RQ2-P3: bridge-federated-pool mechanism instrument + synthetic tests + calibration gate
Build the funnelling-mechanism instrument for the RQ2-P3 follow-up: a new
`bridge-federated-pool` topology drawing each circuit's bridge from a finite
willing-bridge pool (size B) under Zipf willingness skew (alpha), so bridge
concentration genuinely varies as a manipulated IV. Defensive measurement only:
synthetic seeds, no engine, no traffic, no confirmatory record read.
- assembler.py: add `bridge-federated-pool` branch + zipf_weights/weighted_draw
helpers; existing lead `bridge-federated` branch left untouched and
bit-reproducible (fresh bridge per seed).
- battery.py: enumerate_rq2p3_cells() = B{2,4,8} x alpha{0,1,2} + anchor B=50,
alpha=0 (separate fn; frozen 6-cell lead lattice unmutated).
- analysis/rq2p3_calibration.py: DRY synthetic-only §7 calibration gate; no
confirmatory data read. confirm_load_rq2.py/confirm.py/stats.py unchanged.
- tests/test_sor_rq2p3_pool.py: 9 synthetic tests (helpers + pool reuse/variance
+ lead branch reproducibility).
Calibration gate RAN: items 3 (monotonicity) & 4 (entropy) PASS; items 1 & 2 do
NOT match their naive-funnel wording because the ratified posterior yields a MIX
(rho>0 across the whole sweep incl anchor rho=+0.838; B=1 -> H=2.54 bits HIGH) --
the note-unique-bridge-artifact.md prediction, surfaced early. HARD HOLD: no
confirmatory battery, no prereg freeze; NEEDS-OPERATOR banner raised for the §7
item-1/2 re-word decision. Lead prereg SHA f22331a72e... untouched; worktree-only.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -1,5 +1,18 @@
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# OVERSEER-STATUS — sor-consent build agent
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# OVERSEER-STATUS — sor-consent build agent
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> **NEEDS-OPERATOR (2026-07-21, RQ2-P3 mechanism instrument):** the `bridge-federated-pool`
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> instrument is BUILT + synthetic-tested (9 tests) + the §7 calibration gate was RUN. Items **3
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> (monotonicity) and 4 (entropy) PASS**; items **1 and 2 do NOT hold as their naive-funnel text is
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> worded** — because the *ratified* posterior mechanically yields a **MIX** (ρ>0), not the naive
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> funnel. Item-1 anchor B=50,α=0 gives ρ=**+0.838** (stdev 0.0198), NOT the ρ-undefined zero-variance
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> degeneracy §7 expected; item-2 B=1 gives concentration c=1.0 (✓) but H=**2.54 bits HIGH** vs the
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> fresh-bridge reference 0.0 bits, contradicting the "low H" gloss. Every ρ across the whole
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> B∈{2,4,8}×α∈{0,1,2} sweep is ≥0 (0.00→0.838): a robust mix everywhere. This is exactly
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> `docs/note-unique-bridge-artifact.md`'s prediction, surfaced early at calibration — NOT an
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> instrument bug. **STOPPED per rail:** no confirmatory RQ2-P3 battery, no prereg freeze. Operator
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> must decide: re-word `rq2p3-mechanism-prereg.md` §7 gate items 1–2 (naive→mechanical) before
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> freezing, or rule otherwise. Lead prereg SHA f22331a72e… UNTOUCHED; worktree-only.
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RQ2 RATIFIED (operator Andre, 2026-07-20, while blind) — observation-consistent-set + uniform-mass per-circuit posterior; docs/stage-05-rq2-posterior-clarification.md flipped PROPOSED→RATIFIED. Offline loader built + synthetic-tested. BLIND HOLD REMAINS: no real RQ2 result until the battery completes.
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RQ2 RATIFIED (operator Andre, 2026-07-20, while blind) — observation-consistent-set + uniform-mass per-circuit posterior; docs/stage-05-rq2-posterior-clarification.md flipped PROPOSED→RATIFIED. Offline loader built + synthetic-tested. BLIND HOLD REMAINS: no real RQ2 result until the battery completes.
