Alphabeta Math
ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12
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.

Ordinary binary numerals and doubled-bit numerals are polynomially related

Example

Let σ(0)=0, let σ(n) for n>0 be the ordinary binary numeral with leading bit 1, and let τ(n) be the word obtained by repeating each bit of σ(n) twice. Decode σ by rejecting the empty word and noncanonical leading zeros, and otherwise reading the binary numeral. Decode τ by first requiring identical adjacent bit-pairs, replacing each pair by one bit, and then using the decoder for σ. These total decoders return mal on every rejected word and recover n on the displayed codewords, so σ and τ are effective encodings. Moreover, τ(n)=2σ(n) for every n, so the two encodings are polynomially related. For example, σ(13)=1101,τ(13)=11110011. Consequently a bound such as τ(n)3 is also a polynomial bound in σ(n), namely 8σ(n)3.

Facts & Assumptions

Given: The encodings σ and τ defined above.

[L1]

Two encodings are polynomially related when each code length is bounded by a polynomial in the other, by Instance size and polynomially related encodings.

[L2]

Polynomially related encodings preserve polynomial size bounds, by Polynomially related encodings preserve polynomial size bounds.

Verification

technique · direct
1.1

The specified decoders recover n from both codewords, so σ and τ are effective encodings. By construction, each bit of σ(n) contributes exactly two bits to τ(n), so τ(n)=2σ(n) for every n. Hence τ(n)2σ(n) and σ(n)τ(n), which are polynomial bounds in both directions. By [L1], σ and τ are polynomially related.

givenL1
1.2

The displayed example is immediate: σ(13)=1101 and τ(13)=11110011.

given
2.1

Applying [L2] to the polynomial bound m(n)=τ(n)3 gives a polynomial bound in σ(n). Here the calculation is explicit: τ(n)3=(2σ(n))3=8σ(n)3.

L2step 1.1algebra

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · two levels

3 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