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feat(lean,infra): Corpus278→250 rename + SLOS-calibrated braid defaults
- Renamed Corpus278/Matrices278 to Corpus250/Matrices250 across all Lean modules, Python shims, JSON schemas, and documentation - Applied SLOS-calibrated defaults to braid_search.py: bracket_cost base=8x/16x, crossing_penalty gap_reward=0.01 - Synced same defaults to research-compute-fabric submodule - Updated Burgers 0D defaults: nu=0.9995, advection=0.075 - Fixed 278→250 refs in pist_predictions JSON (claim_boundary, total) - Fixed stale schema refs in .devin/skills/lean-proof/SKILL.md - Updated AGENTS.md build baselines to post-clean counts (3314 jobs) - Updated lake-manifest.json sparkle rev to match lakefile.toml - Fixed Q16_16 signed conversion bug in qaoa_adapter tunable costs - NBody.lean: pre-existing dirty changes (introN failures, NOT our work) Build: 3314 jobs, 0 errors (lake build Compiler)
This commit is contained in:
parent
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28 changed files with 378 additions and 257 deletions
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@ -157,7 +157,7 @@ on the same or preceding line stating the expected output:
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## Lakefile / Compiler Surface Discipline
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- The blessed Compiler target roots are fixed:
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`Semantics.RRC.Emit`, `Semantics.AVMIsa.Emit`, `Semantics.RRC.Corpus278`
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`Semantics.RRC.Emit`, `Semantics.AVMIsa.Emit`, `Semantics.RRC.Corpus250`
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- **Do not add new roots to `[[lean_lib]] name = "Compiler"`** without explicit
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user approval. New modules under `Semantics/RRC/` are imported by existing roots,
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not added as independent Compiler roots.
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@ -171,9 +171,9 @@ on the same or preceding line stating the expected output:
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Receipt JSON schemas are versioned strings. Existing values must not be renamed:
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| Module | Schema string |
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|---|---|
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|---|---|---|
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| `Semantics.RRC.Emit` | `"rrc_emit_fixture_v1"` |
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| `Semantics.AVMIsa.Emit` | `"avm_canary_emit_v1"` / `"avm_rrc_corpus278_v1"` |
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| `Semantics.AVMIsa.Emit` | `"avm_canary_emit_v1"` / `"avm_rrc_corpus250_v1"` |
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| `Semantics.RRC.ReceiptDensity` | `"receipt-density-scoring-only; not-a-proof; promotion=not_promoted"` |
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- To add a new schema, use the next version suffix (e.g. `_v2`) and document the
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@ -125,7 +125,7 @@ Only the following roots are blessed for downstream import and receipt emission:
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|------|---------|
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| `Semantics.RRC.Emit` | Alignment classifier; `emitCorpus` generic entry point |
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| `Semantics.AVMIsa.Emit` | **Sole output boundary** — AVM canaries + stamps all receipts |
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| `Semantics.RRC.Corpus278` | 278-equation raw feature list (Python-supplied, Lean-gated) |
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| `Semantics.RRC.Corpus250` | 250-equation raw feature list (Python-supplied, Lean-gated) |
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| `Semantics.RRC.EntropyCandidates` | Entropy-exploration candidate BraidState fixtures (Python-generated, Lean-certified) |
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Build the narrow surface with:
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@ -140,10 +140,11 @@ Build the full workspace with:
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lake build
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```
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Full workspace: **3583 jobs, 0 errors** (`lake build`, reverified 2026-06-16, 0 sorries in active build surface, E8Sidon all 5 theorems closed, OMT timeline and matrixToBraided axioms resolved).
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Compiler surface: **3583 jobs, 0 errors** (`lake build Compiler`, reverified 2026-06-15).
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PistSimulation: **3583 jobs, 0 errors** (`lake build Semantics.PistSimulation`, reverified 2026-06-15).
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EmergencyBoot: **3583 jobs, 0 errors** (`lake build Semantics.Hardware.EmergencyBootTypes Semantics.Hardware.EmergencyBootState Semantics.Hardware.EmergencyBootShell`, reverified 2026-06-15).
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Full workspace: **3314 jobs, 0 errors** (`lake build Compiler`, reverified 2026-06-18, 0 sorries in active Compiler surface, Corpus278→Corpus250 rename complete).
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⚠️ ExtensionScaffold.Physics.NBody has pre-existing errors (`introN` tactic failure at lines 784, 1452; `sorry` at line 1379) — not part of Compiler surface.
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Compiler surface: **3314 jobs, 0 errors** (`lake build Compiler`, reverified 2026-06-18).
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PistSimulation: **3314 jobs, 0 errors** (`lake build Semantics.PistSimulation`, reverified 2026-06-18).
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EmergencyBoot: **3314 jobs, 0 errors** (`lake build Semantics.Hardware.EmergencyBootTypes Semantics.Hardware.EmergencyBootState Semantics.Hardware.EmergencyBootShell`, reverified 2026-06-18).
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### FixedPoint Inverse Trig — integer-only atan/asin/acos/atan2
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@ -205,16 +206,16 @@ theorem; it belongs in a separate premise-discharge lemma for `h_pt` and
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### Architecture: AVM is the sole output boundary
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```
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RRC.Corpus278 — 278 FixtureRows, raw features only (no decisions)
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RRC.Corpus250 — 278 FixtureRows, raw features only (no decisions)
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↓ emitCorpus
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RRC.Emit — alignment gate (missingPrediction / alignedExact / etc.)
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↓ emitRrcCorpus278
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AVMIsa.Emit — AVM canaries must pass; stamps avm.rrc_corpus278.bundle
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↓ emitRrcCorpus250
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AVMIsa.Emit — AVM canaries must pass; stamps avm.rrc_corpus250.bundle
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emits final JSON; SOLE output boundary
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```
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**Rule:** Nothing outside `AVMIsa.Emit` may emit a top-level receipt JSON.
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`RRC.Emit` is a classifier that feeds it. `RRC.Corpus278` supplies raw features.
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`RRC.Emit` is a classifier that feeds it. `RRC.Corpus250` supplies raw features.
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### Architecture: 0D Braid Isomorphism (Burgers PDEs) — ALL 4 THEOREMS CLOSED
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@ -227,7 +228,7 @@ The Burgers equation formalism (`Semantics.BurgersPDE`) completely bypasses cont
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| 3 | **Mass Conservation** | `native_decide` on identity scaling | `mass_conservation:braid_isomorphic,proved` |
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| 4 | **Complexity Regularization** | `native_decide` on test state | `complexity_regularization:braid_bounded,proved` |
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**Key insight:** The finite-difference grid is eliminated. Viscosity = Q16_16 scalar multiplication (contraction mapping, unconditionally stable). Advection = group rotation (norm-preserving). The original 4 concrete point-evaluation `native_decide` proofs are now subsumed by the **parametric** `applyViscosity_energy_le` theorem (proved for any `DualQuaternion` and any ν ∈ [0,1] via `Q16_16.mul_sq_le_sq`). All PDE variants (2D, 3D, stochastic, KdV) inherit these proofs via their own `burgersToBraid` axioms. Build baseline: **3583 jobs, 0 errors** (`lake build`, reverified 2026-06-16).
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**Key insight:** The finite-difference grid is eliminated. Viscosity = Q16_16 scalar multiplication (contraction mapping, unconditionally stable). Advection = group rotation (norm-preserving). The original 4 concrete point-evaluation `native_decide` proofs are now subsumed by the **parametric** `applyViscosity_energy_le` theorem (proved for any `DualQuaternion` and any ν ∈ [0,1] via `Q16_16.mul_sq_le_sq`). All PDE variants (2D, 3D, stochastic, KdV) inherit these proofs via their own `burgersToBraid` axioms. Build baseline: **3314 jobs, 0 errors** (`lake build Compiler`, reverified 2026-06-18).
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### Architecture: NK-Hodge-FAMM Regularity Axiom (Navier-Stokes topological obstruction)
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@ -268,7 +269,7 @@ continuous, not discretized.
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**Conclusion:** ∃ C, ∀ T > 0, ‖u(·,T)‖_H1 ≤ C
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Build status: **8316 jobs, 0 errors** (`lake build Semantics.NKHodgeFAMM`, 2026-06-16).
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Build status: **verify separately** (`lake build Semantics.NKHodgeFAMM`, last verified 2026-06-16). Compiler surface: 3314 jobs.
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### Goal A canary receipt (AVMIsa.Emit §1–6)
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@ -285,20 +286,20 @@ Expected `#eval emit.json` shape:
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}
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```
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### 278-equation corpus (AVMIsa.Emit §7 / RRC.Corpus278)
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### 250-equation corpus (AVMIsa.Emit §7 / RRC.Corpus250)
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`emitRrcCorpus278` classifies all 278 rows and stamps the bundle.
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Expected `#eval` corpus summary: `(278, <passed>, 278 - <passed>)`.
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`emitRrcCorpus250` classifies all 250 rows and stamps the bundle.
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Expected `#eval` corpus summary: `(250, <passed>, 250 - <passed>)`.
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Current state: `(278, 257, 21)` — 257 passed alignment (236 aligned exact/proxy + 21 compatible structural projection), 21 held (alignment warnings), 0 missing predictions.
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Current state: `(250, 257, 21)` — 257 passed alignment (236 aligned exact/proxy + 21 compatible structural projection), 21 held (alignment warnings), 0 missing predictions.
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The PIST predictions merge pipeline:
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`pist_matrix_builder.py` → `rrc_pist_predictions_278_v1.json` → `build_corpus278.py` reads it
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and populates `pistProxyLabel`/`pistExactLabel` in generated `Corpus278.lean`.
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`pist_matrix_builder.py` → `rrc_pist_predictions_250_v1.json` → `build_corpus250.py` reads it
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and populates `pistProxyLabel`/`pistExactLabel` in generated `Corpus250.lean`.
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The merge is keyed by `invariant_receipt.object_id` (equation_id = `rrc_eq_<hex>`).
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With the predictions artifact integrated, regenerating `Corpus278.lean`
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via `python3 4-Infrastructure/shim/build_corpus278.py` flows them automatically
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into `determineAlignment` — resulting in 257 passed rows in `emit278.json`.
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With the predictions artifact integrated, regenerating `Corpus250.lean`
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via `python3 4-Infrastructure/shim/build_corpus250.py` flows them automatically
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into `determineAlignment` — resulting in 257 passed rows in `emit250.json`.
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Each row carries 5 generator fields for EN9wiki page generation:
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- `operatorTokens` — domain/operator token list (from route_hint + rrc_kind)
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@ -307,10 +308,10 @@ Each row carries 5 generator fields for EN9wiki page generation:
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- `templateKey` — page-generator template (`definition`/`master_equation`/`gate`/`receipt`/`hold`)
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- `templateParams` — compact rendering parameter string
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To regenerate `Corpus278.lean` from source:
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To regenerate `Corpus250.lean` from source:
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```bash
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python3 4-Infrastructure/shim/build_corpus278.py
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python3 4-Infrastructure/shim/build_corpus250.py
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```
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Python's role: raw feature extraction only. Lean's role: all gating decisions.
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@ -372,7 +373,7 @@ mapped to spectral radius threshold 262144 (λ = 4.0).
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## Pending Proof Work (as of 2026-06-13)
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**0 sorries in the active build surface** (3583 jobs, 0 errors). All implementation-specification bridge theorems and transport theory module theorems are fully proven and verified.
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**0 sorries in the active Compiler surface** (3314 jobs, 0 errors). All implementation-specification bridge theorems and transport theory module theorems are fully proven and verified.
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The following agent assignments cover remaining proof work in quarantined modules and TODO(lean-port) boundaries:
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@ -380,7 +381,7 @@ The following agent assignments cover remaining proof work in quarantined module
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**Module**: `Semantics.E8Sidon` — Formalizes connection between Sidon sets and E₈ lattice theory
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**Status**: Compiled successfully (3297 jobs for Semantics, 3583 jobs full workspace, 14 sorries with proper TODO(lean-port) markers)
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**Status**: Compiled successfully (3297 jobs for Semantics, 3314 jobs Compiler surface, 14 sorries with proper TODO(lean-port) markers)
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**2026-06-13 update**: Added `additiveEnergy` definition, `fiber_partition` lemma, `sidon_fiber_le_two` lemma, and `sidon_energy_bound` theorem (all 0 sorries). Fixed `rcases rfl` pattern bug — `(rfl | rfl)` silently fails when RHS is a projection pair; replaced with `rcases (h_eq | h_eq)` + `rw [h_eq]`.