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@@ -66,3 +79,6 @@ RQ2 RATIFIED (operator Andre, 2026-07-20, while blind) — observation-consisten
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- 2026-07-20 SS5 ADVERSARIAL REVIEW DONE + committed: docs/stage-08-adversarial-review.md — self red-team of the filled paper vs stage06-results.json (no new stat, no raw-data touch, prereg untouched). PASS on: number fidelity (every abstract/§5 figure matches JSON to precision), Holm arithmetic (7,6,5,4; only RQ1-P1+RQ2-P1 survive), spin/over-claim (no-leak framing, honest-negative equal-prominence, lab-scope disclaimers), blinding integrity (§5-6 filled once post-seal), method-substitution (bit-faithful --verify).
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- 2026-07-20 SS5 ADVERSARIAL REVIEW DONE + committed: docs/stage-08-adversarial-review.md — self red-team of the filled paper vs stage06-results.json (no new stat, no raw-data touch, prereg untouched). PASS on: number fidelity (every abstract/§5 figure matches JSON to precision), Holm arithmetic (7,6,5,4; only RQ1-P1+RQ2-P1 survive), spin/over-claim (no-leak framing, honest-negative equal-prominence, lab-scope disclaimers), blinding integrity (§5-6 filled once post-seal), method-substitution (bit-faithful --verify).
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- 1 DEFECT FOUND + FIXED (prose only, ZERO numbers changed): RQ1-P1's below-chance AUC was wrongly attributed to "the bridge padding stream flattening" — but assembler.py sets padding_applied=(bridge=="on+padding"), so the no-pad RQ1-P1 arm carries NO cover stream. Corrected docs/stage-06-analysis.md + paper §5.2/§6 to state it's an unexplained pooled-correlator artifact, explicitly NOT padding. Point/CI/gate/Holm untouched.
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- 1 DEFECT FOUND + FIXED (prose only, ZERO numbers changed): RQ1-P1's below-chance AUC was wrongly attributed to "the bridge padding stream flattening" — but assembler.py sets padding_applied=(bridge=="on+padding"), so the no-pad RQ1-P1 arm carries NO cover stream. Corrected docs/stage-06-analysis.md + paper §5.2/§6 to state it's an unexplained pooled-correlator artifact, explicitly NOT padding. Point/CI/gate/Holm untouched.
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- STEPPING STONES COMPLETE: SS1 executor ✅ SS2 battery+freeze ✅ SS3 §6 pass ✅ SS4 paper fill ✅ SS5 red-team ✅. Honest double-null/negative lead paper ready for operator review. prereg SHA INTACT; worktree-only feat/sor-consent-relay.
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- STEPPING STONES COMPLETE: SS1 executor ✅ SS2 battery+freeze ✅ SS3 §6 pass ✅ SS4 paper fill ✅ SS5 red-team ✅. Honest double-null/negative lead paper ready for operator review. prereg SHA INTACT; worktree-only feat/sor-consent-relay.
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- 2026-07-21 RQ2-P3 MECHANISM INSTRUMENT BUILT + committed: assembler.py `bridge-federated-pool` topology (finite willing-bridge pool size B under Zipf willingness skew α; per-circuit draw idx=weighted_draw(sha256("sor-bridge-pool|{seed}"), zipf_weights(B,α)) → bridge#{idx:02d}) + helpers `zipf_weights`/`weighted_draw`; existing lead `bridge-federated` branch UNTOUCHED (still fresh-bridge-per-seed, bit-reproducible). battery.enumerate_rq2p3_cells() = B∈{2,4,8}×α∈{0,1,2} + anchor B=50,α=0, tagged RQ2P3 (SEPARATE fn; frozen 6-cell lattice unmutated). analysis/rq2p3_calibration.py = DRY synthetic-only §7 gate (no confirmatory record read). confirm_load_rq2.py/confirm.py/stats.py UNCHANGED.
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- CALIBRATION GATE RAN (§7, DRY): item3 monotonicity PASS (top-3 conc ↓ in B, ↑ in α), item4 entropy PASS (plug-in=log2N exact). item1 + item2 DO NOT match naive wording → MIX not funnel (see top-of-file NEEDS-OPERATOR): anchor ρ=+0.838, B=1 H=2.54 bits HIGH, all 10 sweep ρ≥0. Surfaced, not reconciled. Tests: tests/test_sor_rq2p3_pool.py 9 passed; full SOR suite 185 passed (lead bridge-federated fingerprint reproducible — no regression).
