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.
A read-only-input logarithmic-space machine
Definition
A read-only-input machine has one input tape containing , whose head may move in either direction but whose cells are never changed, and finitely many read/write work tapes. Its work space on inputs of length is the number of visited work-tape cells, not the input cells. A deterministic machine decides when it halts on every input; a nondeterministic machine decides when every branch halts and some branch accepts exactly the inputs in the language.
It is a logspace machine when its work space is . The convention also covers the empty input. This is a work-space convention, distinct from the all-tapes convention in The classes DTIME, NTIME, DSPACE, and NSPACE.
Depends on
Used by
- A nondeterministic branch tree where state swapping is not complementing Counterexample
- Logspace many-one reduction Definition
- The classes L and NL Definition
- Logspace machines have polynomially many configurations Lemma
- Immerman-Szelepcsényi theorem: NL equals coNL Theorem
- Savitch simulation into read-only-input deterministic work space Theorem
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
- Arora and Barak, Computational Complexity, §3.1 and §3.4.1 (standard reference, not scraped)