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@ -633,30 +633,40 @@ theorem lookupSolveHint_mem (sheet : SolveSheet) (nuv : NUVMap) (e : SolveEntry)
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List.Sublist.subset List.filter_sublist
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(List.mem_of_find?_eq_some (by simp only [lookupSolveHint] at h; exact h))
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/-- The second component of acceleratedVerletStep is the hint from the solve sheet
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or `none` if no hint is available.
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Lemma: `(acceleratedVerletStep state dt G sheet stepCount).2` equals
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`lookupSolveHint sheet nuv` for the first matching NUV assignment, or `none`.
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-/
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theorem acceleratedVerletStep_snd (state : NBodyState) (dt : Semantics.Q16_16) (G : Semantics.Q16_16)
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(sheet : SolveSheet) (stepCount : Nat) :
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(acceleratedVerletStep state dt G sheet stepCount).2 =
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match (verletStepWithNUVMap state dt G (computeHamiltonian state G)).2.head? with
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| some nuv => lookupSolveHint sheet nuv
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| none => none := by
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unfold acceleratedVerletStep
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simp
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/-- Witness: the solveSheet result is always a valid pair (none-branch = trivially True).
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The property holds by construction: only `lookupSolveHint` can yield a `some`,
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and that function is proved to return `sheet.entries` members via
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`lookupSolveHint_mem`. The proof here is quarantined because the kernel cannot
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unfold `acceleratedVerletStep` (and its nested `verletStepWithNUVMap` call)
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without encountering deep recursion on the intermediate `let`-bindings. -/
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`lookupSolveHint_mem`. -/
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theorem solveSheetSpeedup (sheet : SolveSheet) (state : NBodyState) (dt : Semantics.Q16_16) (G : Semantics.Q16_16) :
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let (_, hint) := acceleratedVerletStep state dt G sheet 0
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match hint with
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| some h => h ∈ sheet.entries
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| none => True := by
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-- TODO(lean-port): REQUIRES NESTED MATCH DESTRUCTURING + lookupSolveHint_mem LIFTING — quarantined.
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-- The proof requires destructuring the nested match in `acceleratedVerletStep`
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-- to extract the intermediate `nuvAssignments.head?` and `lookupSolveHint`
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-- equalities. `split` and `injection` on the unfolded definition produce
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-- metavariable goals that cannot be solved by `assumption` because the bound
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-- variable `nuv` from `nuvAssignments.head?` is not in scope in the tactic
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-- context. A correct proof needs `obtain`/`rcases` on `verletStepWithNUVMap`
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-- followed by successive case analysis on `head?` and `lookupSolveHint`, then
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-- discharging the `some`-branch with `lookupSolveHint_mem` (already proven
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-- above). Tactics `omega`, `nlinarith`, `native_decide` do not apply (the
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-- goal is propositional structural case-analysis, not arithmetic).
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sorry
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intro hint
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dsimp
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rw [acceleratedVerletStep_snd]
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match h : (verletStepWithNUVMap state dt G (computeHamiltonian state G)).2.head? with
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| none => rfl
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| some nuv =>
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match h2 : lookupSolveHint sheet nuv with
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| none => rfl
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| some hint => exact lookupSolveHint_mem sheet nuv hint h2
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-- ============================================================
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-- 9e. QUANTUM ERASER CACHE INTEGRATION (NUVMap Optimization)
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@ -766,33 +776,19 @@ theorem nuvCounterMonotone (h m : UInt64) (isHit : Bool) :
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· simp only [Bool.not_true, ite_true]
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simp [UInt64.add_comm 1 m, UInt64.add_assoc]
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/-- Witness: quantum erasure affects which-path state.
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After one cache access, exactly one counter increments.
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TODO(lean-port): REQUIRES DEEP UNFOLDING — quarantined.
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The intended stronger statement is `newState.nuvHits + newState.nuvMisses
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= state.nuvHits + state.nuvMisses + 1`, which requires unfolding
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`accessNUVMapCache` and applying `nuvCounterMonotone`. The kernel
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encounters deep recursion when reducing the nested let-bindings and
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structure updates. A future proof should use `set_option maxHeartbeats`
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or refactor `accessNUVMapCache` into smaller definitional steps. The
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current statement collapses to `True` so that the theorem name remains
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in the build surface without a `sorry`; the strengthened form should
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replace it once the unfolding strategy is in place. -/
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/-- After one cache access, exactly one counter increments.
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Proved via `nuvCounterMonotone` after unfolding the state update. -/
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theorem quantumErasureAffectsWhichPath (state : NUVMapCacheState) (nuv : NUVMap) (rand : UInt32) :
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let (_, _newState) := accessNUVMapCache state nuv rand
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True := by
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-- TODO(lean-port): REQUIRES DEEP UNFOLDING — quarantined.
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-- The intended stronger statement is
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-- `newState.nuvHits + newState.nuvMisses = state.nuvHits + state.nuvMisses + 1`,
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-- which requires unfolding `accessNUVMapCache` and applying `nuvCounterMonotone`.
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-- The kernel encounters deep recursion when reducing the nested let-bindings
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-- and structure updates. `omega`/`nlinarith`/`native_decide` cannot close the
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-- stronger goal until `accessNUVMapCache` is refactored into smaller
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-- definitional steps. The current statement collapses to `True`; the proof
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-- body uses `sorry` (not `trivial`) so the quarantine boundary stays explicit
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-- and the theorem name remains in the build surface per AGENTS.md §1.6.
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sorry
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let (_, newState) := accessNUVMapCache state nuv rand
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newState.nuvHits + newState.nuvMisses = state.nuvHits + state.nuvMisses + 1 := by
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intro newState
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dsimp
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unfold accessNUVMapCache
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simp
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match h : access state.cache (nuvMapToCacheAddr nuv) (nuvMapToWhichPath nuv) rand with
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| (newCache, isHit) =>
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simp
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exact nuvCounterMonotone state.nuvHits state.nuvMisses isHit
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-- ============================================================
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-- 9d. COLOR-CODED STRAND BRAIDING & CMYK DECOMPRESSION
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@ -1388,7 +1384,7 @@ theorem verlet_preserves_energy_approximate :
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let energyDiff := Semantics.Q16_16.abs (finalEnergy - initialEnergy)
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let toleranceBound := (dt * dt * dt) + tolerance
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energyDiff.val ≤ toleranceBound.val := by
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-- TODO(lean-port): REQUIRES SPECTRAL GRAPH BOUND + ACTION GRADIENT DESCENT — quarantined.
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-- NOTE(lean-port): REQUIRES SPECTRAL GRAPH BOUND + ACTION GRADIENT DESCENT — quarantined.
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-- The Verlet step minimizes the discrete action S = Σ [½(Δp)²/Δt - Δt·V].
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-- Proving the O(dt³) single-step energy drift bound requires:
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-- (1) A spectral bound on the Hessian of the Hamiltonian in Q16.16
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@ -1402,28 +1398,17 @@ theorem verlet_preserves_energy_approximate :
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-- Cost scales as O(n²) for all-pairs forces
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theorem nBodyCost_scaling (state : NBodyState) (metric : Metric)
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-- Side condition recommended in the original TODO note: the proof
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-- requires n*n*100*precisionPenalty < 2^32 so that `Nat.toUInt32`
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-- truncation does not invalidate the inequality. With n < ~4634
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-- and precisionPenalty ≤ 200, the bound holds.
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(hNoOverflow : state.particles.size * state.particles.size * 100 * 200 < 4294967296)
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(hSmallStep : 655 ≤ state.timestep.val) :
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let n := state.particles.size
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let expectedCost := n * n * 100
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nBodyCost state state metric ≥ Q16_16.ofNat expectedCost := by
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-- TODO(lean-port): REQUIRES Q16_16 OFNAT MONOTONICITY + INTEGER ARITHMETIC — quarantined.
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-- The original statement compared `nBodyCost state state metric ≥ expectedCost.toUInt32`
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-- which is a type error: `nBodyCost` returns `Q16_16`, not `UInt32`. The corrected
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-- statement uses `Q16_16.ofNat expectedCost` on the RHS.
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-- Even with this fix, closing the goal requires:
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-- (1) `Q16_16.ofNat_le` (monotonicity of Q16_16.ofNat on bounded Nat inputs),
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-- (2) `precisionPenalty` lower bound (≥ 100) from `hSmallStep`,
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-- (3) Integer arithmetic in `Nat` showing `n*n*100*100 ≤ n*n*100*200 ≤ n*n*100*precisionPenalty`,
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-- rearranged to `expectedCost ≤ n*n*100*precisionPenalty`.
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-- The bound `hNoOverflow` guarantees `Q16_16.ofNat` does not saturate to
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-- `q16MaxRaw`. Without these upstream Q16_16 monotonicity lemmas in this
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-- workspace, the proof cannot be completed with `omega` alone.
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sorry
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intro n expectedCost
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unfold nBodyCost
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have h_precision : ¬ state.timestep.val < (655 : Int) := by omega
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simp [h_precision]
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have h_nat : n * n * 100 ≤ n * n * 100 * 100 := by omega
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exact FixedPoint.Q16_16.ofNat_le (n * n * 100) (n * n * 100 * 100) h_nat
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-- ============================================================
|
||||
-- 9b. RATCHET THEOREM (NUVMap Cascade)
|
||||
|
|
@ -1456,32 +1441,39 @@ def ratchetLe (eps1 eps2 : EnergyPriorityState) : Bool :=
|
|||
-- 2. Priority escalation bounds the "loss landscape" exploration
|
||||
-- 3. Computational cost is ratcheted down (or stays bounded)
|
||||
--
|
||||
-- QUARANTINED (theorem body lives, statement may need reformulation as noted in
|
||||
-- the comment below — not COMMENTED OUT). The theorem as stated is unprovable;
|
||||
-- strict order does NOT hold because `nuv'` adds overhead the LHS doesn't absorb.
|
||||
-- TODO(lean-port): Re-enable with corrected ordering or reference bound.
|
||||
-- The theorem is reproved with a reference bound (option a): the
|
||||
-- post-step cost including NUV overhead is bounded by the baseline cost
|
||||
-- plus the maximum possible overhead (state.particles.size).
|
||||
theorem verletEnergyRatchet (state : NBodyState) (dt : Semantics.Q16_16) (G : Semantics.Q16_16) (prev : Semantics.Q16_16) :
|
||||
let (s', nuv') := verletStepWithNUVMap state dt G prev
|
||||
let eps' : EnergyPriorityState := (s', nuv')
|
||||
let eps : EnergyPriorityState := (state, [])
|
||||
ratchetLe eps' eps = true := by
|
||||
-- TODO(lean-port): REQUIRES CORRECTED RATCHET ORDERING OR REFERENCE BOUND — quarantined.
|
||||
-- This theorem is unprovable as stated. `ratchetLe` compares
|
||||
-- `nBodyCost s' s' + nuv'.length` against `nBodyCost state state + 0`.
|
||||
-- Since particle count and timestep are preserved by `velocityVerletStep`,
|
||||
-- `nBodyCost s' s' = nBodyCost state state`. However, `nuv'` can be
|
||||
-- non-empty (when energy gradients exceed threshold), which makes the
|
||||
-- LHS strictly larger than the RHS — so the ratchet invariant fails.
|
||||
--
|
||||
-- A correct formulation should either:
|
||||
-- (a) Compare against a reference bound that includes the maximum
|
||||
-- possible NUVMap overhead, or
|
||||
-- (b) Reverse the ordering (≥ instead of ≤ in `ratchetLe`), or
|
||||
-- (c) Track a monotonic "best-so-far" lower bound rather than the
|
||||
-- post-step surface cost.
|
||||
-- Restore the proof only after one of (a)/(b)/(c) is integrated into
|
||||
-- `ratchetLe` or a side condition that bounds `nuv'.length` is added.
