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.
NP is contained in P with a Sharp-P oracle
Statement
.
Facts & Assumptions
Given: with polynomial-time verifier and a polynomial witness-length bound , so witnesses may have any length at most (The class NP via polynomial-time verifiers).
uses a fixed oracle returning its exact binary integer value, by Polynomial time with a Sharp-P oracle.
functions count accepting paths, by Sharp-P and Gap-P functions.
Every function has a polynomial-time parsimonious reduction to , by NumberSAT is Sharp-P-complete under parsimonious reductions.
Proof
Enlarge if needed to a nonnegative integer-valued polynomial bound, and put . Define . A binary-branching polynomial-time machine guesses a word of length . It rejects if has no zero; otherwise it writes using the first zero, and accepts exactly when . This encoding is a bijection between words of length at most and guessed words with a zero. Thus the accepting-path count is exactly , so .
By [L3], compute in polynomial time a formula with . A deterministic oracle machine queries and accepts iff the returned binary integer is nonzero. Since , the answer has at most bits. By the verifier definition, exactly when .
This oracle machine decides , proving the containment.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
10 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
- Arora and Barak, Computational Complexity: A Modern Approach (standard reference, not scraped)
- Lance Fortnow, Counting Complexity (standard reference, not scraped)