Passes 3175–3186: curvature-routed inference and three-edit epoch

.github/workflows/w33_pass3175_3186_curvature_routed_inference.yml

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+name: Passes 3175-3186 Curvature-Routed Inference
+on:
+  workflow_dispatch:
+  pull_request:
+    paths:
+      - 'analysis/*3175*'
+      - 'analysis/*3177*'
+      - 'analysis/*3178*'
+      - 'analysis/*3179*'
+      - 'analysis/*3180*'
+      - 'analysis/*3181*'
+      - 'analysis/*3182*'
+      - 'rtl/*3175*'
+      - 'rtl/tb_w33_pass3175_3183_curvature_routed_runtime.sv'
+      - 'tests/test_bt3175_bt3186_curvature_routed_inference.py'
+      - 'tools/integrate_bt3175_bt3186.py'
+      - '.github/workflows/w33_pass3175_3186_curvature_routed_inference.yml'
+permissions:
+  contents: read
+jobs:
+  exact-rtl-papers:
+    runs-on: ubuntu-latest
+    timeout-minutes: 240
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+      - name: Install exact and digital toolchains
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y iverilog yosys fpga-icestorm nextpnr-ice40
+          python -m pip install numpy pytest
+      - uses: wtfjoke/setup-tectonic@v3
+      - name: Recompute all seven fronts
+        run: |
+          python analysis/bt3175_3176_curvature_conditioned_sensing.py
+          python analysis/bt3177_all194_information_frontier.py
+          python analysis/bt3178_three_edit_phase_epoch.py
+          python analysis/bt3179_m36_proof_envelope.py
+          python analysis/bt3180_routed_joint_utility.py
+          python analysis/bt3181_d4_triangle_wilson_flux.py
+          python analysis/bt3182_recursive_belief_virtualization.py
+          python analysis/bt3175_3186_curvature_routed_inference_summary.py
+      - name: Focused exact regressions
+        run: |
+          pytest -q tests/test_bt3175_bt3186_curvature_routed_inference.py
+          git diff --check
+      - name: Simulate protocol contracts
+        run: |
+          iverilog -g2012 -s tb_w33_pass3175_3183_curvature_routed_runtime -o /tmp/pass3183.vvp \
+            rtl/w33_pass3175_3183_curvature_routed_runtime.sv rtl/tb_w33_pass3175_3183_curvature_routed_runtime.sv
+          vvp /tmp/pass3183.vvp | tee pass3183_iverilog.log
+          grep -F 'PASS curvature, three-edit epoch, envelope, Wilson flux and routed utility' pass3183_iverilog.log
+      - name: Synthesize representative control tops
+        run: |
+          for top in w33_pass3175_curvature_accumulator w33_pass3178_three_edit_epoch_decoder w33_pass3181_d4_triangle_flux w33_pass3180_streamed_routed_utility; do
+            yosys -p "read_verilog -sv rtl/w33_pass3175_3183_curvature_routed_runtime.sv; hierarchy -top $top; synth_ice40 -top $top -json /tmp/$top.json; stat" | tee $top.yosys.log
+            nextpnr-ice40 --hx8k --package ct256 --pcf-allow-unconstrained --json /tmp/$top.json --asc /tmp/$top.asc |& tee $top.nextpnr.log
+          done
+      - name: Integrate front doors idempotently
+        run: |
+          python tools/integrate_bt3175_bt3186.py
+          sha256sum w33_paper.tex photonic_holonet.tex holonet_machine_blueprint.tex docs/index.html > /tmp/a
+          python tools/integrate_bt3175_bt3186.py
+          sha256sum w33_paper.tex photonic_holonet.tex holonet_machine_blueprint.tex docs/index.html > /tmp/b
+          diff -u /tmp/a /tmp/b
+      - name: Compile all three canonical papers
+        run: |
+          tectonic w33_paper.tex
+          tectonic photonic_holonet.tex
+          tectonic holonet_machine_blueprint.tex
+          test -s w33_paper.pdf && test -s photonic_holonet.pdf && test -s holonet_machine_blueprint.pdf
+      - uses: actions/upload-artifact@v4
+        with:
+          name: pass3175-3186-curvature-routed-evidence
+          path: |
+            data/PART_BT3175*.json
+            data/PART_BT3177*.json
+            data/PART_BT3178*.json
+            data/PART_BT3179*.json
+            data/PART_BT3180*.json
+            data/PART_BT3181*.json
+            data/PART_BT3182*.json
+            pass3183_iverilog.log
+            *.yosys.log
+            *.nextpnr.log
+            w33_paper.pdf
+            photonic_holonet.pdf
+            holonet_machine_blueprint.pdf

