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.
The classes PSPACE and NPSPACE
Definition
The class PSPACE is the union of all deterministic polynomial-space classes:
The class NPSPACE is the union of all nondeterministic polynomial-space classes:
Equivalently, a language lies in PSPACE when there is a deterministic multitape Turing machine deciding using at most space for some constant , and similarly lies in NPSPACE when there is such a nondeterministic decider. The meanings of and are those of The classes DTIME, NTIME, DSPACE, and NSPACE.
Remarks
- The page uses polynomial space rather than a single fixed bound because closure and completeness statements are stated for the whole class.
- No closure under complement is built into the definition of NPSPACE; that is a later theorem.
Depends on
Used by
- L is properly contained in PSPACE Corollary
- PSPACE equals NPSPACE and is closed under complement Corollary
- Polynomial space oracle absorption Lemma
- TQBF is in PSPACE Proposition
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
- 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)