How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Choosing a sum-check error budget
Statement
Let . For a supplied sum-check instance with a field satisfying , every prover's probability of acceptance on a false initial claim is at most . This assumes the stated field and trusted evaluation are already supplied; it does not construct a field.
Facts & Assumptions
Given: The objects and hypotheses in the statement above.
False initial claims have acceptance probability at most min(1,sum_i d_i/|F|) for every adaptive prover (Adaptive-prover soundness of sum-check).
Proof
The soundness theorem bounds the false-claim acceptance probability by .
Since and , the size hypothesis implies . Combining gives the result, including (zero error) and (a possibly trivial guarantee). Equality in the field-size inequality is allowed.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
2 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Justin Thaler, Proofs, Arguments, and Zero-Knowledge (2023), Proposition 4.1 and degree/field-size discussion pp.35–38 (standard reference, not scraped)