analysis/BT3175_BT3186_CLAIM_LEDGER.md

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+# Passes 3175–3186 claim ledger
+
+| Claim | Type | Status | Boundary |
+|---|---|---|---|
+| 48,826 hypotheses partition as 45,445 none, 1,725 flat, 1,656 curved | exact finite | source-observed | Uses frozen D4 hypothesis universe. |
+| Curvature-aware information dominates collapsed information | exact theorem | proved | Data processing / chain rule. |
+| Stress action changes 1/32; sparse operational changes 0/32 | exact model | source-observed | Explicit synthetic channel and seed only. |
+| All 194 larger universal ISAs receive information metrics | exact finite | source-observed | Uniform frames/opcodes, not physical bitrate. |
+| Six-objective information frontier has eight designs | exact finite | source-observed | Separate from full-group runtime frontier. |
+| Twelve length-seven markers correct any three edits | exact theorem | proved | Physical confusion rates absent. |
+| Radius-three ball is 3,667,012 per phase | exact combinatorics | source-observed | Analytic enumeration by received length. |
+| M36 envelope detects tampering | exact digital integrity | source-observed | Does not prove candidate physics. |
+| Negative Z0/Z1/Z2 object is validly sealed and rejected | exact fixture | source-observed | No accepted candidate asserted. |
+| Joint utility changes 8/64 actions | exact model | source-observed | Programmable synthetic coefficients. |
+| D4 triple flux census 223/120 and 106 orbits | exact finite | source-observed | Algebraic holonomy only. |
+| Level-six active path uses 312 bits versus 5,461,333,332 replicated bits | exact architecture | source-observed | One active path; concurrency excluded. |
+| RTL simulation/synthesis/place | digital evidence | pending | No observed area or timing. |
+| Canonical paper integration and PDFs | publication evidence | pending | No compiled-PDF claim. |
+| M36 exhaustive result and laboratory behavior | exhaustive/physical | absent | No no-go, candidate, heat, coherence or optical claim. |

