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 DTIME, NTIME, DSPACE, and NSPACE
Definition
Let .
For nonnegative resource functions , the notation means that some constants and satisfy for every . Every resource bound below uses constants fixed for the machine, uniformly over all its inputs and branches. Time counts transitions; space counts all cells visited on all tapes, including the input tape, with each distinct tape/cell pair counted once. No constructibility assumption on or is needed to define these classes.
A language belongs to DTIME when there exists a deterministic multitape Turing machine deciding in time .
A nondeterministic -tape Turing machine is obtained from the deterministic -tape model of Multitape and nondeterministic Turing machine variants by replacing its transition function with a finite-valued transition map One branch chooses one instruction from the finite set at each step.
A language belongs to NTIME when there exists such a nondeterministic -tape machine for which:
- every branch of on every input of length halts within steps, and
- some branch of accepts exactly on the words of , in the same existential sense as Accepting computations of a nondeterministic machine.
A language belongs to DSPACE when a deterministic multitape decider uses worst-case space . It belongs to NSPACE when a nondeterministic multitape machine accepts exactly the words in , every branch halts, and the maximum number of visited cells over all branches and inputs of length is .
Remarks
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These are language classes. Function classes are expressed separately by saying that a machine computing the function does so within a stated bound.
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The chosen machine model is multitape because it is convenient for programming; later theorems show that polynomial-time and polynomial-space notions do not depend on that choice.
Depends on
Used by
- PSPACE equals NPSPACE and is closed under complement Corollary
- A bounded computation tableau for a nondeterministic Turing-machine run Definition
- A read-only-input logarithmic-space machine Definition
- An efficient universal simulation with a clock Definition
- Nondeterministic acceptance time and exact clocks Definition
- P-completeness under logspace reductions Definition
- Polynomial space and nondeterministic polynomial space Definition
- The class P Definition
- The classes EXP and NEXP Definition
- The classes PSPACE and NPSPACE Definition
- A polynomial-round protocol value is computable in polynomial space Lemma
- Padding transfers time bounds Lemma
- Polynomial-time computations have logspace-uniform circuit families Lemma
- Read-only work space becomes all-tapes space after charging input Lemma
- Space-bounded universal simulation Lemma
- The space-diagonal machine halts Lemma
- The time-diagonal language respects its budget Lemma
- NP ⊆ PSPACE ⊆ EXP Proposition
- PH containments and polynomial space Proposition
- Polynomially related encodings preserve polynomial-time and polynomial-space classes Proposition
- Every multitape space-S computation has a single-tape simulation in O(n+S(n)) space Theorem
- Every multitape time-T computation has a single-tape simulation in O((n+T(n))²) time Theorem
- Savitch's theorem: NSPACE(s(n)) is contained in DSPACE(s(n)²) Theorem
- The deterministic space hierarchy theorem Theorem
- The deterministic time hierarchy theorem Theorem
- The nondeterministic time hierarchy theorem Theorem
- The verifier and nondeterministic definitions of NP agree Theorem
Dependency tree · two levels
8 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
- John Watrous, Introduction to the Theory of Computing, Lecture 19: Time-bounded computations (standard reference, not scraped)
- Eric Blais, Models of Computation, 7. Time Complexity (standard reference, not scraped)
- Eric Blais, Models of Computation, 17. Space Complexity (standard reference, not scraped)