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.
CircuitSAT is NP-complete
Statement
is NP-complete under polynomial-time many-one reductions.
Facts & Assumptions
Given: the gate-list encoding of .
Well-formed gate lists have a designated output, and malformed lists are rejected, by Circuit satisfiability.
is NP-complete, by SAT is NP-complete.
A polynomial-time many-one reduction must preserve membership in both directions, by Polynomial-time many-one reductions.
NP-completeness means membership in NP together with NP-hardness, by NP-hard and NP-complete languages.
Proof
A verifier first rejects a malformed list. Otherwise it guesses one bit for every input gate, evaluates the gates in topological order, and accepts iff the designated output is . Its time is polynomial in the list length, so .
Given a Boolean formula , create one circuit input for each variable and one circuit gate for each connective, ordered from leaves toward the root; designate the root gate as output. This map is polynomial time and produces a circuit satisfying for every assignment . Therefore iff , so [L2] and [L3] give NP-hardness.
Combining membership from step 1.1 with hardness from step 1.2 proves NP-completeness by [L4].
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
7 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)