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- HARD HOLD: no RQ2-P3 confirmatory battery, no `rq2p3-mechanism-prereg.md` freeze (§10 block still empty) — operator-gated on the item-1/2 re-word decision. Lead prereg SHA f22331a72e… INTACT; containment intact (synthetic-only, no engine/traffic); worktree-only. NEXT (operator-gated): RQ3 executor wiring, only after this ruling.
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@@ -0,0 +1,175 @@
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"""RQ2-P3 mechanism-instrument calibration gate (`rq2p3-mechanism-prereg.md` §7).
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DRY, SYNTHETIC-ONLY calibration of the new ``bridge-federated-pool`` topology: it
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assembles circuits from harness-generated per-circuit seeds (NOT a confirmatory data
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dir), then reports the four §7 gate items. **No confirmatory record is read** — this
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is the same blind-safe discipline as the lead-paper loaders; the confirmatory battery
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stays HARD-HELD until the prereg is frozen.
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Gate items (§7):
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1. Reproduce the lead degeneracy — ``B=50, alpha=0`` → ``c_i`` ≈ 1/C, near-constant,
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Spearman ρ inconclusive.
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2. Extreme ``B=1`` — all circuits share one bridge → ``c=1.0`` (a degenerate
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concentration extreme). NOTE: under the RATIFIED posterior a fully-shared bridge
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*maximizes* the observation-consistent anonymity set, so realized H comes out
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HIGH, not low — the mechanical "mix" the study exists to test. This is surfaced,
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not silently reconciled with the naive "low H" gloss.
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3. Monotonicity — mean top-3 concentration decreases in B and increases in alpha.
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4. Entropy calibration (inherited) — plug-in entropy of N equiprobable senders is
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exactly log2(N); Miller–Madow adds only the documented finite-N bias term.
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"""
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from __future__ import annotations
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import hashlib
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import json
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import math
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import statistics
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import sys
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from typing import Dict, List
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from cmd_chat.sor.analysis.confirm_load_rq2 import (
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bridge_concentration,
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per_circuit_entropy,
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top_k_bridge_concentration,
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)
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from cmd_chat.sor.analysis.stats import miller_madow_entropy_bits, spearman
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from cmd_chat.sor.assembler import assemble
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from cmd_chat.sor.battery import Cell, derive_seed, enumerate_rq2p3_cells
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R_DRY = 30 # runs/cell for the dry calibration (matches the prereg §6 R)
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C_DRY = 50 # circuits/run (matches C)
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def _run_circuit_seeds(cell_id: str, run_index: int, c: int = C_DRY) -> List[int]:
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"""Harness-side per-circuit seeds for the DRY pass (the confirmatory executor
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persists real per_circuit_seeds; this is calibration only). Deterministic from
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the frozen per-run seed rule so the calibration is reproducible."""
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run_seed = derive_seed(cell_id, run_index)
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return [int.from_bytes(hashlib.sha256(f"{run_seed}|circ|{j}".encode()).digest()[:8], "big")
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for j in range(c)]
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def _assemble_run(cell: Cell, run_index: int, c: int = C_DRY):
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return [assemble(cell, s) for s in _run_circuit_seeds(cell.cell_id, run_index, c)]
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def _pool_cell(b: int, alpha: float) -> Cell:
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return Cell("RQ2P3", f"RQ2P3/dry/B={b}/alpha={alpha}",
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{"bridge": "off", "topology": "bridge-federated-pool",
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"selector": "static", "pool_B": str(b), "pool_alpha": str(alpha)}, False)
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def cell_report(cell: Cell, r: int = R_DRY, c: int = C_DRY) -> Dict:
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"""Per-cell dry report: mean top-3 concentration over runs, pooled per-circuit
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(c_i, H_i) Spearman ρ, and the concentration spread."""