analysis/BT3175_BT3186_curvature_routed_inference.md

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+# Passes 3175–3186 — curvature-routed inference
+
+## Executive result
+
+This packet executes five requested fronts and two independent outside-box fronts while preserving the Holonet manuscript boundaries between clock, route, address, support/readout, phase/execution and fail-closed M36 injection.
+
+## 3175–3176 — curvature as a Bayesian latent
+
+The 48,826 hypotheses split into 45,445 non-shared states, 1,725 shared-flat states and 1,656 shared-curved states. For the explicit three-symbol synthetic channel, the exact identity
+
+\[
+I(H;Y)=I(K;Y)+I(H;Y\mid K)
+\]
+
+shows that resolving flat versus curved interactions cannot lose information. In 32 stress posteriors it changes 1 action; the best-action gain ranges from 0.0126970093 to 0.0902425706 bits, mean 0.0355238394. Under the frozen sparse operational shared-pair mass 3.48484848e-5 it changes 0/32 actions and adds only 2.54e-6 to 6.75e-6 bits. Curvature is therefore real and potentially useful after postselection, but not yet a dominant operational control variable.
+
+## 3177 — exact information frontier over all 194 larger ISAs
+
+All 80 universal five-opcode and 114 universal six-opcode sets are recomputed. The six-objective frontier—maximize average, minimum and normalized dispatch information; minimize variance, collisions and decoder units—contains eight designs. Global extrema are:
+
+- maximum average: 2.4141403814 bits, four attainers;
+- maximum worst-frame capacity: 1.7924812504 bits, 22 attainers;
+- maximum normalized capacity: 0.9481541058, four attainers;
+- minimum variance: 0.0357531815, two attainers;
+- minimum collision probability: 1/9, four attainers.
+
+No single design owns all extrema; information-aware ISA selection is intrinsically vector-valued.
+
+## 3178 — optimal three-edit phase code
+
+Twelve payload-unused symbols label twelve constant markers \(M_p=u_p^7\). Their pairwise and payload distances are at least seven, which is optimal because correcting three adversarial insertions, deletions or substitutions requires \(d_{\min}\ge 2t+1=7\). For a received word of length \(m\) containing \(c\) copies of the marker symbol,
+
+\[
+d_L(u^7,y)=\max(7,m)-\min(7,c).
+\]
+
+The exact radius-three ball contains 3,667,012 traces per phase and 44,004,144 phase-labelled traces in total. The corrected marker carries phase directly; zero clean payload symbols are required afterward.
+
+## 3179 — proof-carrying M36 objects
+
+An M36 candidate envelope is canonical JSON with SHA-256 content addressing, shard/engine/source provenance, independent-certifier status and hashed witness slots. Accepted envelopes must carry projector, Pauli-spectrum and logical-frame hashes plus success, negativity, stabilizer-fidelity lower bound and error-series witnesses. The known Z0/Z1/Z2 negative control is sealed as rejected; a one-field mutation fails digest verification. This protects citation integrity but does not create an accepted candidate.
+
+## 3180 — routed joint utility
+
+The 23 measured triangles form a connected route graph of diameter two and degrees 14–18. The explicit programmable utility combines detector mutual information, curvature information, shortest-route distance, route multiplicity, ISA control capacity, runtime cost and epoch confidence. In 64 deterministic scenarios it changes the detector-only action 8 times; mode choices are fast6=45, low4=11 and current4=8. Modelled utility gain is 0 to 0.0892247164, mean 0.0345842444.
+
+## 3181 BONKERS — D4 triangle Wilson flux
+
+Define \(\Phi(a,b,c)=\kappa(a,b)\oplus\kappa(b,c)\oplus\kappa(c,a)\). Over all 343 ordered nonidentity triples, 223 have zero flux and 120 have unit flux. Simultaneous conjugation produces 106 orbits: one size-one flat orbit, 39 size-two flat orbits, 36 size-four flat orbits and 30 size-four curved orbits. Across 23 measured triangles this gives 5,129 flat-flux and 2,760 curved-flux local assignments. It is an algebraic holonomy syndrome, not physical spacetime curvature.
+
+## 3182 BONKERS — recursive belief virtualization
+
+A live context uses 52 bits: 9 causal, 36 edit-mask, 4 action, 1 valid and 2 curvature-state bits. At level \(n\), the Holonet has \(40^n\) leaves and \((40^n-1)/39\) W33 cores. Replicating every context costs \(52(40^n-1)/39\) bits, whereas one active root-to-leaf path costs only \(52n\) bits with routing diameter at most \(8n\). At level six this is 5,461,333,332 replicated bits versus 312 active-path bits, an exact architectural virtualization ratio of 17,504,273.5.
+
+## Evidence ladder
+
+Exact finite: D4 curvature/flux, 194-ISA information census, length-seven epoch theorem, envelope hashes, route graph and recursive counts. Exact for explicit models: sensing/action changes and joint utility. Source-complete pending digital observation: RTL contracts, tests, integrator and workflows. Absent: exhaustive M36 outcome, placed area/timing/power, PDFs and laboratory likelihoods or optics.

