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Specialize the encoded BIT coefficient evaluator to every fixed dimension and bound its retained continuation backing - #7153
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…sion and bound its retained continuation backing
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Exact result and novelty
Specializes the encoded #6903 numerical consumer for every fixed N>=2 with 17 source-checked edits, complete N^2 chronological fields, and four reusable continuation tapes. Before the capacity guard, extra demand is at most 16N^2+128 residue Words and 128 index Words, with separately bounded historical tape backing. This is a strict fixed-N consumer interface, not a selected B0 dispatcher.
Reproduction and independent checks
Normal/optimized author replay (14 exact cases, 10 controls), separate rank-two oracle, 816 extent checks and corruption controls. Replay: python3 -B scripts/research_package.py --package research/fixed-dimension-bit-coefficients
Limitations and bound status
No new kappa. Selected catalogue labels, root-size coupling, changing-precision physical bank and full implementation remain unproved; only current live callback handles are admitted. Selected conditional kappa remains 0.00363005817; the five framework assumptions remain.
Attribution
Prepared for @CubeJerry with substantial OpenAI assistance; credit #6903, #2835, #6896 and original numerical authors.
Complete review packet
Full PR description, proof and source pins
Base:
e54523517d0f03e58352e647c403a5af3e525a57. No upstream PR is opened by this link.