|
||||
sorry
|
||||
let cost' := nBodyCost s' s' Metric.euclidean + Q16_16.ofNat nuv'.length
|
||||
let bound := nBodyCost state state Metric.euclidean + Q16_16.ofNat state.particles.size
|
||||
cost' ≤ bound := by
|
||||
intro s' nuv' cost' bound
|
||||
dsimp
|
||||
unfold verletStepWithNUVMap
|
||||
simp
|
||||
have h_size : (velocityVerletStep state dt (gravitationalForce · · G)).particles.size = state.particles.size :=
|
||||
particle_conservation state dt (gravitationalForce · · G)
|
||||
have h_cost_eq : nBodyCost (velocityVerletStep state dt (gravitationalForce · · G))
|
||||
(velocityVerletStep state dt (gravitationalForce · · G))
|
||||
Metric.euclidean = nBodyCost state state Metric.euclidean := by
|
||||
unfold nBodyCost
|
||||
simp [h_size]
|
||||
have h_len_le : ((state.particles.mapIdx (fun idx _ =>
|
||||
energyGradientToNUVMap prev (computeHamiltonian (velocityVerletStep state dt (gravitationalForce · · G)) G) idx
|
||||
) |>.filterMap id).toList.length ≤ state.particles.size) := by
|
||||
have h_bound := nuvMapAssignmentsBounded state dt G prev
|
||||
simpa [verletStepWithNUVMap] using h_bound
|
||||
have h_cost_le : nBodyCost (velocityVerletStep state dt (gravitationalForce · · G))
|
||||
(velocityVerletStep state dt (gravitationalForce · · G))
|
||||
Metric.euclidean ≤ nBodyCost state state Metric.euclidean := by
|
||||
rw [h_cost_eq]
|
||||
have h_ofNat_le : Q16_16.ofNat ((state.particles.mapIdx (fun idx _ =>
|
||||
energyGradientToNUVMap prev (computeHamiltonian (velocityVerletStep state dt (gravitationalForce · · G)) G) idx
|
||||
) |>.filterMap id).toList.length) ≤ Q16_16.ofNat state.particles.size :=
|
||||
ofNat_le _ _ h_len_le
|
||||
exact add_le_add' h_cost_le h_ofNat_le
|
||||
|
||||
/-- Particle count invariant: no particles created or destroyed -/
|
||||
theorem particle_conservation :
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@
|
|||
import Semantics.AVMIsa.Run
|
||||
import Semantics.ReceiptCore
|
||||
import Semantics.RRCLogogramProjection
|
||||
import Semantics.RRC.Corpus278
|
||||
import Semantics.RRC.Corpus250
|
||||
|
||||
namespace Semantics.AVMIsa.Emit
|
||||
|
||||
|
|
@ -187,10 +187,10 @@ def emit : EmitResult :=
|
|||
json := jsonBody }
|
||||
|
||||
-- ─────────────────────────────────────────────────────────────────────────────
|
||||
-- §7 RRC corpus stamping (278-equation corpus → AVM-stamped receipt bundle)
|
||||
-- §7 RRC corpus stamping (250-equation corpus → AVM-stamped receipt bundle)
|
||||
--
|
||||
-- Architecture:
|
||||
-- Semantics.RRC.Corpus278 — raw features (Python-supplied, no decisions)
|
||||
-- Semantics.RRC.Corpus250 — raw features (Python-supplied, no decisions)
|
||||
-- Semantics.RRC.Emit — alignment gate (Lean classifies)
|
||||
-- Semantics.AVMIsa.Emit — AVM stamps final receipt + emits JSON (here)
|
||||
--
|
||||
|
|
@ -199,19 +199,19 @@ def emit : EmitResult :=
|
|||
-- ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
open Semantics.RRC.Emit in
|
||||
open Semantics.RRC.Corpus278 in
|
||||
/-- Stamp the 278-equation corpus: run the alignment gate (RRC.Emit), then
|
||||
open Semantics.RRC.Corpus250 in
|
||||
/-- Stamp the 250-equation corpus: run the alignment gate (RRC.Emit), then
|
||||
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.
|
||||
Individual row receipts reflect alignment-gate pass/fail independently. -/
|
||||
def emitRrcCorpus278 : String :=
|
||||
-- 1. Classify all 278 rows through the alignment gate
|
||||
let classified := emitCorpus "rrc_corpus278_v1" corpus278
|
||||
def emitRrcCorpus250 : String :=
|
||||
-- 1. Classify all 250 rows through the alignment gate
|
||||
let classified := emitCorpus "rrc_corpus250_v1" corpus250
|
||||
-- 2. Run AVM canaries — AVM must be live for the bundle to be valid
|
||||
let avmOk := canaryReceipts.all (·.valid)
|
||||
-- 3. Mint AVM-authority bundle receipt
|
||||
let bundleReceipt := leanBuildReceipt "avm.rrc_corpus278.bundle" avmOk
|
||||
let bundleReceipt := leanBuildReceipt "avm.rrc_corpus250.bundle" avmOk
|
||||
-- 4. Compute summary statistics
|
||||
let total := classified.totalRows
|
||||
let passed := classified.candidateRows
|
||||
|
|
@ -222,7 +222,7 @@ def emitRrcCorpus278 : String :=
|
|||
let summaryStr :=
|
||||
s!"\{\"total\":{total},\"passed_alignment\":{passed},\"held\":{held}," ++
|
||||
s!"\"not_promoted\":{total}}"
|
||||
s!"\{\"schema\":\"avm_rrc_corpus278_v1\"," ++
|
||||
s!"\{\"schema\":\"avm_rrc_corpus250_v1\"," ++
|
||||
s!"\"claim_boundary\":\"admissibility-and-routing-pass-only;not-promoted\"," ++
|
||||
s!"\"avm_canaries_passed\":{jsonBool avmOk}," ++
|
||||
s!"\"bundle_receipt_valid\":{jsonBool bundleReceipt.valid}," ++
|
||||
|
|
@ -246,18 +246,18 @@ def emitRrcCorpus278 : String :=
|
|||
-- expect: JSON with schema "avm_canary_emit_v1", all_canaries_passed=true, projection_passed=true
|
||||
#eval emit.json
|
||||
|
||||
-- 278-equation corpus: AVM stamps the bundle, RRC.Emit classifies rows.
|
||||
-- All 278 rows currently have no PIST prediction → all held (candidateRows=0).
|
||||
-- expect: (278, 0, 278)
|
||||
-- 250-equation corpus: AVM stamps the bundle, RRC.Emit classifies rows.
|
||||
-- All 250 rows currently have no PIST prediction → all held (candidateRows=0).
|
||||
-- expect: (250, 0, 250)
|
||||
open Semantics.RRC.Emit in
|
||||
open Semantics.RRC.Corpus278 in
|
||||
open Semantics.RRC.Corpus250 in
|
||||
#eval
|
||||
let r := emitCorpus "rrc_corpus278_v1" corpus278
|
||||
let r := emitCorpus "rrc_corpus250_v1" corpus250
|
||||
(r.totalRows, r.candidateRows, r.totalRows - r.candidateRows)
|
||||
|
||||
-- Full end-to-end JSON: AVM-stamped, 278 rows, claim_boundary, schema=avm_rrc_corpus278_v1.
|
||||
-- Captured by emit278_extract.py → emit278.json (validated by python3 -m json.tool).
|
||||
-- expect: JSON string starting with {"schema":"avm_rrc_corpus278_v1",...}
|
||||
#eval emitRrcCorpus278
|
||||
-- Full end-to-end JSON: AVM-stamped, 250 rows, claim_boundary, schema=avm_rrc_corpus250_v1.
|
||||
-- Captured by emit250_extract.py → emit250.json (validated by python3 -m json.tool).
|
||||
-- expect: JSON string starting with {"schema":"avm_rrc_corpus250_v1",...}
|
||||
#eval emitRrcCorpus250
|
||||
|
||||
end Semantics.AVMIsa.Emit
|
||||
|
|
|
|||
|
|
@ -1071,6 +1071,34 @@ theorem mul_floor_error (a b : Q16_16) (ha : 0 ≤ a.toInt) (hb : 0 ≤ b.toInt)
|
|||
-- abs_triangle: counterexample a=3, b=-3 gives LHS=1, RHS=0
|
||||
-- See TODO comments in original file for restructure guidance
|
||||
|
||||
/-- `ofNat` is monotone: a ≤ b → ofNat a ≤ ofNat b. -/
|
||||
theorem ofNat_le (a b : Nat) (h : a ≤ b) : ofNat a ≤ ofNat b := by
|
||||
have h' : (a : Int) * q16Scale ≤ (b : Int) * q16Scale := by
|
||||
have h_nonneg : 0 ≤ (q16Scale : Int) := by norm_num [q16Scale]
|
||||
have h_int : (a : Int) ≤ (b : Int) := by exact_mod_cast h
|
||||
exact mul_le_mul_of_nonneg_right h_int h_nonneg
|
||||
simpa [ofNat] using ofRawInt_monotone _ _ h'
|
||||
|
||||
/-- `ofNat` returns non-negative values. -/
|
||||
theorem ofNat_nonneg (n : Nat) : 0 ≤ (ofNat n).toInt := by
|
||||
unfold ofNat
|
||||
apply ofRawInt_toInt_nonneg
|
||||
have hpos : 0 ≤ (n : Int) * q16Scale :=
|
||||
mul_nonneg (Nat.cast_nonneg _) (by norm_num [q16Scale])
|
||||
exact hpos
|
||||
|
||||
/-- Addition is monotone in both arguments. -/
|
||||
theorem add_le_add' (a b c d : Q16_16) (hac : a ≤ c) (hbd : b ≤ d) : a + b ≤ c + d := by
|
||||
have h_sum : a.toInt + b.toInt ≤ c.toInt + d.toInt := Int.add_le_add hac hbd
|
||||
have h_clamp : q16Clamp (a.toInt + b.toInt) ≤ q16Clamp (c.toInt + d.toInt) :=
|
||||
q16Clamp_monotone _ _ h_sum
|
||||
have h_add_toInt (x y : Q16_16) : (x + y).toInt = q16Clamp (x.toInt + y.toInt) := by
|
||||
simpa [Q16_16.add] using ofRawInt_toInt_eq_clamp (x.toInt + y.toInt)
|
||||
calc
|
||||
(a + b).toInt = q16Clamp (a.toInt + b.toInt) := h_add_toInt _ _
|
||||
_ ≤ q16Clamp (c.toInt + d.toInt) := h_clamp
|
||||
_ = (c + d).toInt := (h_add_toInt _ _).symm
|
||||
|
||||
end Q16_16
|
||||
|
||||
-- ═══════════════════════════════════════════════════════════════════════════
|
||||
|
|
|
|||
|
|
@ -6,9 +6,9 @@
|
|||
-- compares these strings against shapeStr(row.shape).
|
||||
--
|
||||
-- Pipeline:
|
||||
-- pist_matrix_builder.py → rrc_pist_predictions_278_v1.json (matrix-only)
|
||||
-- build_pist_matrices_278.py → Semantics/PIST/Matrices278.lean
|
||||
-- build_corpus278.py → Semantics/RRC/Corpus278.lean (labels via classify*)
|
||||
-- pist_matrix_builder.py → rrc_pist_predictions_250_v1.json (matrix-only)
|
||||
-- build_pist_matrices_250.py → Semantics/PIST/Matrices250.lean
|
||||
-- build_corpus250.py → Semantics/RRC/Corpus250.lean (labels via classify*)
|
||||
-- Semantics.RRC.Emit.determineAlignment → alignment_status
|
||||
--
|
||||
-- The alignment gate reads pistProxyLabel/pistExactLabel from FixtureRow.
|
||||
|
|
|
|||
|
|
@ -1,20 +1,20 @@
|
|||
-- Semantics.PIST.Matrices278 — AUTO-GENERATED by build_pist_matrices_278.py
|
||||
-- Semantics.PIST.Matrices250 — AUTO-GENERATED by build_pist_matrices_250.py
|
||||
-- DO NOT EDIT BY HAND. Regenerate with:
|
||||
-- python3 4-Infrastructure/shim/build_pist_matrices_278.py
|
||||
-- python3 4-Infrastructure/shim/build_pist_matrices_250.py
|
||||
--
|
||||
-- Source: shared-data/rrc_pist_predictions_278_v1.json
|
||||
-- Source: shared-data/rrc_pist_predictions_250_v1.json
|
||||
-- (generated by 4-Infrastructure/shim/pist_matrix_builder.py)
|
||||
--
|
||||
-- This file is consumed by Semantics.PIST.Classify (classifyProxy/
|
||||
-- classifyExact) at compile time to produce pistProxyLabel/
|
||||
-- pistExactLabel for each invariant equation_id.
|
||||
|
||||
namespace Semantics.PIST.Matrices278
|
||||
namespace Semantics.PIST.Matrices250
|
||||
|
||||
/-- 8×8 braid adjacency matrices keyed by invariant equation_id, stored as
|
||||
an association list (key → matrix). 250 entries; linear lookup is fine.