analysis/BT3175_BT3186_curvature_routed_inference_index_insert.html

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+<section id="bt3175-bt3186-curvature-routed-inference">
+<h2>Curvature-routed proof-carrying inference</h2>
+<p>The exact D4 posterior now exposes none/flat/curved interaction mass. Curvature changes 1/32 stress-policy actions but 0/32 under the frozen sparse operational prior, so it is retained as a typed diagnostic rather than advertised as a universal control gain.</p>
+<p>All 194 larger universal ISAs receive exact frame-local information metrics. Their six-objective Pareto frontier has eight members; mean capacity, worst-frame capacity, variance, collisions and decoder size select different symmetry families.</p>
+<p>Twelve length-seven phase markers correct any three insertions, deletions or substitutions. The exact radius-three ball contains 3,667,012 traces per phase and 44,004,144 phase-labelled traces in total.</p>
+<p>M36 candidates now require content-addressed provenance, independent certification and complete witness hashes. A rejected negative control is sealed and a one-field mutation fails verification.</p>
+<p>The routed controller combines detector information, route cost, epoch confidence, non-Abelian curvature and ISA channel capacity. Two outside-box results add a 106-orbit D4 triangle Wilson-flux census and an exact recursive belief-virtualization law.</p>
+</section>

analysis/BT3175_BT3186_curvature_routed_inference_insert.tex

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+\section{Curvature-routed proof-carrying inference}
+\label{sec:bt3175-bt3186}
+
+The non-Abelian posterior now carries a typed three-valued interaction latent: no shared measured triangle, shared-flat, or shared-curved.  The exact frozen census is $45{,}445+1{,}725+1{,}656=48{,}826$.  Resolving the curvature bit cannot reduce sensor information, since
+\[
+I(H;Y)=I(K;Y)+I(H;Y\mid K).
+\]
+For the explicit synthetic channel it changes one of 32 stress-policy actions, but zero of 32 actions under the frozen sparse operational prior.  The curvature variable is therefore retained as a diagnostic and postselection coordinate rather than promoted as an unqualified operational advantage.
+
+All 194 universal five- and six-opcode designs were independently enriched with frame-local control information.  The six-objective frontier has eight members: maximum mean information is $2.4141403814$ bits per dispatch, maximum worst-frame information is $1.7924812504$ bits, and minimum entropy variance is $0.0357531815$.  These extrema occur on different symmetry families, so the machine exposes the information vector rather than naming one universal scalar winner.
+
+The epoch layer advances from two-edit to three-edit correction.  Twelve payload-unused symbols define constant phase markers $M_p=u_p^7$.  Their mutual and payload distances are at least seven, the minimum possible for three-edit correction.  The exact radius-three ball has $3{,}667{,}012$ traces per phase and $44{,}004{,}144$ phase-labelled traces in total; the corrected marker itself carries phase and requires no clean payload symbols afterward.
+
+M36 outputs are now citation-safe objects.  A candidate envelope contains canonical generators, engine/shard/source provenance, independent certification, witness hashes and a SHA-256 digest.  Any mutation invalidates the envelope.  Accepted envelopes must carry projector, Pauli-spectrum and logical-frame hashes plus clean success, negativity, stabilizer-fidelity lower bound and error-series witnesses.  The existing $Z_0,Z_1,Z_2$ negative control is sealed and rejected; no accepted candidate is asserted.
+
+The action layer combines detector information, curvature gain, shortest-route distance and multiplicity, epoch confidence, ISA channel capacity and runtime cost with externally programmable coefficients.  In the frozen 64-scenario model it changes eight detector-only actions and selects fast-six, low-collision-four and current-four modes $45$, $11$ and $8$ times respectively.  This is a controlled-sensing model, not a physical calibration.
+
+Two further exact structures appear.  First, the triangle Wilson bit
+\[
+\Phi(a,b,c)=\kappa(a,b)\oplus\kappa(b,c)\oplus\kappa(c,a)
+\]
+is invariant under simultaneous $D_4$ conjugation.  Among $7^3=343$ ordered nonidentity triples, $223$ are flat and $120$ curved, forming $106$ conjugation orbits.  Second, a recursive level-$n$ Holonet can virtualize live belief: with a 52-bit context, global replication costs $52(40^n-1)/39$ bits while one active root-to-leaf execution path costs $52n$ bits and has routing diameter at most $8n$.  These are algebraic and architectural statements; neither is a laboratory field or memory measurement.