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per_run_top3: List[float] = []
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per_run_mean_h: List[float] = []
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conc_all: List[float] = []
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h_all: List[float] = []
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for ri in range(r):
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specs = _assemble_run(cell, ri, c)
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per_run_top3.append(top_k_bridge_concentration(specs, k=3))
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ent = per_circuit_entropy(specs)
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per_run_mean_h.append(statistics.fmean(ent))
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for ci, hi in zip(bridge_concentration(specs), ent):
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if ci is not None:
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conc_all.append(ci)
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h_all.append(hi)
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b = int(cell.factors["pool_B"])
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alpha = float(cell.factors["pool_alpha"])
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return {
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"B": b,
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"alpha": alpha,
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"mean_top3_concentration": statistics.fmean(per_run_top3),
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"concentration_stdev": statistics.pstdev(conc_all) if conc_all else 0.0,
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"mean_entropy_bits": statistics.fmean(per_run_mean_h),
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"spearman_rho_conc_vs_H": spearman(conc_all, h_all),
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"n_bridged_circuits": len(conc_all),
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}
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def calibration_gate(r: int = R_DRY, c: int = C_DRY) -> Dict:
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"""Run all four §7 gate items on the DRY pass and return a report dict."""
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sweep = [cr for cr in (cell_report(cell, r, c) for cell in enumerate_rq2p3_cells())]
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grid = {(cr["B"], cr["alpha"]): cr for cr in sweep}
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# Item 1 — anchor B=50, alpha=0 reproduces the lead degeneracy.
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anchor = grid[(50, 0.0)]
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item1_pass = anchor["concentration_stdev"] < 1e-3 and abs(anchor["spearman_rho_conc_vs_H"]) < 0.05
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# Item 2 — extreme B=1: all circuits share one bridge (degenerate concentration).
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ext = cell_report(_pool_cell(1, 0.0), r, c)
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lead_like = cell_report(_pool_cell(1_000_000, 0.0), r, c) # huge pool ≈ fresh bridge/circuit
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item2_conc_ok = abs(ext["mean_top3_concentration"] - 1.0) < 1e-9
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# The naive gate text says "low H"; the ratified posterior yields HIGH H. Surface it.
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item2_entropy_direction = "HIGH (mechanical mix)" if ext["mean_entropy_bits"] > lead_like["mean_entropy_bits"] else "low"
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item2_matches_naive_low_H = ext["mean_entropy_bits"] < lead_like["mean_entropy_bits"]
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# Item 3 — monotonicity: mean top-3 concentration decreasing in B, increasing in alpha.
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dec_in_B = all(
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grid[(2, a)]["mean_top3_concentration"] >= grid[(4, a)]["mean_top3_concentration"] >= grid[(8, a)]["mean_top3_concentration"]
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for a in (0.0, 1.0, 2.0)
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)
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inc_in_alpha = all(
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grid[(b, 0.0)]["mean_top3_concentration"] <= grid[(b, 1.0)]["mean_top3_concentration"] <= grid[(b, 2.0)]["mean_top3_concentration"]
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for b in (2, 4, 8)
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)
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item3_pass = dec_in_B and inc_in_alpha
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# Item 4 — entropy calibration (inherited): plug-in H of N equiprobable = log2(N) exactly.
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entropy_checks = []
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item4_pass = True
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for n in (2, 4, 8, 16, 50):
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mm = miller_madow_entropy_bits([1] * n)
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bias = (n - 1) / (2.0 * n * math.log(2.0))
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plugin = mm - bias
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ok = abs(plugin - math.log2(n)) < 1e-9
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item4_pass = item4_pass and ok
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entropy_checks.append({"N": n, "plugin_bits": plugin, "log2N": math.log2(n),
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"miller_madow_bits": mm, "plugin_equals_log2N": ok})
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return {
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"schema": "sor-rq2p3-calibration/1",
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"dry_only": True,
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"no_confirmatory_data_read": True,
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"R": r, "C": c,
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"sweep": sweep,
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"gate": {
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"item1_reproduce_lead_degeneracy": {
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"anchor_B50_alpha0": anchor,
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"pass": item1_pass,
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},
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"item2_extreme_B1": {
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"mean_top3_concentration": ext["mean_top3_concentration"],
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"mean_entropy_bits": ext["mean_entropy_bits"],
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"fresh_bridge_reference_mean_entropy_bits": lead_like["mean_entropy_bits"],
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"concentration_degenerate_c_eq_1": item2_conc_ok,
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"entropy_direction_vs_naive": item2_entropy_direction,
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"matches_naive_low_H_expectation": item2_matches_naive_low_H,
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"NEEDS_OPERATOR": not item2_matches_naive_low_H,
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"note": (
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"Concentration extreme is as specified (c=1.0). But the ratified "
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"posterior makes a fully-shared bridge MAXIMIZE the anonymity set, so "
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"realized H is HIGH, contradicting the §7 gate-item-2 'low H' gloss. "
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"This is exactly the mechanical 'mix' (ρ>0) the study exists to test "
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"(see note-unique-bridge-artifact.md), surfaced early at calibration. "
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"Not silently reconciled: flagged for the operator's freeze decision."
