Abstract:
Nonuniformity is a central concept in computational complexity with
powerful connections to circuit complexity and randomness. Nonuniform
reductions have been used to study the isomorphism conjecture for NP
and completeness for larger complexity classes. We study the power of
nonuniform reductions for NP-completeness, obtaining both separations
and upper bounds for nonuniform completeness vs uniform completeness
in NP.
Under various hypotheses, we obtain the following separations:
There is a set complete for NP under nonuniform many-one
reductions, but not under uniform many-one reductions. This is true
even with a single bit of nonuniform advice.
There is a set complete for NP under nonuniform many-one
reductions with polynomial-size advice, but not under uniform Turing
reductions. That is, polynomial nonuniformity is stronger than a
polynomial number of queries.
For any fixed polynomial p(n), there is a set complete for NP
under uniform 2-truth-table reductions, but not under nonuniform
many-one reductions that use p(n) advice. That is, giving a uniform
reduction a second query makes it more powerful than a nonuniform
reduction with fixed polynomial advice.
There is a set complete for NP under nonuniform many-one
reductions with polynomial advice, but not under nonuniform many-one
reductions with logarithmic advice. This hierarchy theorem also holds
for other reducibilities, such as truth-table and Turing.
We also consider uniform upper bounds on nonuniform
completeness. Hirahara (2015) showed that unconditionally every set
that is complete for NP under nonuniform truth-table reductions that
use logarithmic advice is also uniformly Turing-complete. We show that
under a derandomization hypothesis, the same statement for truth-table
reductions and truth-table completeness also holds.
Theory of Computing Systems 66(4), 743-757 (2022).
[pdf | DOI]
Proceedings of the
35th International Symposium on Theoretical Aspects of Computer
Science (Caen, France, February 28-March 3, 2018).
[DOI]
Technical Report TR18-011,
Electronic Colloquium on Computational Complexity, 2018.
[pdf]