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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.

Effective Numberings, Reductions, Resources, and Randomness: Examples

1 · Prerequisites

2 · Summary

These three calculations apply the preceding interfaces with all encodings and sample spaces fixed. The specialization example stores the numeral for three, traces the addition routine and displays its tuple blocks. Its program index is specified by the finite compiler output, rather than an invented decimal index.

The affine family uses all twenty-five seeds over the field with five elements, including zero slopes. Solving two output equations gives a unique seed, while an impossible triple of outputs shows exactly where three-wise independence fails. The polynomial example lists all four roots of XY−1 on the twenty-five-point grid and compares the exact probability with the total-degree bound. Both field calculations declare the prime-field construction and verify the elementary arithmetic used. These examples use the algebraic and numbering arguments developed on the companion page.

3 · Logical flowchart

4 · Definitions, theorems and proofs

ExampleConstruction: AI-generatedVerification: AI-adaptedOpen item page →

Smn specializes a two argument index

Example

Take the addition derivation A(a,0)=a, A(a,y+1)=S(A(a,y)) and apply the finite syntax compiler from the normal-form construction (available through specialization). Let w be its emitted machine word and let e=2w1+val(w) be its length-lex index. This specifies an actual compiled index, without pretending it has a particular short decimal value. Concretely its routine parses two numeral blocks, stores the first in an accumulator and the second in a counter, increments the accumulator and decrements the counter until the latter is zero, then writes the accumulator as output. Each binary decrement changes trailing zeros to ones and the preceding one to zero and removes a newly redundant leading zero, retaining the single word 0 for zero.

Set q=s11(e,3). Then q computes y3+y; in particular φq(0)=3 and φq(4)=7.

Facts & Assumptions

Given: The explicitly specified addition routine, compiled with the literal finite-state routine convention of the preceding normal-form and specialization constructions. A fixed ordering of the emitted states is part of that compiler, not a claim that all compilers give the same e.

[F1]

Specialization prepends stored parameters and preserves partial-function values and domains (Smn for the fixed acceptable numbering).

[F2]

Addition is given by primitive recursion and canonical numeral operations are PR (Fixed coding primitive recursive arithmetic and sequences).

Verification

1.1

After j loop iterations, the accumulator is a+j and the counter is yj, for 0jy: initially this is the parsed input, and one increment/decrement preserves the formula. The counter reaches zero after exactly y iterations, giving output a+y. At y=0 the loop is skipped. These are the addition recursion and its finite numeral routines in F2, so the compiled index e has the advertised total binary function.

F2given
2.1

Specialization F1 writes the stored numeral bin(3)=11 before the input numeral and sends the two-entry tuple to e. For y=0 the arity header is 110, the block for 11 is 11011 and the block for 0 is 100, so the exact grouped encoding is 11011011100. For y=4 it is 110110111110100, since the block for 100 is 1110100. The first calculation leaves accumulator 3 unchanged and outputs 11; the second has accumulator values 3,4,5,6,7 and counter values 4,3,2,1,0, outputting 111. Thus canonical input numerals 0 and 100 produce 11 and 111 respectively, and F1 gives the asserted equality for every y.

step 1.1F1
ExampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Pairwise independent affine hashing over a prime field

Example

In F5=Z/5, take all 25 seeds (a,b) and ha,b(x)=ax+b, including zero slope. At inputs 1,3, the outputs 2,4 come from the unique seed (1,1). Each ordered output pair occurs once, but the family is not three-wise independent, since h(2)=2h(1)h(0).

Facts & Assumptions

Given: Uniform sampling of the 25 ordered residue pairs. All following arithmetic is modulo 5.

[F1]

Affine maps over a finite field have uniform marginals and exactly one seed for each prescribed output pair at distinct inputs (Pairwise independent hash family interface).

[F2]

The residue ring modulo a prime is a field (For every prime p, the two operations on Z/p make it a field).

Verification

1.1

The integer 5 is prime: it is greater than one, and its possible positive proper divisors 2,3,4 do not divide it (remainders 1,2,1 respectively). Therefore F2 constructs the field used here, with residues 0,1,2,3,4. Its nonzero inverses are 11=1, 21=3, 31=2, 41=4, as 1,6,6,16 all have remainder one. In particular division by the difference 31=2 is valid.

F2given
2.1

Solving a+b=2 and 3a+b=4 gives 2a=2, hence a=32=1 and b=1. Direct substitution gives h(1)=2, h(3)=4. More generally outputs u,v give a=3(vu), b=ua, a unique seed as in F1. Each joint output has probability 1/25 and each marginal 1/5, so these two values are independent uniform. This counts all slopes, including zero when u=v.

step 1.1F1
3.1

For every seed, h(0)=b, h(1)=a+b, and h(2)=2a+b=2h(1)h(0). Thus h(0)=0 and h(1)=0 force b=a=0 and consequently h(2)=0. The event (h(0),h(1),h(2))=(0,0,1) has probability zero, whereas three independent uniform values would give 1/125. This is a concrete failure of three-wise independence, consistent with the pairwise conclusion.

step 2.1given
ExampleConstruction: AI-generatedVerification: AI-adaptedjudge pass (gpt-5.6-terra)Open item page →

Schwartz zippel for a bivariate polynomial

Example

For the nonzero formal polynomial f(X,Y)=XY1 over F5, total degree is two. Of the 25 independent uniform pairs, precisely (1,1),(2,3),(3,2),(4,4) are roots. The actual zero probability is 4/25, strictly below the Schwartz–Zippel bound 2/5.

Facts & Assumptions

Given: Independent uniform X,Y in the five-element residue field.

[F1]

A nonzero total-degree-d polynomial on a nonempty uniform product set A has zero probability at most min(1,d/A) (Schwartz zippel over finite fields).

[F2]

Verification

1.1

Five has no positive proper divisors other than one: 2,3,4 leave remainders 1,2,1. Thus F2 supplies F5, with distinct residues 0 through 4. At X=0, XY1=1=40. At each nonzero X, the unique Y solving XY=1 is its inverse: 11=1, 23=6=1, 32=6=1, 44=16=1 modulo 5. Cancellation rules out any additional Y for the same X. These are all five possibilities for X, so exactly the four listed pairs are roots.

F2given
2.1

Each pair has mass 1/25, so the count gives probability 4/25. The formal coefficient of XY is one and its total degree is two; the constant term is nonzero but has degree zero, so it does not change total degree. F1 with m=2, d=2 and A equal to the field gives min(1,2/5)=2/5=10/25. Consequently 4/25<10/25. The comparison is an upper bound, not a claimed equality; independence is used to give every pair the same mass.

step 1.1F1

5 · Examples, counterexamples and false statements

None yet.

Sources