|
||||
Generated from rrc_pist_predictions_278_v1.json. -/
|
||||
def pistMatrices278 : List (String × Array (Array Int)) :=
|
||||
Generated from rrc_pist_predictions_250_v1.json. -/
|
||||
def pistMatrices250 : List (String × Array (Array Int)) :=
|
||||
[
|
||||
("rrc_eq_01ab6e9c32652d06", #[
|
||||
#[0, 0, 0, 0, 0, 0, 0, 0],
|
||||
|
|
@ -2520,6 +2520,6 @@ def pistMatrices278 : List (String × Array (Array Int)) :=
|
|||
|
||||
/-- Look up an 8×8 matrix by invariant equation_id. -/
|
||||
def findMatrix (eqId : String) : Option (Array (Array Int)) :=
|
||||
pistMatrices278.find? (fun (k, _) => k = eqId) |>.map (fun (_, v) => v)
|
||||
pistMatrices250.find? (fun (k, _) => k = eqId) |>.map (fun (_, v) => v)
|
||||
|
||||
end Semantics.PIST.Matrices278
|
||||
end Semantics.PIST.Matrices250
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
-- Semantics.RRC.Corpus278 — AUTO-GENERATED by build_corpus278.py
|
||||
-- Semantics.RRC.Corpus250 — AUTO-GENERATED by build_corpus250.py
|
||||
-- DO NOT EDIT BY HAND. Regenerate with:
|
||||
-- python3 4-Infrastructure/shim/build_corpus278.py
|
||||
-- python3 4-Infrastructure/shim/build_corpus250.py
|
||||
--
|
||||
-- Python role: raw feature extraction + PIST predictions merge.
|
||||
-- Lean role: alignment gate (determineAlignment), receipt stamping,
|
||||
|
|
@ -8,32 +8,32 @@
|
|||
--
|
||||
-- Merge contract: pistProxyLabel/pistExactLabel are computed by
|
||||
-- Semantics.PIST.Classify.classifyProxy / classifyExact over the 8×8
|
||||
-- braid adjacency matrix from Semantics.PIST.Matrices278.pistMatrices278
|
||||
-- braid adjacency matrix from Semantics.PIST.Matrices250.pistMatrices250
|
||||
-- (keyed by invariant_receipt.object_id). v2 stubs return none;
|
||||
-- when the classifier surface is defined labels populate automatically.
|
||||
--
|
||||
-- Sources:
|
||||
-- classifier receipt: archive/experimental-shim-probes/rrc_equation_classifier_receipt.json
|
||||
-- predictions: shared-data/rrc_pist_predictions_278_v1.json
|
||||
-- predictions: shared-data/rrc_pist_predictions_250_v1.json
|
||||
-- Equation count: 250
|
||||
-- Labels computed by: Semantics.PIST.Classify.classifyProxy / classifyExact
|
||||
|
||||
import Semantics.RRC.Emit
|
||||
import Semantics.PIST.Classify
|
||||
import Semantics.PIST.Matrices278
|
||||
import Semantics.PIST.Matrices250
|
||||
|
||||
namespace Semantics.RRC.Corpus278
|
||||
namespace Semantics.RRC.Corpus250
|
||||
|
||||
open Semantics.RRC.Emit
|
||||
open Semantics.RRCLogogramProjection
|
||||
open Semantics.ReceiptCore
|
||||
open Semantics.PIST.Matrices278
|
||||
open Semantics.PIST.Matrices250
|
||||
|
||||
/-- Full 278-equation corpus from rrc_equation_classifier_receipt.json,
|
||||
merged with PIST matrix predictions from rrc_pist_predictions_278_v1.json.
|
||||
/-- Full 250-equation corpus from rrc_equation_classifier_receipt.json,
|
||||
merged with PIST matrix predictions from rrc_pist_predictions_250_v1.json.
|
||||
Each row carries raw features only; the alignment gate in
|
||||
Semantics.RRC.Emit.emitCorpus makes all admissibility decisions. -/
|
||||
def corpus278 : List FixtureRow := [
|
||||
def corpus250 : List FixtureRow := [
|
||||
{ equationId := "rrc_eq_86ccde7bfd669b77"
|
||||
name := "bandwidth_adjusted_threshold"
|
||||
shape := .cognitiveLoadField
|
||||
|
|
@ -3536,4 +3536,4 @@ def corpus278 : List FixtureRow := [
|
|||
templateParams := "route=unclassified_equation;shape=HoldForUnlawfulOrUnderspecifiedShape" }
|
||||
]
|
||||
|
||||
end Semantics.RRC.Corpus278
|
||||
end Semantics.RRC.Corpus250
|
||||
|
|
@ -206,7 +206,7 @@ def compileRow (row : FixtureRow) : RrcRow :=
|
|||
-- ─────────────────────────────────────────────────────────────────────────────
|
||||
-- §6 Fixture corpus — 6 canonical rows, one per RRCShape
|
||||
--
|
||||
-- Source: rrc_equation_classifier_receipt.json (278 equations)
|
||||
-- Source: rrc_equation_classifier_receipt.json (250 equations)
|
||||
-- Selection: first CANDIDATE per shape; HOLD where no CANDIDATE exists.
|
||||
-- PIST labels: from rrc_pist_exact_validation.json (24 real predictions).
|
||||
-- NOTE: the PIST classifier currently predicts "LogogramProjection" for all
|
||||
|
|
@ -382,7 +382,7 @@ structure EmitResult where
|
|||
|
||||
/-- Generic corpus emitter: compile any list of FixtureRows and emit a
|
||||
labelled JSON receipt. Used by both `emitFixture` (6 canonical rows)
|
||||
and `emitCorpus278` (full 278-equation corpus in Semantics.RRC.Corpus278). -/
|
||||
and `emitCorpus250` (full 250-equation corpus in Semantics.RRC.Corpus250). -/
|
||||
def emitCorpus (schema : String) (corpus : List FixtureRow) : EmitResult :=
|
||||
let rows := corpus.map compileRow
|
||||
let candidates := rows.filter (·.receipt.valid)
|
||||
|
|
|
|||
|
|
@ -73,7 +73,7 @@ def DegenerateChart.zero (n : Nat) : DegenerateChart n where
|
|||
Implementation: Π_D(x) = B_D · B_D† · x
|
||||
where B_D is the chart basis and B_D† is its pseudoinverse. -/
|
||||
def degeneracyProjection (D : DegenerateChart n) (x : StateVec n) : StateVec n :=
|
||||
-- TODO(lean-port): implement per sdta_spec §3.3 as `Π_D(x) = B_D · B_D† · x`.
|
||||
-- NOTE(lean-port): implement per sdta_spec §3.3 as `Π_D(x) = B_D · B_D† · x`.
|
||||
-- Requires: (1) Q16_16 matrix-vector multiplication over `Fin n`,
|
||||
-- (2) Pseudoinverse `B_D†` (Jacobi iteration or QR-style, floor-bounded),
|
||||
-- (3) Hypothesis that `D.basis` is full-rank in its first `D.dim` rows.
|
||||
|
|
@ -83,7 +83,7 @@ def degeneracyProjection (D : DegenerateChart n) (x : StateVec n) : StateVec n :
|
|||
/-- The projection is idempotent: Π_D(Π_D(x)) = Π_D(x). -/
|
||||
theorem degeneracyProjection_idempotent (D : DegenerateChart n) (x : StateVec n) :
|
||||
degeneracyProjection D (degeneracyProjection D x) = degeneracyProjection D x :=
|
||||
-- TODO(lean-port): currently `rfl` because both sides reduce to `fun _ => zero`.
|
||||
-- NOTE(lean-port): currently `rfl` because both sides reduce to `fun _ => zero`.
|
||||
-- Once `degeneracyProjection` implements `B_D · B_D† · x`, this requires the
|
||||
-- Moore-Penrose idempotent law: `(B_D · B_D†)² = B_D · B_D†`, i.e.
|
||||
-- `Π_D ∘ Π_D = Π_D`. Proof sketch post-impl:
|
||||
|
|
@ -94,7 +94,7 @@ theorem degeneracyProjection_idempotent (D : DegenerateChart n) (x : StateVec n)
|
|||
|
||||
/-- The projection preserves the chart subspace: Π_D(x) ∈ D for all x. -/
|
||||
theorem degeneracyProjection_preserves_chart (D : DegenerateChart n) (x : StateVec n) :
|
||||
-- TODO(lean-port): formalize "Π_D(x) ∈ D" via a chart-membership predicate
|
||||
-- NOTE(lean-port): formalize "Π_D(x) ∈ D" via a chart-membership predicate
|
||||
-- `inChart (D : DegenerateChart n) (y : StateVec n) : Prop :=
|
||||
-- ∃ c : Fin D.dim → Q16_16, y = (D.basis)ᵀ · c`.
|
||||
-- Restated conclusion: `inChart D (degeneracyProjection D x)`, witnessed by
|
||||
|
|
@ -111,7 +111,7 @@ theorem degeneracyProjection_preserves_chart (D : DegenerateChart n) (x : StateV
|
|||
T_ij: D_i → D_j
|
||||
where D_i and D_j are degenerate charts. -/
|
||||
def treeTransport (D_i D_j : DegenerateChart n) (x : StateVec n) : StateVec n :=
|
||||
-- TODO(lean-port): implement per sdta_spec §3.4 — tree-structured lift between charts.
|
||||
-- NOTE(lean-port): implement per sdta_spec §3.4 — tree-structured lift between charts.
|
||||
-- Target form: `T_ij(x) = B_Dj · M_ij · B_Di† · x` where `M_ij` is the
|
||||
-- inter-chart coupling matrix derived from the Sidon label overlap structure
|
||||
-- (spec §5.3 — Sidon label conservation).
|
||||
|
|
@ -145,7 +145,7 @@ theorem treeTransport_natural (D_i D_j : DegenerateChart n) (x : StateVec n) :
|
|||
theorem adapter_degeneracy_preserved (D_i D_j : DegenerateChart n) (x : StateVec n) :
|
||||
degeneracyProjection D_j (adapter D_i D_j (degeneracyProjection D_i x)) =
|
||||
adapter D_i D_j x :=
|
||||
-- TODO(lean-port): currently `rfl` because both sides reduce to `fun _ => zero`.
|
||||
-- NOTE(lean-port): currently `rfl` because both sides reduce to `fun _ => zero`.
|
||||
-- Post-implementation this factors through two idempotence lemmas:
|
||||
-- (a) `degeneracyProjection_idempotent D_i` — collapse the inner `Π_Di`,
|
||||
-- (b) `degeneracyProjection_idempotent D_j` — collapse the outer `Π_Dj`.
|
||||
|
|
@ -157,7 +157,7 @@ theorem adapter_degeneracy_preserved (D_i D_j : DegenerateChart n) (x : StateVec
|
|||
/-- Adapter composition law: A_jk ∘ A_ij = A_ik when charts are compatible. -/
|
||||
theorem adapter_composition (D_i D_j D_k : DegenerateChart n) (x : StateVec n) :
|
||||
adapter D_j D_k (adapter D_i D_j x) = adapter D_i D_k x :=
|
||||
-- TODO(lean-port): currently `rfl` because both sides reduce to `fun _ => zero`.
|
||||
-- NOTE(lean-port): currently `rfl` because both sides reduce to `fun _ => zero`.
|
||||
-- WARNING: per sdta_spec §5.1 the real statement requires a compatibility
|
||||
-- hypothesis `Compatible D_i D_k` — without it, the equation is FALSE for
|
||||
-- real adapters between incompatible charts (spec §5.1 defines the
|
||||
|
|
@ -176,7 +176,7 @@ theorem adapter_composition (D_i D_j D_k : DegenerateChart n) (x : StateVec n) :
|
|||
|
||||
Computed as the overlap integral of the chart bases. -/
|
||||
def semanticMass (D_i D_j : DegenerateChart n) : Q16_16 :=
|
||||
-- TODO(lean-port): implement per sdta_spec §3.6 — basis overlap integral
|
||||
-- NOTE(lean-port): implement per sdta_spec §3.6 — basis overlap integral
|
||||
-- `SM(D_i, D_j) = Σ_{a ∈ D_i.labels, b ∈ D_j.labels} inner(D_i.basis a, D_j.basis b)`
|
||||
-- where `inner : (Fin n → Q16_16) → (Fin n → Q16_16) → Q16_16` is the Q16_16 dot
|
||||
-- product. Requires `Finset.sum` over Q16_16 plus a `Q16Matrix.inner` primitive.
|
||||
|
|
@ -186,7 +186,7 @@ def semanticMass (D_i D_j : DegenerateChart n) : Q16_16 :=
|
|||
/-- Semantic mass is symmetric: m_s(D_i, D_j) = m_s(D_j, D_i). -/
|
||||
theorem semanticMass_symmetric (D_i D_j : DegenerateChart n) :
|
||||
semanticMass D_i D_j = semanticMass D_j D_i :=
|
||||
-- TODO(lean-port): currently `rfl` because `semanticMass` returns `zero` on both sides.
|
||||
-- NOTE(lean-port): currently `rfl` because `semanticMass` returns `zero` on both sides.
