对于[数学]电路而言,非确定性准多项式时间是平均情况下的难点

IF 1.2 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS SIAM Journal on Computing Pub Date : 2024-02-23 DOI:10.1137/20m1321231
Lijie Chen
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引用次数: 0

摘要

SIAM 计算期刊》,提前印刷。 摘要继[R. R. Williams, J. ACM, 61 (2014)]的开创性工作之后,[C. D. Murray and R. R. Williams, STOC 2018]最近又有突破性进展,证明了[math](非确定性准多项式时间)不存在多项式大小的[math]电路(由固定常数[math]的[math]/[math]/[math]门组成的恒定深度电路,是电路复杂性的前沿类)。我们通过证明对于所有常数[math],[math]中存在一种语言无法用多项式大小的[math]电路来[math]逼近,从而将上述下界强化为平均情况下的下界。我们的工作还改进了 [R. Chen, I. C. Oliveira, and R. Santhanam, LATIN 2018, pp.我们的新下界建立在几个有趣的组成部分之上,包括以下内容:1.巴林顿定理和随机自还原的[数学]完全语言的存在。2.R. R. Williams, SIAM J. Comput., 45 (2016), pp.3.一个 "几乎 "几乎无处不在的[数学]平均情况下界(它加强了[C. D. Murray and R. R. Williams, STOC 2018]中相应的最坏情况下界)。4.一种[math]完备语言,它是向下自可还原的、同长可检查的、可纠错的和可填充的。此外,它的所有可还原性都有相应的低深度非适应性甲骨文电路。我们的构造建立在 [L. Trevisan 和 S. P. Vadhan, Comput. Complexity, 16 (2007), pp.]与其他通过 "算法方法 "证明的下界一样,我们所利用的 [math] 的唯一属性是 [math] 存在一个非难 [math] 算法 [R. R. Williams, J. ACM, 61 (2014)]。因此,对于任何典型的电路类[math],如果发现了[math]的非难[math](事实上是[math])算法,我们的结果也适用于[math]。
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Nondeterministic Quasi-Polynomial Time is Average-Case Hard for [math] Circuits
SIAM Journal on Computing, Ahead of Print.
Abstract. Following the seminal work of [R. R. Williams, J. ACM, 61 (2014)], in a recent breakthrough, [C. D. Murray and R. R. Williams, STOC 2018] proved that [math] (nondeterministic quasi-polynomial time) does not have polynomial-size [math] circuits (constant depth circuits consisting of [math]/[math]/[math] gates for a fixed constant [math], a frontier class in circuit complexity). We strengthen the above lower bound to an average-case one, by proving that for all constants [math], there is a language in [math] that cannot be [math]-approximated by polynomial-size [math] circuits. Our work also improves the average-case lower bound for [math] against polynomial-size [math] circuits by [R. Chen, I. C. Oliveira, and R. Santhanam, LATIN 2018, pp. 317–330]. Our new lower bound builds on several interesting components, including the following: 1. Barrington’s theorem and the existence of an [math]-complete language that is random self-reducible. 2. The subexponential witness-size lower bound for [math] against [math] and the conditional nondeterministic pseudorandom generator (PRG) construction in [R. R. Williams, SIAM J. Comput., 45 (2016), pp. 497–529]. 3. An “almost” almost-everywhere [math] average-case lower bound (which strengthens the corresponding worst-case lower bound in [C. D. Murray and R. R. Williams, STOC 2018]). 4. A [math]-complete language that is downward self-reducible, same-length checkable, error-correctable, and paddable. Moreover, all its reducibility properties have corresponding low-depth nonadaptive oracle circuits. Our construction builds on [L. Trevisan and S. P. Vadhan, Comput. Complexity, 16 (2007), pp. 331–364]. Like other lower bounds proved via the “algorithmic approach,” the only property of [math] exploited by us is the existence of a nontrivial [math] algorithm for [math] [R. R. Williams, J. ACM, 61 (2014)]. Therefore, for any typical circuit class [math], our results apply to [math] as well if a nontrivial [math] (in fact, [math]) algorithm for [math] is discovered.
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来源期刊
SIAM Journal on Computing
SIAM Journal on Computing 工程技术-计算机:理论方法
CiteScore
4.60
自引率
0.00%
发文量
68
审稿时长
6-12 weeks
期刊介绍: The SIAM Journal on Computing aims to provide coverage of the most significant work going on in the mathematical and formal aspects of computer science and nonnumerical computing. Submissions must be clearly written and make a significant technical contribution. Topics include but are not limited to analysis and design of algorithms, algorithmic game theory, data structures, computational complexity, computational algebra, computational aspects of combinatorics and graph theory, computational biology, computational geometry, computational robotics, the mathematical aspects of programming languages, artificial intelligence, computational learning, databases, information retrieval, cryptography, networks, distributed computing, parallel algorithms, and computer architecture.
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