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.
A false sum-check claim rarely becomes true
Statement
At any round of sum-check, condition on a reached past transcript of positive probability for which . If the next message fails its format or consistency check it is rejected. Otherwise, conditioned also on the prover's fixed message, the probability that the updated claim becomes true is at most . The same upper bound holds after averaging over a randomized choice of message. Fresh verifier randomness is drawn after the message.
Facts & Assumptions
Given: The objects and hypotheses in the statement above.
The current true value is S_{i-1}, the honest message is q_i, and a fresh uniform r_i is drawn only after h_i is fixed (Sum-check with explicit degree bounds).
A nonzero polynomial of degree m over an integral domain has at most m distinct roots in that domain (A nonzero polynomial of degree over an integral domain has at most distinct roots).
Proof
Let be the true partial sum at the fixed prefix. Its degree is at most because specialization and addition preserve degree upper bounds, and . Any well-formed consistent instead has , so is a nonzero formal polynomial of degree at most . Messages failing these checks reject immediately.
A field is an integral domain, since with implies . Apply the root bound to : it has at most roots in . The next scalar is true precisely if , because . The fresh is uniform even after conditioning on the fixed message, so this probability is at most .
The bound holds for each allowed message, so averaging its conditional probability over any prover randomness preserves it. If , the nonzero difference is constant and the probability is zero; if , the cap at one is merely trivial. The argument includes , , characteristic two, and challenges . A false updated claim need not be detected in this round; only its becoming true is the exceptional event bounded here.
Depends on
Used by
Dependency tree · two levels
9 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 non-inductive proof, pp.36–37 (standard reference, not scraped)