Alphabeta Math
False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-05
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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.

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A pseudopolynomial algorithm is polynomial in the binary input length

Statement

A pseudopolynomial algorithm is polynomial in the binary input length.

Facts & Assumptions

Given: The standard dynamic program for SUBSET SUM that fills an n×T table for an instance with n input numbers and target T.

[F1]

A SUBSET SUM instance writes its target integer in binary, by Subset sum and partition decision problems.

[L1]

Worst-case running time is measured as a function of the input length, not of the numeric value of a parameter written inside that input, by Worst-case time and space complexity of a machine.

Refutation

technique · direct
1.1

Consider the one-number SUBSET SUM instances ([2m],2m) for m1. By [F1], the binary input length is O(m).

F1given
2.1

The standard table-filling algorithm uses Θ(nT)=Θ(2m) time on this family because here n=1 and T=2m.

step 1.1givenalgebra
3.1

Since 2m is exponential in the binary length m, the running time in step 2.1 is not polynomial in the input length. By [L1], polynomial-time complexity is measured against that binary length. Therefore pseudopolynomial dependence on T does not imply polynomial dependence on the bit-length of T.

L1step 1.1step 2.1
4.1

The statement is false.

step 3.1

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · two levels

5 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