analysis/bt3175_3176_curvature_conditioned_sensing.py

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+#!/usr/bin/env python3
+"""Passes 3175-3176: curvature-aware Bayesian sensing.
+
+The full 48,826-state filter is partitioned into a typed latent:
+none / shared-flat / shared-curved. Results are exact for the stated
+synthetic channels and deterministic random seeds; they are not lab likelihoods.
+"""
+from __future__ import annotations
+import json, math
+from pathlib import Path
+import numpy as np
+ROOT=Path(__file__).resolve().parents[1]
+OUT=ROOT/'data/PART_BT3175_BT3176_CURVATURE_CONDITIONED_SENSING_results.json'
+ACTIONS=23; TOTAL_H=48826; NONE_H=45445; FLAT_H=1725; CURVED_H=1656
+CHANNEL=np.array([[.94,.03,.03],[.08,.86,.06],[.08,.06,.86]],float)
+def mi(pnone,pf,pc,a,aware):
+    probs=[pnone]; cond=[CHANNEL[0]]
+    for t in range(ACTIONS):
+        probs.extend((float(pf[t]),float(pc[t])))
+        cond.extend((CHANNEL[1] if t==a else CHANNEL[0],CHANNEL[2] if t==a else CHANNEL[0]))
+    p=np.array(probs);c=np.array(cond)
+    if not aware:c=np.column_stack((c[:,0],c[:,1]+c[:,2]))
+    py=p@c;ans=0.0
+    for ph,row in zip(p,c):
+        if ph<=0:continue
+        for y,q in enumerate(row):
+            if q>0 and py[y]>0:ans+=ph*q*math.log2(q/py[y])
+    return ans
+def one(rng,shared):
+    tri=rng.dirichlet(np.ones(ACTIONS)*.7);split=rng.beta(.7,.7,size=ACTIONS)
+    pf=shared*tri*split;pc=shared*tri*(1-split);pn=1-shared
+    aware=np.array([mi(pn,pf,pc,a,True) for a in range(ACTIONS)])
+    collapsed=np.array([mi(pn,pf,pc,a,False) for a in range(ACTIONS)])
+    assert np.all(aware+1e-14>=collapsed)
+    return {'aware_action':int(np.argmax(aware)),'collapsed_action':int(np.argmax(collapsed)),
+      'aware_best_bits':float(np.max(aware)),'collapsed_best_bits':float(np.max(collapsed)),
+      'best_gain_bits':float(np.max(aware)-np.max(collapsed))}
+def summarize(cases):
+    gains=[c['best_gain_bits'] for c in cases]
+    return {'cases':len(cases),'action_changes':sum(c['aware_action']!=c['collapsed_action'] for c in cases),
+      'minimum_best_action_gain_bits':min(gains),'mean_best_action_gain_bits':sum(gains)/len(gains),
+      'maximum_best_action_gain_bits':max(gains)}
+def main():
+    rng=np.random.default_rng(3175)
+    stress=[one(rng,float(rng.uniform(.15,.70))) for _ in range(32)]
+    operational_mass=.0005*(69/990);operational=[one(rng,operational_mass) for _ in range(32)]
+    out={'schema':'w33.pass3175_3176.curvature_conditioned_sensing.v1',
+      'hypothesis_partition':{'total':TOTAL_H,'none':NONE_H,'flat':FLAT_H,'curved':CURVED_H},
+      'channel_rows_true_none_flat_curved':CHANNEL.tolist(),
+      'identity':'I(H;Y)=I(K;Y)+I(H;Y|K); collapsing flat/curved cannot increase information',
+      'stress':summarize(stress),'operational_sparse_prior':{'total_shared_pair_mass':operational_mass,**summarize(operational)},
+      'stress_cases':stress,'operational_cases':operational,
+      'boundary':'Exact for the explicit synthetic channel and seeds. Curvature is an algebraic latent, not a measured optical field.'}
+    OUT.write_text(json.dumps(out,indent=2,sort_keys=True)+'\n');print(json.dumps({'stress':out['stress'],'operational':out['operational_sparse_prior']},sort_keys=True))
+if __name__=='__main__':main()