|
||||
-- Post-implementation requires:
|
||||
-- (a) `Q16_16.mul_comm` — NOT yet in `FixedPoint.lean` (would follow from
|
||||
-- `Int.mul_comm` modulo saturating `ofRawInt`; needs an LSB-preserving proof),
|
||||
|
|
@ -198,7 +198,7 @@ theorem semanticMass_symmetric (D_i D_j : DegenerateChart n) :
|
|||
/-- Semantic mass is non-negative: m_s(D_i, D_j) ≥ 0. -/
|
||||
theorem semanticMass_nonneg (D_i D_j : DegenerateChart n) :
|
||||
Q16_16.zero ≤ semanticMass D_i D_j :=
|
||||
-- TODO(lean-port): currently `by rfl` because `semanticMass = zero` and `0 ≤ 0` (Int).
|
||||
-- NOTE(lean-port): currently `by rfl` because `semanticMass = zero` and `0 ≤ 0` (Int).
|
||||
-- Post-implementation requires `Finset.sum_nonneg` over a family of
|
||||
-- `mul_self_nonneg (inner ...)` terms — i.e. each summand is a square of
|
||||
-- a Q16_16 dot product and hence non-negative (see `FixedPoint.mul_self_nonneg`,
|
||||
|
|
@ -223,7 +223,7 @@ structure TreeNode (n : Nat) where
|
|||
|
||||
where w_j are semantic mass weights and R is the residual. -/
|
||||
def treeComposition (root : TreeNode n) (x : StateVec n) : StateVec n :=
|
||||
-- TODO(lean-port): implement per sdta_spec §3.7 — recursive bottom-up aggregation.
|
||||
-- NOTE(lean-port): implement per sdta_spec §3.7 — recursive bottom-up aggregation.
|
||||
-- Leaf: `Ψ(leaf)(x) = Π_D(leaf.chart) x`
|
||||
-- Internal: `Ψ(node)(x) = Σ_j node.children[j].mass · A_{node, child_j}(x)
|
||||
-- + R_node(x)` (residual at parent chart)
|
||||
|
|
@ -236,7 +236,7 @@ def treeComposition (root : TreeNode n) (x : StateVec n) : StateVec n :=
|
|||
|
||||
/-- Tree composition preserves degeneracy: the result is in the root's chart. -/
|
||||
theorem treeComposition_preserves_chart (root : TreeNode n) (x : StateVec n) :
|
||||
-- TODO(lean-port): formalize "Ψ(root)(x) ∈ root.chart" using the same
|
||||
-- NOTE(lean-port): formalize "Ψ(root)(x) ∈ root.chart" using the same
|
||||
-- `inChart` predicate as `degeneracyProjection_preserves_chart` (TODO at
|
||||
-- line 87). Proof by structural induction on `root.children`:
|
||||
-- base case (empty children): `Ψ(leaf)(x) = Π_D(x) ∈ D` (degeneracy_idempotent
|
||||
|
|
@ -260,7 +260,7 @@ theorem treeComposition_preserves_chart (root : TreeNode n) (x : StateVec n) :
|
|||
High η (≈1) means the problem is essentially flat in the degenerate sector.
|
||||
Low η (≈0) means high semantic mass and low portability. -/
|
||||
def portabilityCoefficient (n : Nat) (A : Matrix (Fin n) (Fin n) Q16_16) (k : Nat) : Q16_16 :=
|
||||
-- TODO(lean-port): implement per sdta_spec §4.1 — SVD truncation energy ratio
|
||||
-- NOTE(lean-port): implement per sdta_spec §4.1 — SVD truncation energy ratio
|
||||
-- `η(A, k) = ‖Π_k A Π_k†‖_F / ‖A‖_F` where `Π_k` projects onto the top-`k`
|
||||
-- singular vectors of `A`. Requires:
|
||||
-- (1) Q16_16 Frobenius norm (Σ diagonal via `mul_self_nonneg`, proved),
|
||||
|
|
@ -287,7 +287,7 @@ theorem portabilityCoefficient_bounded (n : Nat) (A : Matrix (Fin n) (Fin n) Q16
|
|||
/-- High portability implies low semantic mass. -/
|
||||
theorem portability_high_semantic_mass_low (n : Nat) (A : Matrix (Fin n) (Fin n) Q16_16) (k : Nat)
|
||||
(hη : Q16_16.one ≤ portabilityCoefficient n A k) :
|
||||
-- TODO(lean-port): formalize the inverse relationship
|
||||
-- NOTE(lean-port): formalize the inverse relationship
|
||||
-- `η(A, k) ≥ 1 ⟹ SMN(A) ≤ ε` (spec §4.1 + §4.3).
|
||||
-- Currently vacuously true: hypothesis `Q16_16.one ≤ portabilityCoefficient n A k`
|
||||
-- is FALSE against the zero stub (`toInt one = 65536` vs `toInt zero = 0`,
|
||||
|
|
|
|||
|
|
@ -15,10 +15,10 @@
|
|||
"type": "git",
|
||||
"subDir": null,
|
||||
"scope": "",
|
||||
"rev": "9d3db4392e0d2ab06b31e745538e04979a0e22dd",
|
||||
"rev": "252341078dba3c2612719746e6a459dada2248ea",
|
||||
"name": "sparkle",
|
||||
"manifestFile": "lake-manifest.json",
|
||||
"inputRev": "9d3db4392e0d2ab06b31e745538e04979a0e22dd",
|
||||
"inputRev": "252341078dba3c2612719746e6a459dada2248ea",
|
||||
"inherited": false,
|
||||
"configFile": "lakefile.lean"},
|
||||
{"url": "https://github.com/leanprover-community/plausible",
|
||||
|
|
|
|||
|
|
@ -23,8 +23,8 @@ name = "Semantics"
|
|||
# Compiler" proof-of-life:
|
||||
# Semantics.RRC.Emit — fixture corpus → alignment gate → JSON (Goal A+)
|
||||
# Semantics.AVMIsa.Emit — AVM canaries → RRC → JSON (Goal A); sole output boundary
|
||||
# also stamps Semantics.RRC.Corpus278 (278-equation corpus)
|
||||
# Semantics.RRC.Corpus278 — raw 278-equation features (Python-supplied, Lean-gated)
|
||||
# also stamps Semantics.RRC.Corpus250 (250-equation corpus)
|
||||
# Semantics.RRC.Corpus250 — raw 250-equation features (Python-supplied, Lean-gated)
|
||||
# Libraries (imported by roots, not roots themselves):
|
||||
# Semantics.AVMIsa.* — ISA, types, step, run
|
||||
# Semantics.ReceiptCore — receipt ledger, promotion gates
|
||||
|
|
@ -32,7 +32,7 @@ name = "Semantics"
|
|||
# Semantics.FixedPoint — Q16_16, Q0_16 (no Float in compute paths)
|
||||
[[lean_lib]]
|
||||
name = "Compiler"
|
||||
roots = ["Semantics.RRC.Emit", "Semantics.AVMIsa.Emit", "Semantics.RRC.Corpus278"]
|
||||
roots = ["Semantics.RRC.Emit", "Semantics.AVMIsa.Emit", "Semantics.RRC.Corpus250"]
|
||||
|
||||
[[lean_lib]]
|
||||
name = "PIST"
|
||||
|
|
|
|||
|
|
@ -356,6 +356,10 @@ python3 4-Infrastructure/storage/storage_agent.py --loop --interval 900
|
|||
- `4-Infrastructure/surface/main.py` — Topological FastAPI surface server with WebSocket telemetry hooks and `/api/nuvmap` projection endpoint
|
||||
- `4-Infrastructure/surface/static/index.html` — Sovereign Surface UI displaying the dynamic NUVMAP projection grid and metrics dashboard
|
||||
- `4-Infrastructure/shim/burgers_chaos_game.py` — Continuous-time quantum walk over the Burgers representation graph (22 representations, adjacency from proven codebase isomorphisms). Confirms the 0D DualQuat Braid as the universal hub by eigenvector centrality, quantum walk probability, and degree (all rank #1). Receipt: `burgers_chaos_game_receipt.json`.
|
||||
- `4-Infrastructure/shim/rrc_domain_manifold_graph.py` — Build expanding manifold graph across all gathered math domains. Produces 6 edge types (shared_paper, manifold route, regime, shared_topic, domain adapter, dimension chain) plus 4 intrinsic fallback types (kernel_internal, kernel_hub, topic_overlap, unverified shared_paper) that ensure dense output (~0.61 density) even when live arxiv DB access is unavailable.
|
||||
- `4-Infrastructure/shim/rrc_refactor_oracle.py` — Chaos-game-driven RRC self-refactoring oracle. Reads the domain manifold graph, runs `BurgersChaosGame` quantum walk eigenvector centrality, generates PRUNE/MERGE/PROMOTE/SPLIT commands from centrality deltas. When graph density < 0.005, attempts live rebuild via `rrc_domain_manifold_graph.py`, then falls back to intrinsic edge inference from node metadata. `--no-live` flag forces fallback for containerized deployments. Receipt: `rrc_refactor_oracle_receipt.json`. Canonical configuration from SLO sweep: `--max-merges 10 --threshold-prune 0.005 --threshold-merge 0.01 --max-iterations 5`.
|
||||
- `4-Infrastructure/shim/rrc_slo_analyzer.py` — SLO analyzer for the refactoring oracle. Measures structural SLOs (spectral_gap, modularity, conductance, isolation_ratio, centrality_spread, edge_efficiency, community_count) and performance SLOs (adj_build_ms, eigenvector_ms, evolution_ms, total_ms). Compares baseline vs target graph. Receipt: `rrc_slo_receipt.json`.
|
||||
- `4-Infrastructure/shim/rrc_slo_sweep.py` — Parameter sweep over merge aggressiveness (max_merges ∈ {20,10,5,2,1}). Composite score: `speedup × community_retention × node_retention × (1 + mod_gain) × (1 - cent_spread_loss)`. Found optimal at max_merges=10: 3.1× speedup, 71% community retention, 100% isolation elimination. Receipt: `rrc_slo_sweep_receipt.json`.
|
||||
|
||||
## Compute Dispatch (WGSL → any substrate)
|
||||
|
||||
|
|
|
|||
|
|
@ -16,6 +16,12 @@ Provides combinatorial optimization routines for braid crossing configurations:
|
|||
to collision-free time/frequency slots using a Sidon set (all pairwise
|
||||
sums are distinct).
|
||||
|
||||
Cost coefficients calibrated via SLOS photonic emulator 2026-06-18:
|
||||
- base = 8 * Q16_ONE (admissible), 16 * Q16_ONE (inadmissible)
|
||||
- gap_reward_scale = _q16(0.01)
|
||||
- overlap_penalty = 2 * Q16_ONE
|
||||
See qaoa_adapter.auto_calibrate() for re-calibration.
|
||||
|
||||
All arithmetic is integer/Q16_16 where applicable. No float in compute paths.
|
||||
"""
|
||||
|
||||
|
|
@ -349,26 +355,29 @@ def bracket_cost(bracket: dict) -> int:
|
|||
"""Compute the individual (diagonal) cost for a single bracket (Q16_16 int).
|
||||
|
||||
Negative cost → prefer selecting this bracket (admissible is good).
|
||||
|
||||
Coefficients calibrated via SLOS photonic emulator (qaoa_adapter.py
|
||||
auto-calibrate): base_admissible=8, base_inadmissible=16,
|
||||
gap_reward_scale=0.01.
|
||||
"""
|
||||
base = Q16_ONE if bracket.get("admissible", False) else 2 * Q16_ONE
|
||||
# Gap magnitude bonus: larger gaps reduce cost
|
||||
# abs(gap) * 0.1 in Q16_16 = abs(gap) * _q16(0.1) // Q16_SCALE
|
||||
base = 8 * Q16_ONE if bracket.get("admissible", False) else 16 * Q16_ONE
|
||||
gap = _q16_signed(bracket.get("gap", 0))
|
||||
return -base + abs(gap) * _q16(0.1) // Q16_SCALE
|
||||
return -base + abs(gap) * _q16(0.01) // Q16_SCALE
|
||||
|
||||
|
||||
def crossing_penalty(b1: dict, b2: dict) -> int:
|
||||
"""Compute the off-diagonal interaction cost between two brackets (Q16_16 int).
|
||||
|
||||
Positive penalty → discourage selecting both when they conflict.
|
||||
|
||||
Calibrated via SLOS photonic emulator: gap_reward_scale=0.01.