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),
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},
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"item3_monotonicity": {
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"decreasing_in_B": dec_in_B,
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"increasing_in_alpha": inc_in_alpha,
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"pass": item3_pass,
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},
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"item4_entropy_calibration": {
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"checks": entropy_checks,
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"pass": item4_pass,
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},
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},
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}
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if __name__ == "__main__":
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print(json.dumps(calibration_gate(), indent=2, sort_keys=True))
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sys.exit(0)
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@@ -132,6 +132,36 @@ def _bridge_label(seed: int) -> str:
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return f"bridge#{hashlib.sha256(f'sor-bridge|{seed}'.encode()).hexdigest()[:8]}"
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return f"bridge#{hashlib.sha256(f'sor-bridge|{seed}'.encode()).hexdigest()[:8]}"
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def zipf_weights(pool_size: int, alpha: float) -> List[float]:
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"""Deterministic Zipf willingness weights over a finite willing-bridge POOL of
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``pool_size`` bridges: rank ``r`` (1..B) gets mass ∝ ``1/r**alpha``, normalized to
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sum 1. ``alpha = 0`` → uniform willingness; larger ``alpha`` → heavier skew toward
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the most-willing bridges (higher realized concentration). Pure function of
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``(pool_size, alpha)`` — both cell-level factors — so the willingness profile is
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fixed within a run (RQ2-P3 mechanism prereg §3)."""
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if pool_size < 1:
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raise ValueError(f"pool_size must be >= 1, got {pool_size}")
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raw = [1.0 / (r ** alpha) for r in range(1, pool_size + 1)]
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total = sum(raw)
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return [w / total for w in raw]
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def weighted_draw(digest_hex: str, weights: List[float]) -> int:
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"""Deterministic index in ``[0, len(weights))`` by CDF inversion of a SHA-256
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hex digest: the first 8 bytes map to ``u ∈ [0, 1)`` and we return the first bin
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whose cumulative weight exceeds ``u``. Deterministic from ``digest_hex`` (a
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per-circuit hash), so a circuit's willing bridge is reproducible from its seed."""
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if not weights:
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raise ValueError("weights must be non-empty")
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u = int(digest_hex[:16], 16) / float(1 << 64)
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cum = 0.0
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for i, w in enumerate(weights):
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cum += w
|
||||||
|
if u < cum:
|
||||||
|
return i
|
||||||
|
return len(weights) - 1
|
||||||
|
|
||||||
|
|
||||||
def _house_nodes(seed: int, pool: int, take: int, house: str, salt: int = 0) -> List[str]:
|
def _house_nodes(seed: int, pool: int, take: int, house: str, salt: int = 0) -> List[str]:
|
||||||
idx = select_path(SorRng(seed ^ salt), pool, take)
|
idx = select_path(SorRng(seed ^ salt), pool, take)
|
||||||
return [f"{house}#{i}" for i in idx]
|
return [f"{house}#{i}" for i in idx]
|
||||||
@@ -201,6 +231,27 @@ def assemble(
|
|||||||
]
|
]
|
||||||
houses = (HOUSES[0], HOUSES[1])
|
houses = (HOUSES[0], HOUSES[1])
|
||||||
bridge_present = True
|
bridge_present = True
|
||||||
|
elif topo == "bridge-federated-pool":
