Partial proof for weighted_correlated_agreement_for_parameterized_curves'#419
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🤖 Gemini PR SummaryMathematical Formalization
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Lean Declarations ✏️ **Added:** 25 declaration(s)
✏️ **Affected:** 3 declaration(s) (line number changed)
✅ **Removed:** 3 `sorry`(s)
❌ **Added:** 3 `sorry`(s)
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Last updated: 2026-03-10 06:38 UTC. |
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Closing: partial proof for weighted correlated agreement variant — large BCIKS20 patch with new sorrys/placeholders. Donor-only. |
Some theorems may only have informal proofs available.
Some hard-to-prove facts may have been replaced with axioms.
Proven lemmas: 25/26
The main goal is to prove a “weighted correlated agreement over parameterized curves” theorem (BCIKS20 Thm 7.2, Version II): if many curve-parameter values z give weighted agreement ≥ α between the curve word i ↦ ∑j z^j u_j(i) and some Reed–Solomon codeword of degree < deg, then there exist global Reed–Solomon codewords v_j such that the set of coordinates i where all u_j(i) = v_j(i) has μ-measure ≥ α.
The proof is decomposed into (i) basic lemmas about extracting a witness codeword from an “agree_set” maximum, (ii) converting between the finitary carrier finCarrier and ReedSolomon.code, (iii) an “extraction” pipeline that from a large set S of good parameters produces a large subset S′ and global coefficients v_j matching the per-z decoded codewords, and (iv) a final lemma that turns “agreement for all z ∈ S′” into correlated agreement on coordinates.
Progress so far is strong on the elementary and algebraic glue: most helper lemmas are finished (20 nodes proven out of 28 total), including the machinery to pick codewords from agree_set, membership equivalences, and a clean reduction to a bivariate-polynomial representation of curve codewords (bivariatePoly_to_curveCodewords is proved, along with supporting coefficient/degree lemmas).
What remains is essentially one mathematical bottleneck: the “curve extraction” step that is the curve-analogue of BCIKS20 Section 5 (for lines). Concretely, the key missing lemma is the one that, from many z with good agreement, extracts a large S′ and a single bivariate polynomial P(Z,X) (degree in Z ≤ l+1, degree in X < deg) such that for all z ∈ S′ we have P(z, X) equal to the chosen decoder polynomial p_z; several downstream statements are currently blocked because this lemma is not available in the library.
Once that extraction lemma is supplied/proved, the rest of the proof is ready: it immediately yields global v_j, transfers the per-z agreement to agreement between curveEval(u,z) and curveEval(v,z) on S′, and then applies the already-available “sufficiently large list agreement on a curve ⇒ correlated agreement” lemma to conclude μ_set μ {i | ∀j, u_j(i)=v_j(i)} ≥ α.
The main challenge is that the missing step is not just algebraic rewriting; it packages the Guruswami–Sudan/Johnson-bound combinatorial-geometric argument specialized to curves (the heavy part of the paper), whereas the rest of the development is largely “glue code” plus polynomial interpolation/degree bookkeeping.