One-Tape Turing Machine and Branching Program Lower Bounds for MCSP

IF 0.6 4区 计算机科学 Q4 COMPUTER SCIENCE, THEORY & METHODS
Mahdi Cheraghchi, Shuichi Hirahara, Dimitrios Myrisiotis, Yuichi Yoshida
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引用次数: 0

Abstract

For a size parameter \(s:\mathbb {N}\to \mathbb {N}\), the Minimum Circuit Size Problem (denoted by MCSP[s(n)]) is the problem of deciding whether the minimum circuit size of a given function f : {0,1}n →{0,1} (represented by a string of length N := 2n) is at most a threshold s(n). A recent line of work exhibited “hardness magnification” phenomena for MCSP: A very weak lower bound for MCSP implies a breakthrough result in complexity theory. For example, McKay, Murray, and Williams (STOC 2019) implicitly showed that, for some constant μ1 > 0, if \(\text {MCSP}[2^{\mu _{1}\cdot n}]\) cannot be computed by a one-tape Turing machine (with an additional one-way read-only input tape) running in time N1.01, then P≠NP. In this paper, we present the following new lower bounds against one-tape Turing machines and branching programs: (1) A randomized two-sided error one-tape Turing machine (with an additional one-way read-only input tape) cannot compute \(\text {MCSP}[2^{\mu _{2}\cdot n}]\) in time N1.99, for some constant μ2 > μ1. (2) A non-deterministic (or parity) branching program of size \(o(N^{1.5}/\log N)\) cannot compute MKTP, which is a time-bounded Kolmogorov complexity analogue of MCSP. This is shown by directly applying the Nečiporuk method to MKTP, which previously appeared to be difficult. (3) The size of any non-deterministic, co-non-deterministic, or parity branching program computing MCSP is at least \(N^{1.5-o\left (1\right )}\). These results are the first non-trivial lower bounds for MCSP and MKTP against one-tape Turing machines and non-deterministic branching programs, and essentially match the best-known lower bounds for any explicit functions against these computational models. The first result is based on recent constructions of pseudorandom generators for read-once oblivious branching programs (ROBPs) and combinatorial rectangles (Forbes and Kelley, FOCS 2018; Viola, Electron. Colloq. Comput. Complexity (ECCC) 26, 51, 2019). En route, we obtain several related results: (1) There exists a (local) hitting set generator with seed length \(\widetilde {O}(\sqrt {N})\) secure against read-once polynomial-size non-deterministic branching programs on N-bit inputs. (2) Any read-once co-non-deterministic branching program computing MCSP must have size at least \(2^{\widetilde {\Omega }(N)}\).

单带图灵机与MCSP的分支程序下界
对于尺寸参数\(s:\mathbb {N}\to \mathbb {N}\),最小电路尺寸问题(用MCSP[s(n)]表示)是确定给定函数f: 0,1n→{0,1}(由长度n:= 2n的字符串表示)的最小电路尺寸是否最多为阈值s(n)的问题。最近的一项研究显示了MCSP的“硬度放大”现象:MCSP的一个非常弱的下界意味着复杂性理论的一个突破性结果。例如,McKay, Murray, and Williams (STOC 2019)隐式地表明,对于某个常数μ1 &gt; 0,如果在N1.01时间运行的单磁带图灵机(带有额外的单向只读输入磁带)无法计算{}\(\text {MCSP}[2^{\mu _{1}\cdot n}]\),则P≠NP。本文给出了单带图灵机和分支程序的新的下界:(1)随机双侧误差单带图灵机(带有一个额外的单向只读输入磁带)不能在N1.99时间内计算\(\text {MCSP}[2^{\mu _{2}\cdot n}]\),对于某个常数μ2 &gt;μ1;(2)一个大小为\(o(N^{1.5}/\log N)\)的非确定性(或奇偶性)分支程序不能计算MKTP, MKTP是MCSP的一个有时间限制的Kolmogorov复杂度模拟。这可以通过直接应用ne iporuk方法来证明,这在以前看来是困难的。(3)计算MCSP的任何非确定性、共非确定性或奇偶性分支程序的大小至少为\(N^{1.5-o\left (1\right )}\)。这些结果是针对单带图灵机和非确定性分支程序的MCSP和MKTP的第一个非平凡下界,并且基本上与针对这些计算模型的任何显式函数的最著名的下界相匹配。第一个结果是基于最近构建的用于读取一次无关分支程序(robp)和组合矩形的伪随机生成器(Forbes和Kelley, FOCS 2018;维奥拉,电子。口语:计算机。复杂性(ECCC) 26, 51, 2019)。在此过程中,我们得到了几个相关的结果:(1)存在一个(局部)命中集生成器,其种子长度为\(\widetilde {O}(\sqrt {N})\),可以防止在n位输入上读取一次多项式大小的不确定性分支程序。(2)任何计算MCSP的只读一次共不确定性分支程序的大小必须至少为\(2^{\widetilde {\Omega }(N)}\)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Theory of Computing Systems
Theory of Computing Systems 工程技术-计算机:理论方法
CiteScore
1.90
自引率
0.00%
发文量
36
审稿时长
6-12 weeks
期刊介绍: TOCS is devoted to publishing original research from all areas of theoretical computer science, ranging from foundational areas such as computational complexity, to fundamental areas such as algorithms and data structures, to focused areas such as parallel and distributed algorithms and architectures.
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