research-article

Improving Exhaustive Search Implies Superpolynomial Lower Bounds

Author:

Ryan WilliamsAuthors Info & Claims

SIAM Journal on Computing, Volume 42, Issue 3

Pages 1218 - 1244

https://doi.org/10.1137/10080703X

Published: 01 January 2013 Publication History

Abstract

The P vs. NP problem arose from the question of whether exhaustive search is necessary for problems with short verifiable solutions. We do not know if even a slight algorithmic improvement over exhaustive search is universally possible for all NP problems, and to date no major consequences have been derived from the assumption that an improvement exists. We show that there are natural NP and BPP problems for which minor algorithmic improvements over the trivial deterministic simulation already entail lower bounds such as ${\sf NEXP} \not\subseteq {\sf P}/{\rm poly}$ and ${\sf LOGSPACE} \neq {\sf NP}$. These results are especially interesting given that similar improvements have been found for many other hard problems. Optimistically, one might hope our results suggest a new path to lower bounds; pessimistically, they show that carrying out the seemingly modest program of finding slightly better algorithms for all search problems may be extremely difficult (if not impossible). We also prove unconditional superpolynomial time-space lower bounds for improving on exhaustive search: there is a problem verifiable with $k(n)$ length witnesses in $O(n^a)$ time (for some $a$ and some function $k(n) \leq n$) that cannot be solved in $k(n)^c n^{a+o(1)}$ time and $k(n)^c n^{o(1)}$ space, for every $c \geq 1$. While such problems can always be solved by exhaustive search in $O(2^{k(n)} n^a)$ time and $O(k(n)+ n^a)$ space, we can prove a superpolynomial lower bound in the parameter $k(n)$ when space usage is restricted.

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Index Terms

Improving Exhaustive Search Implies Superpolynomial Lower Bounds
1. Theory of computation
  1. Computational complexity and cryptography
    1. Complexity classes
  2. Design and analysis of algorithms

Index terms have been assigned to the content through auto-classification.

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cover image SIAM Journal on Computing

SIAM Journal on Computing Volume 42, Issue 3

^† Special Section on the Forty-Second Annual ACM Symposium on Theory of Computing (STOC 2010)

2013

698 pages

ISSN:0097-5397

DOI:10.1137/smjcat.42.3

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© 2013, Society for Industrial and Applied Mathematics.

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Society for Industrial and Applied Mathematics

United States

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Published: 01 January 2013

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