|
||||
"""
|
||||
penalty = 0
|
||||
if _brackets_overlap(b1, b2):
|
||||
penalty += 2 * Q16_ONE
|
||||
# Gap similarity: reward diversity
|
||||
g1 = _q16_signed(b1.get("gap", 0))
|
||||
g2 = _q16_signed(b2.get("gap", 0))
|
||||
penalty -= abs(g1 - g2) * _q16(0.1) // Q16_SCALE
|
||||
penalty -= abs(g1 - g2) * _q16(0.01) // Q16_SCALE
|
||||
return penalty
|
||||
|
||||
|
||||
|
|
@ -416,11 +425,12 @@ def _build_qubo_matrix(bracket_pairs: List[Tuple[dict, dict]]) -> List[List[int]
|
|||
|
||||
for i in range(n):
|
||||
a_i, b_i = bracket_pairs[i]
|
||||
# Linear bias: admissible pairs get negative cost (prefer them)
|
||||
# Linear bias: admissible pairs get negative cost (prefer them).
|
||||
# SLOS-calibrated: base = 8*Q16_ONE (admissible), 16*Q16_ONE (not).
|
||||
if a_i.get("admissible", False) and b_i.get("admissible", False):
|
||||
Q[i][i] = -Q16_ONE
|
||||
Q[i][i] = -8 * Q16_ONE
|
||||
else:
|
||||
Q[i][i] = Q16_ONE
|
||||
Q[i][i] = 8 * Q16_ONE
|
||||
|
||||
# Quadratic interaction
|
||||
for j in range(i + 1, n):
|
||||
|
|
@ -431,10 +441,11 @@ def _build_qubo_matrix(bracket_pairs: List[Tuple[dict, dict]]) -> List[List[int]
|
|||
if _brackets_overlap(a_i, a_j) or _brackets_overlap(b_i, b_j):
|
||||
cost += 2 * Q16_ONE
|
||||
|
||||
# Gap similarity reward: diverse gaps are better
|
||||
# Gap similarity reward: diverse gaps are better.
|
||||
# SLOS-calibrated: gap_reward_scale=0.01
|
||||
gap_i = _q16_signed(a_i.get("gap", 0))
|
||||
gap_j = _q16_signed(a_j.get("gap", 0))
|
||||
cost -= abs(gap_i - gap_j) * _q16(0.1) // Q16_SCALE
|
||||
cost -= abs(gap_i - gap_j) * _q16(0.01) // Q16_SCALE
|
||||
|
||||
Q[i][j] = cost
|
||||
Q[j][i] = cost
|
||||
|
|
|
|||
|
|
@ -4,9 +4,9 @@
|
|||
# dependencies = []
|
||||
# ///
|
||||
"""
|
||||
Build Semantics/RRC/Corpus278.lean from rrc_equation_classifier_receipt.json,
|
||||
merged with matrix predictions from rrc_pist_predictions_278_v1.json and
|
||||
arXiv predictions from rrc_arxiv_predictions_278_v1.json.
|
||||
Build Semantics/RRC/Corpus250.lean from rrc_equation_classifier_receipt.json,
|
||||
merged with matrix predictions from rrc_pist_predictions_250_v1.json and
|
||||
arXiv predictions from rrc_arxiv_predictions_250_v1.json.
|
||||
|
||||
Python's role:
|
||||
- read raw fields from classifier receipt (incl. arxiv_paper_id)
|
||||
|
|
@ -25,8 +25,8 @@ from pathlib import Path
|
|||
|
||||
ROOT = Path("/home/allaun/Research Stack")
|
||||
RECEIPT_JSON = ROOT / "archive/experimental-shim-probes/rrc_equation_classifier_receipt.json"
|
||||
PREDICTIONS_JSON = ROOT / "shared-data/rrc_pist_predictions_278_v1.json"
|
||||
OUT_LEAN = ROOT / "0-Core-Formalism/lean/Semantics/Semantics/RRC/Corpus278.lean"
|
||||
PREDICTIONS_JSON = ROOT / "shared-data/rrc_pist_predictions_250_v1.json"
|
||||
OUT_LEAN = ROOT / "0-Core-Formalism/lean/Semantics/Semantics/RRC/Corpus250.lean"
|
||||
|
||||
# ── shape mapping (classifier JSON → Lean RRCShape constructor) ──────────────
|
||||
SHAPE_MAP = {
|
||||
|
|
@ -88,7 +88,7 @@ def lean_classify_label(eq_id: str, fn: str) -> str:
|
|||
"""Generate Lean expression for PIST label.
|
||||
|
||||
Checks prediction sources in order:
|
||||
1. PIST predictions (rrc_pist_predictions_278_v1.json)
|
||||
1. PIST predictions (rrc_pist_predictions_250_v1.json)
|
||||
2. arXiv predictions (rrc_arxiv_predictions_v1.json)
|
||||
3. OEIS predictions (rrc_oeis_predictions_v1.json)
|
||||
4. Fallback to matrix-hash lookup via classifyProxy/classifyExact
|
||||
|
|
@ -112,7 +112,7 @@ def load_predictions(path: Path) -> dict[str, dict]:
|
|||
|
||||
|
||||
ROOT = Path("/home/allaun/Research Stack")
|
||||
PIST_BY_ID = load_predictions(ROOT / "shared-data/rrc_pist_predictions_278_v1.json")
|
||||
PIST_BY_ID = load_predictions(ROOT / "shared-data/rrc_pist_predictions_250_v1.json")
|
||||
ARXIV_BY_ID = load_predictions(ROOT / "shared-data/rrc_arxiv_predictions_v1.json")
|
||||
OEIS_BY_ID = load_predictions(ROOT / "shared-data/rrc_oeis_predictions_v1.json")
|
||||
|
||||
|
|
@ -123,9 +123,9 @@ def main() -> None:
|
|||
print(f"Loaded {len(eqs)} equations from classifier receipt", file=sys.stderr)
|
||||
|
||||
lines: list[str] = []
|
||||
lines.append("-- Semantics.RRC.Corpus278 — AUTO-GENERATED by build_corpus278.py")
|
||||
lines.append("-- Semantics.RRC.Corpus250 — AUTO-GENERATED by build_corpus250.py")
|
||||
lines.append("-- DO NOT EDIT BY HAND. Regenerate with:")
|
||||
lines.append("-- python3 4-Infrastructure/shim/build_corpus278.py")
|
||||
lines.append("-- python3 4-Infrastructure/shim/build_corpus250.py")
|
||||
lines.append("--")
|
||||
lines.append("-- Python role: raw feature extraction + PIST predictions merge.")
|
||||
lines.append("-- Lean role: alignment gate (determineAlignment), receipt stamping,")
|
||||
|
|
@ -133,32 +133,32 @@ def main() -> None:
|
|||
lines.append("--")
|
||||
lines.append("-- Merge contract: pistProxyLabel/pistExactLabel are computed by")
|
||||
lines.append("-- Semantics.PIST.Classify.classifyProxy / classifyExact over the 8×8")
|
||||
lines.append("-- braid adjacency matrix from Semantics.PIST.Matrices278.pistMatrices278")
|
||||
lines.append("-- braid adjacency matrix from Semantics.PIST.Matrices250.pistMatrices250")
|
||||
lines.append("-- (keyed by invariant_receipt.object_id). v2 stubs return none;")
|
||||
lines.append("-- when the classifier surface is defined labels populate automatically.")
|
||||
lines.append("--")
|
||||
lines.append("-- Sources:")
|
||||
lines.append(f"-- classifier receipt: archive/experimental-shim-probes/rrc_equation_classifier_receipt.json")
|
||||
lines.append(f"-- predictions: shared-data/rrc_pist_predictions_278_v1.json")
|
||||
lines.append(f"-- predictions: shared-data/rrc_pist_predictions_250_v1.json")
|
||||
lines.append(f"-- Equation count: {len(eqs)}")
|
||||
lines.append("-- Labels computed by: Semantics.PIST.Classify.classifyProxy / classifyExact")
|
||||
lines.append("")
|
||||
lines.append("import Semantics.RRC.Emit")
|
||||
lines.append("import Semantics.PIST.Classify")
|
||||
lines.append("import Semantics.PIST.Matrices278")
|
||||
lines.append("import Semantics.PIST.Matrices250")
|
||||
lines.append("")
|
||||
lines.append("namespace Semantics.RRC.Corpus278")
|
||||
lines.append("namespace Semantics.RRC.Corpus250")
|
||||
lines.append("")
|
||||
lines.append("open Semantics.RRC.Emit")
|
||||
lines.append("open Semantics.RRCLogogramProjection")
|
||||
lines.append("open Semantics.ReceiptCore")
|
||||
lines.append("open Semantics.PIST.Matrices278")
|
||||
lines.append("open Semantics.PIST.Matrices250")
|
||||
lines.append("")
|
||||
lines.append("/-- Full 278-equation corpus from rrc_equation_classifier_receipt.json,")
|
||||
lines.append(" merged with PIST matrix predictions from rrc_pist_predictions_278_v1.json.")
|
||||
lines.append("/-- Full 250-equation corpus from rrc_equation_classifier_receipt.json,")
|
||||
lines.append(" merged with PIST matrix predictions from rrc_pist_predictions_250_v1.json.")
|
||||
lines.append(" Each row carries raw features only; the alignment gate in")
|
||||
lines.append(" Semantics.RRC.Emit.emitCorpus makes all admissibility decisions. -/")
|
||||
lines.append("def corpus278 : List FixtureRow := [")
|
||||
lines.append("def corpus250 : List FixtureRow := [")
|
||||
|
||||
row_strs: list[str] = []
|
||||
for eq in eqs:
|
||||
|
|
@ -210,7 +210,7 @@ def main() -> None:
|
|||
lines.append(",\n".join(row_strs))
|
||||
lines.append("]")
|
||||
lines.append("")
|
||||
lines.append("end Semantics.RRC.Corpus278")
|
||||
lines.append("end Semantics.RRC.Corpus250")
|
||||
lines.append("")
|
||||
|
||||
OUT_LEAN.write_text("\n".join(lines))
|
||||
|
|
@ -4,7 +4,7 @@
|
|||
# dependencies = []
|
||||
# ///
|
||||
"""
|
||||
Build Semantics/PIST/Matrices278.lean from rrc_pist_predictions_278_v1.json.
|
||||
Build Semantics/PIST/Matrices250.lean from rrc_pist_predictions_250_v1.json.
|
||||
|
||||
Python's role: read the predictions artifact, serialize each 8×8 matrix as a
|
||||
Lean Array (Array Int) literal, emit a Std.HashMap keyed by rrc_eq_<hex>.
|
||||
|
|
@ -13,18 +13,18 @@ Generated Lean file is consumed by Semantics.PIST.Classify (classifyProxy/
|
|||
classifyExact) when labels are computed in v2+.
|
||||
|
||||
Usage:
|
||||
python3 4-Infrastructure/shim/build_pist_matrices_278.py
|
||||
python3 4-Infrastructure/shim/build_pist_matrices_250.py
|
||||
|
||||
Dependencies:
|
||||
shared-data/rrc_pist_predictions_278_v1.json (pist_matrix_builder.py output)
|
||||
shared-data/rrc_pist_predictions_250_v1.json (pist_matrix_builder.py output)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
import json, sys
|
||||
from pathlib import Path
|
||||
|
||||
ROOT = Path("/home/allaun/Research Stack")
|
||||
PREDICTIONS_JSON = ROOT / "shared-data/rrc_pist_predictions_278_v1.json"
|
||||
OUT_LEAN = ROOT / "0-Core-Formalism/lean/Semantics/Semantics/PIST/Matrices278.lean"
|
||||
PREDICTIONS_JSON = ROOT / "shared-data/rrc_pist_predictions_250_v1.json"
|
||||
OUT_LEAN = ROOT / "0-Core-Formalism/lean/Semantics/Semantics/PIST/Matrices250.lean"
|
||||
|
||||
|
||||
def lean_str(s: str) -> str:
|
||||
|
|
@ -50,23 +50,23 @@ def main() -> int:
|
|||
print(f"Loaded {len(raw)} predictions from {PREDICTIONS_JSON}", file=sys.stderr)
|
||||
|
||||
lines: list[str] = []
|
||||
lines.append("-- Semantics.PIST.Matrices278 — AUTO-GENERATED by build_pist_matrices_278.py")
|
||||
lines.append("-- Semantics.PIST.Matrices250 — AUTO-GENERATED by build_pist_matrices_250.py")
|
||||
lines.append("-- DO NOT EDIT BY HAND. Regenerate with:")
|
||||
lines.append("-- python3 4-Infrastructure/shim/build_pist_matrices_278.py")
|
||||
lines.append("-- python3 4-Infrastructure/shim/build_pist_matrices_250.py")
|
||||
lines.append("--")
|
||||
lines.append("-- Source: shared-data/rrc_pist_predictions_278_v1.json")
|
||||
lines.append("-- Source: shared-data/rrc_pist_predictions_250_v1.json")
|
||||
lines.append("-- (generated by 4-Infrastructure/shim/pist_matrix_builder.py)")
|
||||
lines.append("--")
|
||||
lines.append("-- This file is consumed by Semantics.PIST.Classify (classifyProxy/")
|
||||
lines.append("-- classifyExact) at compile time to produce pistProxyLabel/")
|
||||
lines.append("-- pistExactLabel for each invariant equation_id.")
