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Comparing reductions to NP-complete sets

Journal Article journal-article Computer Science · Theoretical Computer Science

Abstract

Under the assumption that NP does not have p-measure 0, we investigate reductions to NP-complete sets and prove the following: (1) Adaptive reductions are more powerful than nonadaptive reductions: there is a problem that is Turing-complete for NP but not truth-table-complete. (2) Strong nondeterministic reductions are more powerful than deterministic reductions: there is a problem that is SNP-complete for NP but not Turing-complete. (3) Every problem that is many-one complete for NP is complete under length-increasing reductions that are computed by polynomial-size circuits. The first item solves one of Lutz and Mayordomo’s “Twelve Problems in Resource-Bounded Measure” (1999). We also show that every many-one complete problem for NE is complete under one-to-one, length-increasing reductions that are computed by polynomial-size circuits.

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Context

Venue
Information and Computation
Archive span
1987-2026
Indexed papers
3021
Paper id
144253019503165353
v2026.09.13