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.
PSPACE equals NPSPACE and is closed under complement
Statement
and if then its complement also lies in PSPACE.
Facts & Assumptions
Given: the classes PSPACE and NPSPACE.
PSPACE and NPSPACE are the unions of and over polynomial bounds (The classes PSPACE and NPSPACE).
Savitch's theorem gives for every (Savitch's theorem: NSPACE(s(n)) is contained in DSPACE(s(n)^2)).
A deterministic space class is defined by deterministic deciders (The classes DTIME, NTIME, DSPACE, and NSPACE).
Proof
If , then [L1] gives a polynomial with . By [L2], , because the square of a polynomial is again a polynomial. Thus .
The reverse inclusion is immediate from [L1] because every deterministic machine is a special case of a nondeterministic one. Hence .
If , choose a deterministic polynomial-space decider for using [L1] and [L3]. Swapping the accepting and rejecting halting states of gives a deterministic polynomial-space decider for the complement of . Therefore PSPACE is closed under complement.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
9 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
- Sanjeev Arora and Boaz Barak, Computational Complexity: A Modern Approach (standard reference, not scraped)
- Eric Blais, Models of Computation, 17. Space Complexity (standard reference, not scraped)