|
||||
lines.append("")
|
||||
lines.append("namespace Semantics.PIST.Matrices278")
|
||||
lines.append("namespace Semantics.PIST.Matrices250")
|
||||
lines.append("")
|
||||
lines.append("/-- 8×8 braid adjacency matrices keyed by invariant equation_id, stored as")
|
||||
lines.append(" an association list (key → matrix). 250 entries; linear lookup is fine.")
|
||||
lines.append(" Generated from rrc_pist_predictions_278_v1.json. -/")
|
||||
lines.append(f"def pistMatrices278 : List (String × Array (Array Int)) :=")
|
||||
lines.append(" Generated from rrc_pist_predictions_250_v1.json. -/")
|
||||
lines.append(f"def pistMatrices250 : List (String × Array (Array Int)) :=")
|
||||
lines.append(" [")
|
||||
|
||||
entry_strs: list[str] = []
|
||||
|
|
@ -84,9 +84,9 @@ def main() -> int:
|
|||
lines.append("")
|
||||
lines.append("/-- Look up an 8×8 matrix by invariant equation_id. -/")
|
||||
lines.append("def findMatrix (eqId : String) : Option (Array (Array Int)) :=")
|
||||
lines.append(" pistMatrices278.find? (fun (k, _) => k = eqId) |>.map (fun (_, v) => v)")
|
||||
lines.append(" pistMatrices250.find? (fun (k, _) => k = eqId) |>.map (fun (_, v) => v)")
|
||||
lines.append("")
|
||||
lines.append("end Semantics.PIST.Matrices278")
|
||||
lines.append("end Semantics.PIST.Matrices250")
|
||||
lines.append("")
|
||||
|
||||
OUT_LEAN.write_text("\n".join(lines))
|
||||
|
|
@ -116,10 +116,10 @@ def main() -> int:
|
|||
|
||||
args = parser.parse_args()
|
||||
|
||||
# Q16_16 parameters
|
||||
# Q16_16 parameters (SLOS-calibrated 2026-06-18)
|
||||
initial_energy = 1 * Q16 # 1.0
|
||||
nu_decay_factor = int(0.999 * Q16) # Slight viscosity decay per step
|
||||
advection_phase = int(0.05 * Q16) # Nonlinear advection rotation per step
|
||||
nu_decay_factor = int(0.9995 * Q16) # Viscosity decay per step (was 0.999)
|
||||
advection_phase = int(0.075 * Q16) # Advection rotation per step (was 0.05)
|
||||
|
||||
res = solve_burgers_0d(args.steps, initial_energy, nu_decay_factor, advection_phase)
|
||||
|
||||
|
|
|
|||
|
|
@ -4,16 +4,16 @@
|
|||
# dependencies = []
|
||||
# ///
|
||||
"""
|
||||
emit278_extract.py — run `lake build Semantics.AVMIsa.Emit` and capture the
|
||||
`#eval emitRrcCorpus278` output, writing it as emit278.json.
|
||||
emit250_extract.py — run `lake build Semantics.AVMIsa.Emit` and capture the
|
||||
`#eval emitRrcCorpus250` output, writing it as emit250.json.
|
||||
|
||||
Python role: subprocess + I/O only.
|
||||
Lean role: all alignment-gate, receipt-stamping, and JSON-emission logic.
|
||||
|
||||
Usage:
|
||||
python3 4-Infrastructure/shim/emit278_extract.py
|
||||
python3 4-Infrastructure/shim/emit278_extract.py --out /tmp/emit278.json
|
||||
python3 4-Infrastructure/shim/emit278_extract.py --validate-only
|
||||
python3 4-Infrastructure/shim/emit250_extract.py
|
||||
python3 4-Infrastructure/shim/emit250_extract.py --out /tmp/emit250.json
|
||||
python3 4-Infrastructure/shim/emit250_extract.py --validate-only
|
||||
"""
|
||||
from __future__ import annotations
|
||||
import argparse, json, re, subprocess, sys
|
||||
|
|
@ -21,13 +21,13 @@ from pathlib import Path
|
|||
|
||||
ROOT = Path("/home/allaun/Research Stack")
|
||||
LEAN_DIR = ROOT / "0-Core-Formalism/lean/Semantics"
|
||||
DEFAULT_OUT = ROOT / "shared-data/data/stack_solidification/emit278.json"
|
||||
DEFAULT_OUT = ROOT / "shared-data/data/stack_solidification/emit250.json"
|
||||
|
||||
# The #eval for emitRrcCorpus278 is in AVMIsa/Emit.lean — its info: line
|
||||
# will contain the string starting with {"schema":"avm_rrc_corpus278_v1",...}
|
||||
# The #eval for emitRrcCorpus250 is in AVMIsa/Emit.lean — its info: line
|
||||
# will contain the string starting with {"schema":"avm_rrc_corpus250_v1",...}
|
||||
# In the raw lake output the JSON string is Lean-repr-escaped, so quotes appear
|
||||
# as \" — we search for both forms.
|
||||
MARKER = 'avm_rrc_corpus278_v1'
|
||||
MARKER = 'avm_rrc_corpus250_v1'
|
||||
|
||||
|
||||
def build_and_capture() -> str:
|
||||
|
|
@ -74,7 +74,7 @@ def extract_json(info_line: str) -> str:
|
|||
|
||||
|
||||
def main() -> None:
|
||||
ap = argparse.ArgumentParser(description="Extract emit278.json from lake build output")
|
||||
ap = argparse.ArgumentParser(description="Extract emit250.json from lake build output")
|
||||
ap.add_argument("--out", default=str(DEFAULT_OUT), help="Output JSON path")
|
||||
ap.add_argument("--validate-only", action="store_true",
|
||||
help="Parse and validate JSON only; do not write file")
|
||||
|
|
@ -105,11 +105,11 @@ def main() -> None:
|
|||
len(rows_val.get("rows", [])) if isinstance(rows_val, dict) else -1
|
||||
print(f"rows in JSON : {row_count}", file=sys.stderr)
|
||||
|
||||
if schema != "avm_rrc_corpus278_v1":
|
||||
if schema != "avm_rrc_corpus250_v1":
|
||||
print(f"ERROR: unexpected schema '{schema}'", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
if total != 278 or row_count != 278:
|
||||
print(f"ERROR: expected 278 rows, got total={total}, rows={row_count}", file=sys.stderr)
|
||||
if total != 250 or row_count != 250:
|
||||
print(f"ERROR: expected 250 rows, got total={total}, rows={row_count}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
if args.validate_only:
|
||||
|
|
@ -574,7 +574,7 @@ def main():
|
|||
|
||||
print(f"\nTo certify candidates:")
|
||||
print(f" lake build Semantics.AVMIsa.Emit")
|
||||
print(f" python3 4-Infrastructure/shim/emit278_extract.py")
|
||||
print(f" python3 4-Infrastructure/shim/emit250_extract.py")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@ Builds token→strand adjacency matrices. This is a feature-extraction shim
|
|||
only — it produces no classifier output and no Lean spectral analysis.
|
||||
proxy_pred/exact_pred are left null for the Lean surface.
|
||||
|
||||
Output schema: rrc_pist_predictions_278_v1 (claim_boundary: matrix-only)
|
||||
Output schema: rrc_pist_predictions_250_v1 (claim_boundary: matrix-only)
|
||||
"""
|
||||
|
||||
import hashlib
|
||||
|
|
@ -23,7 +23,7 @@ RECEIPT_JSON = os.path.join(
|
|||
)
|
||||
OUTPUT_FILE = os.path.join(
|
||||
os.path.dirname(__file__), "../..",
|
||||
"shared-data/rrc_pist_predictions_278_v1.json",
|
||||
"shared-data/rrc_pist_predictions_250_v1.json",
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -288,7 +288,7 @@ def main() -> int:
|
|||
"consider tuning ρ.", flush=True)
|
||||
|
||||
artifact = {
|
||||
"schema": "rrc_pist_predictions_278_v1",
|
||||
"schema": "rrc_pist_predictions_250_v1",
|
||||
"claim_boundary": "matrix-only;hermite-kernel-added;no-classifier;no-lean-spectral",
|
||||
"matrix_schema": "token_strand_adjacency_8x8_v1",
|
||||
"hermite_kernel_schema": "mehler_kernel_8x8_v1_generalized_bilinear_generating_function",
|
||||
|
|
|
|||
|
|
@ -313,6 +313,64 @@ def main():
|
|||
"to_label": DIMENSION_DESCRIPTIONS.get(dim + 1, ""),
|
||||
})
|
||||
|
||||
# ── Edge type 7: Intrinsic kernel_internal (content nodes within same kernel) ──
|
||||
kernel_groups: dict[str, list[dict]] = defaultdict(list)
|
||||
for n in node_map.values():
|
||||
kernel_groups[n["kernel"]].append(n)
|
||||
for kernel, members in kernel_groups.items():
|
||||
if len(members) < 2:
|
||||
continue
|
||||
for i in range(len(members)):
|
||||
for j in range(i + 1, len(members)):
|
||||
if i * len(members) + j % 7 == 0: # ~14% density, deterministic
|
||||
add_edge(members[i]["id"], members[j]["id"], {
|
||||
"type": "kernel_internal",
|
||||
"kernel": kernel,
|
||||
"dimension": members[i].get("dimension"),
|
||||
})
|
||||
|
||||
# ── Edge type 8: kernel_hub (cross-kernel hub connections) ──
|
||||
hubs: dict[str, str] = {}
|
||||
for kernel, members in kernel_groups.items():
|
||||
hubs[kernel] = members[len(members) // 2]["id"]
|
||||
kernel_names = list(kernel_groups.keys())
|
||||
for i in range(len(kernel_names)):
|
||||
for j in range(i + 1, len(kernel_names)):
|
||||
add_edge(hubs[kernel_names[i]], hubs[kernel_names[j]], {
|
||||
"type": "kernel_hub",
|
||||
"from_kernel": kernel_names[i],
|
||||
"to_kernel": kernel_names[j],
|
||||
})
|
||||
|
||||
# ── Edge type 9: topic_overlap (label token overlap between content nodes) ──
|
||||
node_list = list(node_map.values())
|
||||
for i in range(len(node_list)):
|
||||
ni = node_list[i]
|
||||
ni_tokens = set(ni.get("label", "").lower().split())
|
||||
for j in range(i + 1, len(node_list)):
|
||||
nj = node_list[j]
|
||||
overlap = ni_tokens & set(nj.get("label", "").lower().split())
|
||||
if len(overlap) >= 2:
|
||||
add_edge(ni["id"], nj["id"], {
|
||||
"type": "topic_overlap",
|
||||
"overlap_count": len(overlap),
|
||||
"shared_terms": list(overlap)[:5],
|
||||
})
|
||||
|
||||
# ── Edge type 10: shared_paper fallback (unverified) ──
|
||||
live_share_count = sum(1 for e in edges if e["type"] == "shared_paper")
|
||||
if live_share_count == 0:
|
||||
for pid, nids in paper_node.items():
|
||||
for i in range(len(nids)):
|
||||
for j in range(i + 1, len(nids)):
|
||||
n1, n2 = nids[i], nids[j]
|
||||
if node_map[n1]["kernel"] != node_map[n2]["kernel"]:
|
||||
add_edge(n1, n2, {
|
||||
"type": "shared_paper",
|
||||
"paper_id": pid,
|
||||
"verified": False,
|
||||
})
|
||||
|
||||
# ── Build output ──
|
||||
manifold = {
|
||||
"schema": "domain_manifold_graph_v1",
|
||||
|
|
|
|||
|
|
@ -1030,7 +1030,7 @@ must hold byte-for-byte.
|
|||
See root `AGENTS.md` for:
|
||||
- **Post-Interaction Workflow** (mandatory 5-step session-end procedure)
|
||||
- **Programming Choice Flow** (Lean owns decisions; Python owns I/O)
|
||||
- **Compiler Surface Blessing** (RRC.Emit, AVMIsa.Emit, RRC.Corpus278 are the 3 blessed roots)
|
||||
- **Compiler Surface Blessing** (RRC.Emit, AVMIsa.Emit, RRC.Corpus250 are the 3 blessed roots)
|
||||
- **AVMIsa.Emit sole output boundary** — nothing outside AVMIsa.Emit may emit a top-level receipt JSON
|
||||
- **Do Not Sweep** rules (no broad `git add .`)
|
||||
- **Git Remote Hygiene**
|
||||
|
|
|
|||
|
|
@ -68,7 +68,7 @@ Receipts are emitted as nested JSON objects via `AVMIsa.Emit`. Example receipt f
|
|||
}
|
||||
```
|
||||
|
||||
The corpus receipt (`emit278.json`) uses 250 flat rows with explicit field names — no depth encoding.
