Alphabeta Math
Pipeline-generated
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.

Arithmetization and the Sum-Check Protocol: Examples and Counterexamples

1 · Prerequisites

2 · Summary

These examples expand a two-bit interpolation table, check every round of a three-variable sum-check transcript, and count the successful seeds of a noisy linear self-corrector. The product-polynomial counterexample makes the verifier’s cost explicit even when the Boolean cube has exponentially many points.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Interpolating a two-bit table over F_5

Example

Over F5, let f(0,0)=1, f(0,1)=2, f(1,0)=1, and f(1,1)=4. Its unique multilinear extension is f~(X,Y)=1+Y+2XY. In particular f~(2,3)=1 in F5.

Facts & Assumptions

Given: The objects and hypotheses in the statement above.

[F1]

Every field-valued Boolean table has the unique multilinear extension given by the product-basis interpolation sum (Boolean-cube interpolation).

Verification

1.1F1algebra

The interpolation formula gives (1−X)(1−Y)+2(1−X)Y+X(1−Y)+4XY. Expanding and combining coefficients yields 1+Y+2XY, which has degree at most one in each variable.

2.1F1step 1.1algebra∎

Its values at (0,0),(0,1),(1,0),(1,1) are respectively 1,2,1,4, so it agrees with the table; uniqueness follows from the interpolation theorem. At (2,3) its integer expression is 1+3+2⋅2⋅3=16, which reduces to one modulo five.

ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

A complete sum-check transcript over F_101

Example

Over F101 let g(X,Y,Z)=2X3+XZ+YZ, with individual bounds (3,1,1) and claimed sum H=12. An honest transcript with successive challenges 2,3,6 has messages h1(X)=8X3+2X+1,h2(Y)=34+Y,h3(Z)=16+5Z. The successive scalar claims are 69,37,46, and the terminal equality holds. For this polynomial, a false initial sum claim is accepted with probability at most 5/101 by the randomized protocol; a displayed fixed challenge sequence alone is not a soundness proof.

Facts & Assumptions

Given: The objects and hypotheses in the statement above.

[F1]

Honest messages are partial cube sums, with coefficient, endpoint-consistency and terminal checks (Sum-check with explicit degree bounds).

[F2]

For any false initial claim, acceptance is at most min(1,sum_i d_i/|F|) under fresh independent challenges and trusted evaluation (Adaptive-prover soundness of sum-check).

Verification

1.1F1algebra

Sum g over Boolean Y,Z to obtain q1(X)=8X3+2X+1. Then q1(0)+q1(1)=1+11=12 and q1(2)=64+4+1=69. This also computes the cube sum by splitting over X.

2.1F1step 1.1algebra

After r1=2, sum g(2,Y,Z) over Z=0,1: q2(Y)=16+(16+2+Y)=34+Y. Its endpoint sum is 34+35=69, and its value at r2=3 is 37.

3.1F1step 2.1algebra

With that prefix q3(Z)=g(2,3,Z)=16+5Z. Its endpoint sum is 16+21=37. At r3=6 its value is 46, also g(2,3,6)=16+12+18=46. The coefficient lists have lengths 4,2,2 and the degrees meet (3,1,1), so all checks pass modulo 101.

4.1F2algebra∎

For any false initial claim the soundness theorem applies to the fixed polynomial and trusted degree bounds, giving error at most (3+1+1)/101=5/101 over fresh independent challenges. It asserts this for all adaptive provers, separately from the honest transcript just computed.

ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

Correcting one corrupted table entry

Example

On F23, let ℓ(x)=x1, and let f agree with ℓ except that f(0)=1. Thus dist⁡(f,ℓ)=1/8. At every fixed nonzero x, the two-query corrector succeeds with probability exactly 6/8=3/4; it fails exactly for seeds y=0 and y=x. At x=0 it always returns zero.

Facts & Assumptions

Given: The objects and hypotheses in the statement above.

[F1]

At distance delta<1/4 from a linear function, the two-query corrector succeeds at every point with probability at least 1-2delta, and that nearby linear function is unique (Pointwise correctness under less than quarter noise).

Verification

1.1F1algebra

There are eight cube points, with precisely the zero point corrupted, so δ=1/8<1/4. The self-correction theorem gives a unique nearby linear function and success at least 1−2δ=3/4 at each point.

2.1step 1.1algebra∎

For fixed x≠0, the query y is corrupted exactly when y=0, and the query x+y is corrupted exactly when y=x. These are distinct seeds. At either seed exactly one summand is flipped, so the output is wrong; at the other six seeds neither is flipped and linearity gives the right answer. At x=0, the sum f(y)+f(y) is zero for every seed, equal to ℓ(0). Thus the lower bound is attained for nonzero requests and exceeded for the zero request.

CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-07Open item page →

One point evaluation for an exponentially large cube

Statement refuted

The assertion that a sum-check verifier must evaluate g separately at every Boolean vertex is false. For n≥1, take g(X1,…,Xn)=∏iXi over a supplied finite field, with individual bounds di=1. Its cube sum is one although the cube has 2n points. The verifier uses O(n) field work, including one evaluation of g with at most n multiplications. False initial claims have acceptance probability at most min⁡(1,n/∣F∣).

Facts & Assumptions

Given: The objects and hypotheses in the statement above.

[F1]

The verifier checks coefficient messages round by round and evaluates g at the terminal challenge point (Sum-check with explicit degree bounds).

[F2]

Verifier field work is O(D) plus a single terminal point evaluation with D=sum_i(d_i+1) (Sum-check verifier resources).

[F3]

The false-claim acceptance probability is at most min(1,sum_i d_i/|F|) (Adaptive-prover soundness of sum-check).

Counterexample

1.1givenalgebra

At the all-one vertex the product equals one, and at every other Boolean vertex a zero coordinate makes it zero. Hence the cube sum is one. There are two independent choices per coordinate, giving 2n vertices, also when n=1.

1.2F1F2algebra

The specified protocol uses one terminal evaluation. Implement it by multiplying the n supplied coordinates starting from one, at a cost of at most n multiplications. Here D=∑i(1+1)=2n, so the resource lemma bounds all verifier field work, including this evaluation, by O(n). Zeros among the challenge coordinates simply make the product zero, without any division.

2.1F3step 1.1step 1.2algebra∎

The soundness theorem gives the stated false-claim bound from ∑idi=n, including the cap at one when the field is small. Thus the verifier does not need 2n separate evaluations of g. The claim concerns verifier work with a supplied evaluator and imposes no general efficiency assertion on the prover.

Sources