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.
Any machine that fully reads every input of length n needs at least linear time
Statement
Let be a -tape machine, and suppose that at least one input word of length exists and that halts on every input of that length. If, on every such input, the accepting or rejecting branch of scans each of the first input cells before halting, then
Facts & Assumptions
Given: A halting machine , an inhabited length- input set, and the input-reading property stated above.
Worst-case running time is the maximum number of steps over inputs of length , by Worst-case time and space complexity of a machine.
Proof
For the claimed lower bound is immediate. For , the input head starts at cell and moves at most one cell per transition. Reaching cell therefore takes at least transitions. The hypothesis says the machine scans that cell before halting, so it must make a further transition from a nonhalting configuration scanning the cell before it can enter an accepting or rejecting state. Thus every such halting branch takes at least steps.
The hypothesis says this lower bound applies on every input of length , and the input set is nonempty. By [L1], its worst-case maximum is at least the time on any one such input, so . Without the nonemptiness premise the claim fails for an empty input alphabet and , because the revised worst-case convention gives value zero.
Depends on
Used by
Dependency tree · two levels
4 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)