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Volume 13 (2017) Article 4 pp. 1-22
On the (Non) NP-Hardness of Computing Circuit Complexity
Received: October 30, 2015
Revised: February 15, 2017
Published: June 30, 2017
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Keywords: circuit lower bounds, reductions, NP-completeness, projections, minimum circuit size problem
ACM Classification: F.2.3, F.1.3
AMS Classification: 68Q15, 68Q17

Abstract: [Plain Text Version]

\newcommand{\MCSP}{\mathrm{MCSP}} \newcommand{\NMCSP}{\mathrm{NMCSP}} \def \AC {{\sf AC}} \def \poly {\mathrm{poly}} \def \P {{\sf P}} \def \ZPP {{\sf ZPP}} \def \EXP {{\sf EXP}} \def \NP {{\sf NP}} \def \eps {{\varepsilon}} \def \E {{\sf E}} \def \SIZE {{\sf SIZE}} \def \BPP {{\sf BPP}} \def \Ppoly {{\P/\poly}} \def \io {\mathrm{i.o.}{\text{-}}}

The Minimum Circuit Size Problem (\MCSP) is: given the truth table of a Boolean function f and a size parameter k, is the circuit complexity of f at most k? This is the definitive problem of circuit synthesis, and it has been studied since the 1950s. Unlike many problems of its kind, \MCSP is not known to be \NP-hard, yet an efficient algorithm for this problem also seems very unlikely: for example, \MCSP\in \P would imply there are no pseudorandom functions.

Although most \NP-complete problems are complete under strong “local” reduction notions such as polylogarithmic-time projections, we show that \MCSP is provably not \NP-hard under O(n^{1/2-\eps})-time projections, for every \eps > 0, and is not \NP-hard under randomized O(n^{1/5-\eps})-time projections, for every \eps > 0. We prove that the \NP-hardness of \MCSP under (logtime-uniform) \AC0 reductions would imply extremely strong lower bounds: \NP \not\subset \Ppoly and \E \not\subset \io\SIZE(2^{\delta n}) for some \delta > 0 (hence \P = \BPP also follows). We show that even the \NP-hardness of \MCSP under general polynomial-time reductions would separate complexity classes: \EXP \neq \NP \cap \Ppoly, which implies \EXP \neq \ZPP. These results help explain why it has been so difficult to prove that \MCSP is \NP-hard.

We also consider the nondeterministic generalization of \MCSP: the Nondeterministic Minimum Circuit Size Problem (\NMCSP), where one wishes to compute the nondeterministic circuit complexity of a given function. We prove that the \Sigma_2 \P-hardness of \NMCSP, even under arbitrary polynomial-time reductions, would imply \EXP \not\subset \Ppoly.

A preliminary version of this paper appeared in the Proceedings of the 30th IEEE Conference on Computational Complexity, 2015.