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Tooling: prune signed-sparse coefficient enumeration with exact stream equivalence - #833
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Mister-Meeseeks merged 2 commits intoOct 14, 2026
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100-PR batch review at Merged to Reviewed scope: Degree-pruned signed-sparse enumeration preserving ordered terms and exact certificate payloads; no mathematical claim change. The pinned scoped command passed; the batch ledger contains its command, input hashes, environment and log. This incorporates the research/tooling contribution and does not change the selected κ or discharge the inherited multiplication-theorem assumptions. Batch review, attribution and evidence. Thank you for the contribution. |
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Tooling improvement; no new κ. The historical signed-sparse coefficient checker scans all
4^hcoordinate words before rejecting excessive degree. This change rejects impossible prefixes while preserving the exact ordered term stream, parity filter, feature guard and expansion cap.At h=8, seven alternating-order runs measured enumeration speedups of 574x / 52x / 3.08x for q=2 / 4 / 8. These are millisecond-scale microbenchmarks. The standard complete audit measured 0.982x: no end-to-end speedup is claimed. All mathematical certificate fields are identical; two regenerated certificates change only the affected source hash.
Validation: exhaustive equivalence for all 13 admissible (h,q) pairs through h=8, pinned original implementation and complete audit comparison, 14 relevant tests, two deliberate factor corruptions rejected, and the 10 signed-sparse tests also passing under
python3 -O. Reproduce with:Base:
7ee02b7c96d85f22b38d28bd7ed49bb8c1aeb261. Seed 92, verification engineering. No pinned coordination issue; scope and candidate selection are recorded locally. Checked current PR metadata for overlap. Existing performance PRs address other routines.upstream/and selected frontier are unchanged; full repository verification and selected cold replay were not run for this historical helper change.Evidence, exact source pins, limits and predecessor credit:
research/signed-sparse-pruning/README.mdandRESULT.json. Credits the existing signed-sparse construction integrated by Douglas R. Colkitt. Contribution by anudeepadi with substantial OpenAI Codex AI assistance; Apache-2.0.