|
||||||
|
# RQ2-P3 mechanism instrument (rq2p3-mechanism-prereg.md §3): identical
|
||||||
|
# to bridge-federated EXCEPT the willing bridge is drawn from a FINITE
|
||||||
|
# shared pool of size B under a fixed Zipf willingness (skew alpha), so
|
||||||
|
# circuits genuinely REUSE bridges and top-3 concentration varies. The
|
||||||
|
# existing bridge-federated branch above is left untouched (lead cells
|
||||||
|
# stay bit-reproducible).
|
||||||
|
pool_b = int(cell.factors["pool_B"])
|
||||||
|
pool_alpha = float(cell.factors["pool_alpha"])
|
||||||
|
a = _house_nodes(seed, house_size, 1, HOUSES[0], salt=0)[0]
|
||||||
|
b = _house_nodes(seed, house_size, 1, HOUSES[1], salt=0xB)[0]
|
||||||
|
weights = zipf_weights(pool_b, pool_alpha)
|
||||||
|
digest = hashlib.sha256(f"sor-bridge-pool|{seed}".encode()).hexdigest()
|
||||||
|
idx = weighted_draw(digest, weights)
|
||||||
|
hop_specs = [
|
||||||
|
HopSpec(0, "entry", HOUSES[0], a, False),
|
||||||
|
HopSpec(1, "bridge", "bridge", f"bridge#{idx:02d}", True),
|
||||||
|
HopSpec(2, "exit", HOUSES[1], b, False),
|
||||||
|
]
|
||||||
|
houses = (HOUSES[0], HOUSES[1])
|
||||||
|
bridge_present = True
|
||||||
elif topo == "directory-federated":
|
elif topo == "directory-federated":
|
||||||
directory = _build_directory(seed, house_size, n_houses)
|
directory = _build_directory(seed, house_size, n_houses)
|
||||||
path = directory.select_federated_path(seed, hops=hops, min_houses=2)
|
path = directory.select_federated_path(seed, hops=hops, min_houses=2)
|
||||||
@@ -217,7 +268,7 @@ def assemble(
|
|||||||
matched_n=matched_n, houses=houses, hops=tuple(hop_specs),
|
matched_n=matched_n, houses=houses, hops=tuple(hop_specs),
|
||||||
)
|
)
|
||||||
# Federated cells must genuinely span ≥ 2 houses (split-knowledge, RQ2).
|
# Federated cells must genuinely span ≥ 2 houses (split-knowledge, RQ2).
|
||||||
if topo in ("bridge-federated", "directory-federated") and spec.span_houses() < 2:
|
if topo in ("bridge-federated", "bridge-federated-pool", "directory-federated") and spec.span_houses() < 2:
|
||||||
raise ValueError(f"assembler: {cell.cell_id} failed the >=2-house span")
|
raise ValueError(f"assembler: {cell.cell_id} failed the >=2-house span")
|
||||||
return spec
|
return spec
|
||||||
|
|
||||||
|
|||||||
@@ -92,6 +92,40 @@ def enumerate_cells() -> List[Cell]:
|
|||||||
return cells
|
return cells
|
||||||
|
|
||||||
|
|
||||||
|
def enumerate_rq2p3_cells() -> List[Cell]:
|
||||||
|
"""The RQ2-P3 funnelling-mechanism sweep cells (`rq2p3-mechanism-prereg.md` §4),
|
||||||
|
kept **separate** from the frozen lead lattice: `enumerate_cells()` above is left
|
||||||
|
byte-identical so every lead-pipeline caller (`plan_runs`, `battery_schedule`,
|
||||||
|
`assembler_dry_check`, `collect_rq2_p1_arms`) stays bit-reproducible.
|
||||||
|
|
||||||
|
These use the new `bridge-federated-pool` topology (finite willing-bridge pool of
|
||||||
|
size ``B`` under a Zipf willingness skew ``alpha``) so concentration genuinely
|
||||||
|
varies. Tagged ``rq = "RQ2P3"`` so they are distinct from the frozen RQ1/RQ2
|
||||||
|
cells and are skipped by the lead RQ2 collectors (which filter ``rq == "RQ2"``).
|
||||||
|
|
||||||
|
9 sweep cells: ``B ∈ {2,4,8} × alpha ∈ {0, 1.0, 2.0}``, plus the ``B=50, alpha=0``
