] + c[1]*t + c[2]*t**2) / (1 + d[0]*t + d[1]*t**2 + d[2]*t**3)
def main():
sig_path = ROOT / "signatures" / "cross_domain_signatures.json"
sigs = json.loads(sig_path.read_text())
entries = sigs["signatures"]
phases = {}
for e in entries:
phases.setdefault(e.get("phase", 0), []).append(e)
results = []
for phase_num in sorted(phases):
group = phases[phase_num]
domain = group[0].get("domain", "Unknown")
deviations = [abs(e["deviation"]) for e in group if "deviation" in e]
residuals = [e["residual_mhz"] for e in group if "residual_mhz" in e]
values = deviations or residuals
n = len(values)
if n < 2:
results.append({
"phase": phase_num, "domain": domain,
"n": n, "status": "insufficient_data"
})
continue
mean_val = sum(values) / n
var = sum((v - mean_val)**2 for v in values) / (n - 1) if n > 1 else 0
se = math.sqrt(var / n)
z = mean_val / se if se > 0 else 0.0
p = gaussian_p_value(z)
sigma = sigma_from_p(p)
results.append({
"phase": phase_num,
"domain": domain,
"n": n,
"mean_deviation": round(mean_val, 6),
"std_err": round(se, 6),
"z_score": round(z, 4),
"sigma_level": round(sigma, 2) if sigma < 1e6 else "inf",
"passes_6sigma": bool(sigma >= 6.0),
})
summary = {
"schema": "cross_domain_significance_v1",
"generated_at": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"),
"source": "cross_domain_signatures.json",
"total_entries": len(entries),
"phases": results,
}
out_path = ROOT / "signatures" / "cross_domain_significance.json"
out_path.write_text(json.dumps(summary, indent=2) + "\n")
print(f"Wrote {out_path}")
for r in results:
s = r.get("sigma_level")
if s is not None and s != "inf":
tag = "✅" if r["passes_6sigma"] else "❌"
print(f" Phase {r['phase']} ({r['domain']}): σ={s} {tag}")
else:
tag = "✅" if r.get("status") == "insufficient_data" else "❌"
print(f" Phase {r['phase']} ({r['domain']}): σ={s} {tag}")
if __name__ == "__main__":
main()

80
scripts/setup_authentik.sh Normal file
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@ -0,0 +1,80 @@
#!/bin/bash
# setup_authentik.sh — Deploy Authentik + Caddy on neon-64gb
# Uses existing Postgres (arxiv-pg) and Redis on neon.
#
# Run from any node with SSH access to neon:
# bash scripts/setup_authentik.sh
#
# Authentik listens on:
# HTTP → port 30001 (Caddy at auth.neon.lan proxies to this)
# HTTPS → port 30100 (reserved for future direct TLS)
set -euo pipefail
NEON="allaun@100.92.88.64"
echo "=== Step 1: Create authentik database ==="
ssh "$NEON" "
psql -h localhost -U postgres -tc \"SELECT 1 FROM pg_database WHERE datname='authentik'\" | grep -q 1 || \
psql -h localhost -U postgres -c 'CREATE DATABASE authentik'
"
echo "=== Step 2: Generate shared secret key ==="
AUTH_KEY=$(python3 -c "import secrets; print(secrets.token_hex(32))")
echo "=== Step 3: Pull image ==="
ssh "$NEON" "podman pull ghcr.io/goauthentik/server:latest"
echo "=== Step 4: Remove old containers ==="
ssh "$NEON" "podman rm -f authentik-server authentik-worker 2>/dev/null || true"
echo "=== Step 5: Start server (port 30001) ==="
ssh "$NEON" "
podman run -d --name authentik-server \
--network host \
-e AUTHENTIK_SECRET_KEY='$AUTH_KEY' \
-e AUTHENTIK_POSTGRESQL__NAME=authentik \
-e AUTHENTIK_POSTGRESQL__USER=postgres \
-e AUTHENTIK_POSTGRESQL__HOST=localhost \
-e AUTHENTIK_POSTGRESQL__PORT=5432 \
-e AUTHENTIK_POSTGRESQL__PASSWORD=postgres \
-e AUTHENTIK_REDIS__HOST=localhost \
-e AUTHENTIK_REDIS__PORT=6379 \
-e AUTHENTIK_LISTEN__HTTP=0.0.0.0:30001 \
ghcr.io/goauthentik/server:latest server
"
echo "=== Step 6: Start worker ==="
ssh "$NEON" "
podman run -d --name authentik-worker \
--network host \
-e AUTHENTIK_SECRET_KEY='$AUTH_KEY' \
-e AUTHENTIK_POSTGRESQL__NAME=authentik \
-e AUTHENTIK_POSTGRESQL__USER=postgres \
-e AUTHENTIK_POSTGRESQL__HOST=localhost \
-e AUTHENTIK_POSTGRESQL__PORT=5432 \
-e AUTHENTIK_POSTGRESQL__PASSWORD=postgres \
-e AUTHENTIK_REDIS__HOST=localhost \
-e AUTHENTIK_REDIS__PORT=6379 \
ghcr.io/goauthentik/server:latest worker
"
echo "=== Step 7: Wait for migrations ==="
sleep 10
echo "=== Status ==="
ssh "$NEON" "
podman ps --filter name=auth --format '{{.Names}} {{.Status}}'
curl -s -o /dev/null -w 'HTTP port 30001: %{http_code}\n' http://localhost:30001/
"
echo "=== Done ==="
echo " Authentik: http://localhost:30001 (neon) or http://auth.neon.lan via Caddy"
echo " Setup wizard at first visit creates the admin account."
echo ""
echo " To route via Caddy (if desired):"
echo " ssh $NEON 'cat > ~/caddy/Caddyfile << EOF"
echo " auth.neon.lan {"
echo " reverse_proxy localhost:30001"
echo " }"
echo " EOF""
echo " ssh $NEON 'podman restart caddy'"

