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 universal simulator can realize T steps with machine-dependent O(T log T) overhead
Statement
There exists a deterministic multitape universal simulator for the chosen machine coding with the following property: for every valid machine code there is a constant such that, for every input word and every integer , if halts on within at most steps with output word , then halts on input with output within steps; if diverges on , then diverges as well. The constant may depend on the finite alphabet, states, and transition table encoded by , but not on or .
Facts & Assumptions
Given: A valid machine code , an input word , and a time bound .
Machine codes are effectively decodable finite tuples, by A fixed effective binary encoding of deterministic one-tape Turing machines and The chosen machine coding is injective and has a total decoder.
The definition of a universal Turing machine is to reproduce halting outputs and divergence for the coded machine/input pair, by A universal Turing machine relative to a fixed machine encoding.
Worst-case time counts simulation steps of the simulator itself, by Worst-case time and space complexity of a machine.
Proof
By [L1], the simulator can first decode into the finite control data of and copy those data to a read-only program track. It then stores the current simulated configuration in a geometrically blocked tape layout whose block sizes double outward from the simulated heads. This representation keeps recently accessed cells near the center while allowing farther regions to be reached after only logarithmically many block crossings.
One simulated step of changes only the current state, one scanned tape symbol, and one head position. In the blocked layout from step 1.1, finding the current symbol, updating it, and recentering after a head move costs amortized over the first simulated steps: most steps touch only the central blocks, and a level- reblocking costs but occurs only once per simulated head moves. Summing over the occupied levels gives the asserted amortized bound. The subscript records the fixed cost of interpreting the finite alphabet, state set, and transition table encoded by ; the cited efficient-universality theorem permits exactly this machine dependence. No constructibility hypothesis on the integer is used.
Summing the amortized cost over at most simulated steps gives total simulation time . The initial decode-and-load work contributes . If the simulation halts with output word , at most simulated tape cells can belong to its visited output segment. A final scan therefore converts to the self-delimiting word in time, which is absorbed by the displayed bound. By [L2], the simulator is universal because it emits exactly and, when diverges, continues simulating forever rather than entering a halting state.
Therefore, for each fixed valid code , the machine has the claimed universal behavior with total running time bounded by for a suitable constant independent of and .
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
10 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)
- John Watrous, Introduction to the Theory of Computing, Lecture 19: Time-bounded computations (standard reference, not scraped)