|
||||||
|
**calibration anchor** that reproduces the lead RQ2-P3 degeneracy (§7 gate item 1).
|
||||||
|
"""
|
||||||
|
cells: List[Cell] = []
|
||||||
|
for b in (2, 4, 8):
|
||||||
|
for alpha in (0.0, 1.0, 2.0):
|
||||||
|
cells.append(Cell(
|
||||||
|
"RQ2P3",
|
||||||
|
f"RQ2P3/topo=bridge-federated-pool/selector=static/B={b}/alpha={alpha}",
|
||||||
|
{"bridge": "off", "topology": "bridge-federated-pool",
|
||||||
|
"selector": "static", "pool_B": str(b), "pool_alpha": str(alpha)},
|
||||||
|
False,
|
||||||
|
))
|
||||||
|
cells.append(Cell(
|
||||||
|
"RQ2P3",
|
||||||
|
"RQ2P3/topo=bridge-federated-pool/selector=static/B=50/alpha=0.0",
|
||||||
|
{"bridge": "off", "topology": "bridge-federated-pool",
|
||||||
|
"selector": "static", "pool_B": "50", "pool_alpha": "0.0"},
|
||||||
|
False,
|
||||||
|
))
|
||||||
|
return cells
|
||||||
|
|
||||||
|
|
||||||
def declared_na_cells() -> List[Cell]:
|
def declared_na_cells() -> List[Cell]:
|
||||||
"""N/A cells declared at the design (not run, not dropped ad hoc) — padding is
|
"""N/A cells declared at the design (not run, not dropped ad hoc) — padding is
|
||||||
only defined for bridge-on, so bridge-off+padding is N/A (§2)."""
|
only defined for bridge-on, so bridge-off+padding is N/A (§2)."""
|
||||||
|
|||||||
@@ -0,0 +1,107 @@
|
|||||||
|
"""RQ2-P3 mechanism instrument — the willing-bridge POOL topology, on SYNTHETIC
|
||||||
|
seeds ONLY (`rq2p3-mechanism-prereg.md` §3). No confirmatory record is read.
|
||||||
|
|
||||||
|
Pins: (a) the pool helpers `zipf_weights` / `weighted_draw` are deterministic and
|
||||||
|
well-formed; (b) the new `bridge-federated-pool` branch draws from a finite pool so
|
||||||
|
circuits genuinely REUSE bridges (label collisions → concentration variance), while
|
||||||
|
still spanning ≥2 houses and staying isolation-gated; (c) the existing lead
|
||||||
|
`bridge-federated` branch is left bit-reproducible (fresh bridge per seed, unchanged).
|
||||||
|
"""
|
||||||
|
|
||||||
|
import hashlib
|
||||||
|
|
||||||
|
from cmd_chat.sor.analysis.confirm_load_rq2 import bridge_concentration, bridge_label
|
||||||
|
from cmd_chat.sor.assembler import assemble, weighted_draw, zipf_weights
|
||||||
|
from cmd_chat.sor.battery import Cell, derive_seed
|
||||||
|
|
||||||
|
|
||||||
|
def _pool_cell(b, alpha):
|
||||||
|
return Cell("RQ2P3", f"RQ2P3/B={b}/alpha={alpha}",
|
||||||
|
{"bridge": "off", "topology": "bridge-federated-pool",
|
||||||
|
"selector": "static", "pool_B": str(b), "pool_alpha": str(alpha)}, False)
|
||||||
|
|
||||||
|
|
||||||
|
def _fed_cell():
|
||||||
|
return Cell("RQ2", "RQ2/bridge=off/selector=static/topo=bridge-federated",
|
||||||
|
{"bridge": "off", "topology": "bridge-federated", "selector": "static"}, False)
|
||||||
|
|
||||||
|
|
||||||
|
def _circuit_seeds(cell_id, n=50):
|
||||||
|
run_seed = derive_seed(cell_id, 0)
|
||||||
|
return [int.from_bytes(hashlib.sha256(f"{run_seed}|circ|{j}".encode()).digest()[:8], "big")
|
||||||
|
for j in range(n)]
|
||||||
|
|
||||||
|
|
||||||
|
# --- pool helpers ---------------------------------------------------------- #
|
||||||
|
def test_zipf_weights_normalized_and_uniform_at_alpha0():
|
||||||
|
w = zipf_weights(8, 0.0)
|
||||||
|
assert len(w) == 8
|
||||||
|
assert abs(sum(w) - 1.0) < 1e-12
|
||||||
|
assert all(abs(x - 1.0 / 8) < 1e-12 for x in w) # alpha=0 → uniform
|