54
signatures/cross_domain_significance.json Normal file
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@ -0,0 +1,54 @@
{
"schema": "cross_domain_significance_v1",
"generated_at": "2026-06-30T07:48:42Z",
"source": "cross_domain_signatures.json",
"total_entries": 16,
"phases": [
{
"phase": 1,
"domain": "Rydberg",
"n": 3,
"mean_deviation": 123.266667,
"std_err": 37.656621,
"z_score": 3.2734,
"sigma_level": 3.07,
"passes_6sigma": false
},
{
"phase": 2,
"domain": "Superconductor",
"n": 3,
"mean_deviation": 0.006286,
"std_err": 0.002245,
"z_score": 2.7997,
"sigma_level": 2.57,
"passes_6sigma": false
},
{
"phase": 3,
"domain": "EnergyStorage",
"n": 3,
"mean_deviation": 0.077504,
"std_err": 0.023425,
"z_score": 3.3085,
"sigma_level": 3.11,
"passes_6sigma": false
},
{
"phase": 4,
"domain": "Electromagnetic",
"n": 3,
"mean_deviation": 0.003333,
"std_err": 0.003333,
"z_score": 1.0,
"sigma_level": 0.47,
"passes_6sigma": false
},
{
"phase": 5,
"domain": "Rydberg",
"n": 0,
"status": "insufficient_data"
}
]
}

103
tests/test_python_modules.py Normal file
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@ -0,0 +1,103 @@
"""test_python_modules.py — Sanity checks for Python shim modules.
Tests that each module can be imported and key functions run without error.
For deterministic modules, checks that output matches expected values.
"""
from __future__ import annotations
import sys
import unittest
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "python"))
sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "qubo"))
class TestPistBraidBridge(unittest.TestCase):
"""pist_braid_bridge: PIST trace → braid strand mapping."""
def test_import(self):
import pist_braid_bridge
self.assertTrue(hasattr(pist_braid_bridge, "float_to_q16"))
self.assertTrue(hasattr(pist_braid_bridge, "q16_to_float"))
class TestSidonAddress(unittest.TestCase):
"""sidon_address: Sidon label propagation."""
def test_import(self):
import sidon_address
self.assertTrue(hasattr(sidon_address, "verify_sidon_property"))
self.assertTrue(hasattr(sidon_address, "spectral_to_sidon_address"))
class TestSpectralProfile(unittest.TestCase):
"""spectral_profile: spectral feature extraction."""
def test_import(self):
import spectral_profile
self.assertTrue(hasattr(spectral_profile, "compute_spectral_profile"))
class TestBuildManifold(unittest.TestCase):
"""build_manifold: manifold generation pipeline."""
def test_lean_q16_16(self):
from build_manifold import lean_q16_16
self.assertEqual(lean_q16_16(0.0), "Q16_16.zero")
self.assertEqual(lean_q16_16(0.5), "Q16_16.ofRatio 1 2")
self.assertEqual(lean_q16_16(0.25), "Q16_16.ofRatio 1 4")
class TestQ16Canonical(unittest.TestCase):
"""q16_canonical: Q16_16 encoding/decoding."""
def test_import(self):
import q16_canonical
self.assertTrue(hasattr(q16_canonical, "float_to_q16"))
self.assertTrue(hasattr(q16_canonical, "q16_to_float"))
class TestDnaCodec(unittest.TestCase):
"""dna_codec: DNA ↔ binary codec."""
def test_import(self):
import dna_codec
self.assertTrue(hasattr(dna_codec, "melting_temperature"))
class TestExprTree(unittest.TestCase):
"""expr_tree: expression tree parsing."""
def test_import(self):
import expr_tree
self.assertTrue(hasattr(expr_tree, "ExprNode"))
class TestBuildPistMatrices(unittest.TestCase):
"""build_pist_matrices_250: PIST matrix generation."""
def test_import(self):
import build_pist_matrices_250
self.assertTrue(hasattr(build_pist_matrices_250, "lean_str"))
class TestDnaQuboSort(unittest.TestCase):
"""dna_qubo_sort: QUBO-based DNA sorting."""
def test_import(self):
import dna_qubo_sort
self.assertTrue(hasattr(dna_qubo_sort, "QuboDnaCandidate"))
class TestChaosGame(unittest.TestCase):
"""chaos_game: chaos game IFS engine."""
def test_import(self):
import chaos_game
self.assertTrue(hasattr(chaos_game, "LCG"))
if __name__ == "__main__":
unittest.main()