|
||||
The corpus receipt (`emit250.json`) uses 250 flat rows with explicit field names — no depth encoding.
|
||||
|
||||
---
|
||||
|
||||
|
|
@ -389,9 +389,9 @@ Proof sketch (dot-depth version):
|
|||
|
||||
---
|
||||
|
||||
## 6. Concrete Corpus278 Example
|
||||
## 6. Concrete Corpus250 Example
|
||||
|
||||
Current JSON row (emit278.json):
|
||||
Current JSON row (emit250.json):
|
||||
```json
|
||||
{
|
||||
"equation_id": "rrc_eq_86ccde7bfd669b77",
|
||||
|
|
@ -405,7 +405,7 @@ Current JSON row (emit278.json):
|
|||
|
||||
Equivalent DP-RRC form:
|
||||
```
|
||||
; Corpus278 row as DP-Expr
|
||||
; Corpus250 row as DP-Expr
|
||||
.row
|
||||
..rrc_eq_86ccde7bfd669b77 ; equation_id
|
||||
..bandwidth_adjusted_threshold ; name
|
||||
|
|
@ -417,8 +417,8 @@ Equivalent DP-RRC form:
|
|||
|
||||
The full 250-row corpus:
|
||||
```
|
||||
; avm_rrc_corpus278_v1 in DP-RRC
|
||||
.corpus278
|
||||
; avm_rrc_corpus250_v1 in DP-RRC
|
||||
.corpus250
|
||||
;; Row 1
|
||||
..rrc_eq_86ccde7bfd669b77
|
||||
...bandwidth_adjusted_threshold
|
||||
|
|
@ -545,7 +545,7 @@ by
|
|||
|
||||
### 8.3 Integration into AVMIsa.Emit
|
||||
|
||||
Add a `dp_rrc_corpus278_v1` schema alongside the existing `avm_rrc_corpus278_v1`. The AVM canary check is the same; only the output format changes. The DP-Expr form can be emitted as a `#eval` string in the existing JSON bundle under a `"dp_expr"` key.
|
||||
Add a `dp_rrc_corpus250_v1` schema alongside the existing `avm_rrc_corpus250_v1`. The AVM canary check is the same; only the output format changes. The DP-Expr form can be emitted as a `#eval` string in the existing JSON bundle under a `"dp_expr"` key.
|
||||
|
||||
---
|
||||
|
||||
|
|
|
|||
|
|
@ -353,6 +353,31 @@ the structural mapping:
|
|||
|
||||
---
|
||||
|
||||
## Future Work: Azure Quantum One-Shot
|
||||
|
||||
Gemini-proposed quantum approaches, saved for planned Azure Quantum one-shot:
|
||||
|
||||
### A. QUBO/QAOA (Quantinuum H2 gate model)
|
||||
- Frame as search for time t minimizing a penalty function (penalize runners too close to origin or each other)
|
||||
- Map cost function → quantum Hamiltonian, ground state = maximal "loneliness"
|
||||
- QAOA/VQE on Quantinuum H2; uses existing Lean β₀ rising-edge circuit as cost oracle
|
||||
|
||||
### B. Analog Quantum Simulation (PASQAL neutral atoms)
|
||||
- Reformulate as view-obstruction / graph-coloring problem
|
||||
- Map graph vertices to physical atom arrangement, use Ising model dynamics
|
||||
- PASQAL atoms natively encode the S¹ adjacency geometry
|
||||
|
||||
### C. Quantum Phase Estimation (fault-tolerant, Shor-style)
|
||||
- Map runner speeds to qubit phase rotations
|
||||
- Use QPE to probe combined periodic state space for lonely phase configurations
|
||||
- Applies Diophantine approximation structure of the conjecture
|
||||
|
||||
### Implementation Plan
|
||||
- Target: Azure Quantum platform (Quantinuum H2 + PASQAL)
|
||||
- Timeline: One-shot experiment, requires cost-function synthesis from Lean `beta0Circular` / `scarRegion`
|
||||
- Pre-requisite: classical GPU simulation sweep to validate cost landscape
|
||||
- Shim: `4-Infrastructure/shim/lonely_runner_sim.py` can be extended as classical baseline
|
||||
|
||||
## References
|
||||
|
||||
1. Wills, J. M. (1967). "Zwei Sätze über inhomogene diophantische Approximation
|
||||
|
|
@ -364,3 +389,5 @@ the structural mapping:
|
|||
Internal project document, Research Stack.
|
||||
5. Bohm, A., et al. (2026). "Navier-Stokes Shadow Control Gap Map."
|
||||
`docs/famm/NAVIER_STOKES_SHADOW_CONTROL_GAP_MAP.md`, Research Stack.
|
||||
6. Farhi, E., Goldstone, J., Gutmann, S. (2014). "A Quantum Approximate
|
||||
Optimization Algorithm." *arXiv:1411.4028*.
|
||||
|
|
|
|||
16
AGENTS.md
16
AGENTS.md
|
|
@ -193,7 +193,7 @@ Build: <N> jobs, 0 errors (lake build)
|
|||
```
|
||||
|
||||
Types: `feat`, `fix`, `chore`, `docs`, `refactor`.
|
||||
Scope examples: `lean`, `rrc`, `avm-isa`, `infra`, `corpus278`.
|
||||
Scope examples: `lean`, `rrc`, `avm-isa`, `infra`, `corpus250`.
|
||||
|
||||
### 4. Check tree cleanliness
|
||||
|
||||
|
|
@ -378,7 +378,7 @@ These terms appear throughout all AGENTS.md files and the codebase:
|
|||
- **AVM** — Adaptive Virtual Machine. Universal bridge between math languages and
|
||||
Python bytecode. Core ISA is live in `Semantics.AVMIsa.*` (Types, Value, Instr,
|
||||
State, Step, Run). AVM is the **sole output boundary** for RRC receipts:
|
||||
`AVMIsa.Emit` stamps all top-level receipt JSON; `RRC.Emit` and `RRC.Corpus278`
|
||||
`AVMIsa.Emit` stamps all top-level receipt JSON; `RRC.Emit` and `RRC.Corpus250`
|
||||
feed it as classifier and raw-feature supplier respectively.
|
||||
- **enwik9** — the Hutter Prize 1GB Wikipedia XML corpus, used as the canonical
|
||||
end-to-end test vector for the hierarchical compressor.
|
||||
|
|
@ -478,10 +478,10 @@ Never "last wins".
|
|||
|
||||
### Prediction artifact (v1, matrix-only)
|
||||
|
||||
Generate: `shared-data/rrc_pist_predictions_278_v1.json`
|
||||
Generate: `shared-data/rrc_pist_predictions_250_v1.json`
|
||||
|
||||
Constraints:
|
||||
- `schema: "rrc_pist_predictions_278_v1"`
|
||||
- `schema: "rrc_pist_predictions_250_v1"`
|
||||
- `claim_boundary: "matrix-only;no-classifier;no-lean-spectral"`
|
||||
- `proxy_pred: null`, `exact_pred: null` (until a classifier surface is defined)
|
||||
- include:
|
||||
|
|
@ -501,11 +501,11 @@ Constraints:
|
|||
|
||||
```
|
||||
pist_matrix_builder.py
|
||||
→ writes rrc_pist_predictions_278_v1.json (dedup by invariant id)
|
||||
→ build_corpus278.py reads it and merges by equation_id = rrc_eq_<hex>
|
||||
→ regenerates Semantics/RRC/Corpus278.lean with pistProxyLabel/pistExactLabel
|
||||
→ writes rrc_pist_predictions_250_v1.json (dedup by invariant id)
|
||||
→ build_corpus250.py reads it and merges by equation_id = rrc_eq_<hex>
|
||||
→ regenerates Semantics/RRC/Corpus250.lean with pistProxyLabel/pistExactLabel
|
||||
populated when present
|
||||
→ emit278.json alignment gate becomes non-missing_prediction only when labels exist.
|
||||
→ emit250.json alignment gate becomes non-missing_prediction only when labels exist.
|
||||
```
|
||||
|
||||
### Required validations (every change)
|
||||
|
|
|
|||
|
|
@ -169,7 +169,7 @@ GCCL = Law Stack (what must be preserved)
|
|||
|
||||
| Path | Purpose |
|
||||
|------|---------|
|
||||
| `0-Core-Formalism/lean/Semantics/` | Lean 4 source (truth), FixedPoint, PIST, GWL, AVMR, FAMM, RRC.Emit, AVMIsa.Emit, RRC.Corpus278 |
|
||||
| `0-Core-Formalism/lean/Semantics/` | Lean 4 source (truth), FixedPoint, PIST, GWL, AVMR, FAMM, RRC.Emit, AVMIsa.Emit, RRC.Corpus250 |
|
||||
| `0-Core-Formalism/otom/` | One-Truth-Only-Model consolidated spec |
|
||||
| `0-Core-Formalism/core/` | Rust/Python extraction targets |
|
||||
| `1-Distributed-Systems/` | ENE mesh nodes, gossip, waveprobe |
|
||||
|
|
@ -193,7 +193,7 @@ import and receipt emission. Only three roots are blessed:
|
|||
|
||||
| Root | Role |
|
||||
|------|------|
|
||||
| `Semantics.RRC.Corpus278` | 278 raw FixtureRows — Python-supplied, Lean-gated; no decisions |
|
||||
| `Semantics.RRC.Corpus250` | 250 raw FixtureRows — Python-supplied, Lean-gated; no decisions |
|
||||
| `Semantics.RRC.Emit` | Alignment classifier (`missingPrediction` / `alignedExact` / etc.) |
|
||||
| `Semantics.AVMIsa.Emit` | **Sole output boundary** — AVM canaries must pass; stamps and emits all receipt JSON |
|
||||
|
||||
|
|
@ -201,7 +201,7 @@ import and receipt emission. Only three roots are blessed:
|
|||
The pipeline is:
|
||||
|
||||
```
|
||||
RRC.Corpus278 →(emitCorpus)→ RRC.Emit →(emitRrcCorpus278)→ AVMIsa.Emit → JSON receipt
|
||||
RRC.Corpus250 →(emitCorpus)→ RRC.Emit →(emitRrcCorpus250)→ AVMIsa.Emit → JSON receipt
|
||||
```
|
||||
|
||||
Build the narrow surface: `lake build Compiler` (3311 jobs, 0 errors, commit `8d158bf9`).
|
||||
|
|
|
|||
|
|
@ -131,13 +131,13 @@ PCIe FPGA = future math-hell router (VU9P-class)
|
|||
- `4-Infrastructure/shim/rrc_equation_classifier_curriculum.jsonl`
|
||||
- `4-Infrastructure/shim/rrc_equation_classifier_table.csv`
|
||||
- `docs/rrc_equation_classification.md`
|
||||
- `Semantics/RRC/Corpus278.lean` — 278 FixtureRows, Python-supplied, Lean-gated ✅
|
||||
- `Semantics/RRC/Corpus250.lean` — 250 FixtureRows, Python-supplied, Lean-gated ✅
|
||||
- `Semantics/RRC/Emit.lean` — alignment classifier (missingPrediction / alignedExact / etc.) ✅
|
||||
- `Semantics/AVMIsa/Emit.lean` — sole output boundary; stamps avm.rrc_corpus278.bundle ✅
|
||||
- `Semantics/AVMIsa/Emit.lean` — sole output boundary; stamps avm.rrc_corpus250.bundle ✅
|
||||
- **Owner:** Python shim / Lean bridge
|
||||
- **Status:** 🔄 IN_PROGRESS
|
||||
- **Result:** 278 equation surfaces projected; 29 CANDIDATE, 249 HOLD. Labels demoted to non-authoritative route hints.
|
||||
Lean Compiler surface (RRC.Corpus278 → RRC.Emit → AVMIsa.Emit) implemented and building:
|
||||
- **Result:** 250 equation surfaces projected; 29 CANDIDATE, 249 HOLD. Labels demoted to non-authoritative route hints.
|
||||
Lean Compiler surface (RRC.Corpus250 → RRC.Emit → AVMIsa.Emit) implemented and building:
|
||||
`lake build Compiler` → 3311 jobs, 0 errors (commit `8d158bf9`).
|
||||
- **Next action:** Add `scale_band_declared` witnesses and negative-control strength fields,
|
||||
then rerun the receipt and measure HOLD deltas.
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
Subproject commit 412841b6077f9ee64a14a5cad368555a3ecac2e7
|
||||
Subproject commit d232653c72ed7d8a7260500990324fb0d773020e
|
||||
Loading…
Add table
Reference in a new issue