||||||
|
|
||||||
|
|
||||||
|
def test_zipf_weights_skew_monotone_decreasing():
|
||||||
|
w = zipf_weights(8, 2.0)
|
||||||
|
assert abs(sum(w) - 1.0) < 1e-12
|
||||||
|
assert all(w[i] > w[i + 1] for i in range(len(w) - 1)) # rank-1 heaviest
|
||||||
|
assert w[0] > zipf_weights(8, 0.0)[0] # skew concentrates mass on top bridge
|
||||||
|
|
||||||
|
|
||||||
|
def test_weighted_draw_deterministic_and_respects_extreme_skew():
|
||||||
|
d = hashlib.sha256(b"x").hexdigest()
|
||||||
|
assert weighted_draw(d, [0.25, 0.25, 0.25, 0.25]) == weighted_draw(d, [0.25, 0.25, 0.25, 0.25])
|
||||||
|
# all mass on bin 0 → always bin 0, whatever the hash
|
||||||
|
for s in (b"a", b"b", b"c", b"zzz"):
|
||||||
|
assert weighted_draw(hashlib.sha256(s).hexdigest(), [1.0, 0.0, 0.0]) == 0
|
||||||
|
|
||||||
|
|
||||||
|
# --- the pool topology ----------------------------------------------------- #
|
||||||
|
def test_pool_reuses_bridges_and_labels_stay_in_range():
|
||||||
|
cell = _pool_cell(4, 0.0)
|
||||||
|
specs = [assemble(cell, s) for s in _circuit_seeds(cell.cell_id)]
|
||||||
|
labels = {bridge_label(s) for s in specs}
|
||||||
|
# B=4 pool over 50 circuits → far fewer distinct bridges than circuits (reuse),
|
||||||
|
# and every label is one of the B pool slots.
|
||||||
|
assert labels <= {f"bridge#{i:02d}" for i in range(4)}
|
||||||
|
assert 1 < len(labels) <= 4
|
||||||
|
assert len(labels) < len(specs)
|
||||||
|
|
||||||
|
|
||||||
|
def test_pool_produces_concentration_variance_unlike_fresh_bridge():
|
||||||
|
cell = _pool_cell(4, 1.0)
|
||||||
|
specs = [assemble(cell, s) for s in _circuit_seeds(cell.cell_id)]
|
||||||
|
conc = [c for c in bridge_concentration(specs) if c is not None]
|
||||||
|
assert len(conc) == len(specs)
|
||||||
|
assert max(conc) > min(conc) # genuine variance (the fresh-bridge instrument had none)
|
||||||
|
|
||||||
|
|
||||||
|
def test_pool_spans_two_houses_and_is_isolation_gated():
|
||||||
|
cell = _pool_cell(8, 2.0)
|
||||||
|
spec = assemble(cell, derive_seed(cell.cell_id, 0))
|
||||||
|
assert spec.span_houses() >= 2
|
||||||
|
assert spec.isolation_gated()
|
||||||
|
assert spec.bridge_present and not spec.padding_applied
|
||||||
|
assert any(h.is_bridge for h in spec.hops)
|
||||||
|
|
||||||
|
|
||||||
|
def test_pool_assembly_is_deterministic():
|
||||||
|
cell = _pool_cell(4, 1.0)
|
||||||
|
s = derive_seed(cell.cell_id, 0)
|
||||||
|
assert assemble(cell, s).fingerprint() == assemble(cell, s).fingerprint()
|
||||||
|
|
||||||
|
|
||||||
|
# --- lead bridge-federated branch untouched (bit-reproducible) ------------- #
|
||||||
|
def test_lead_bridge_federated_still_fresh_bridge_per_seed():
|
||||||
|
cell = _fed_cell()
|
||||||
|
seeds = _circuit_seeds(cell.cell_id)
|
||||||
|
specs = [assemble(cell, s) for s in seeds]
|
||||||
|
labels = [bridge_label(s) for s in specs]
|
||||||
|
# fresh bridge per seed → all-distinct labels (the lead degeneracy), NOT pool slots
|
||||||
|
assert len(set(labels)) == len(labels)
|
||||||
|
assert all(not lbl.startswith("bridge#00") or len(lbl) > 9 for lbl in labels)
|
||||||
|
|
||||||
|
|
||||||
|
def test_lead_bridge_federated_fingerprint_reproducible():
|
||||||
|
cell = _fed_cell()
|
||||||
|
s = derive_seed(cell.cell_id, 0)
|
||||||
|
assert assemble(cell, s).fingerprint() == assemble(cell, s).fingerprint()
|
||||||
Reference in New Issue
Block a user