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The Cook-Levin reduction map is computable in polynomial time
Statement
For a fixed nondeterministic polynomial-time machine , the map sending an input to the Cook-Levin formula is computable in polynomial time.
Facts & Assumptions
Given: A fixed machine running in time at most on inputs of length .
The exactly-one-symbol family has polynomial size in the tableau side length, by The exactly-one-symbol constraints have polynomial size.
The start, accept, and transition families also have polynomial size in the tableau side length, by The start, accept, and transition constraints have polynomial size.
A time bound means that every run on length- inputs halts within the stated bound, in the worst-case sense formalized by Worst-case time and space complexity of a machine.
Proof
On an input of length , [L3] gives a tableau side length with . A deterministic transducer can loop over all cells, all alphabet symbols, and all local windows in lexicographic order and print the corresponding clauses of .
By [L1] and [L2], the number of printed variables and clauses is polynomial in , hence polynomial in because . Each loop iteration performs only constant-size bookkeeping for the fixed machine .
Therefore the transducer from step 1.1 halts after polynomially many steps and outputs . So the Cook-Levin map is polynomial-time computable.
Depends on
Used by
Dependency tree · two levels
13 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
- MIT 18.404J / 6.840J, Lecture 16: Cook-Levin Theorem (standard reference, not scraped)
- Stephen A. Cook, The Complexity of Theorem-Proving Procedures (standard reference, not scraped)