Mahdi Cheraghchi, Shuichi Hirahara, Dimitrios Myrisiotis, Yuichi Yoshida
{"title":"单带图灵机与MCSP的分支程序下界","authors":"Mahdi Cheraghchi, Shuichi Hirahara, Dimitrios Myrisiotis, Yuichi Yoshida","doi":"10.1007/s00224-022-10113-9","DOIUrl":null,"url":null,"abstract":"<p>For a size parameter <span>\\(s:\\mathbb {N}\\to \\mathbb {N}\\)</span>, the Minimum Circuit Size Problem (denoted by MCSP[<i>s</i>(<i>n</i>)]) is the problem of deciding whether the minimum circuit size of a given function <i>f</i> : {0,1}<sup><i>n</i></sup> →{0,1} (represented by a string of length <i>N</i> := 2<sup><i>n</i></sup>) is at most a threshold <i>s</i>(<i>n</i>). 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 <i>μ</i><sub>1</sub> > 0, if <span>\\(\\text {MCSP}[2^{\\mu _{1}\\cdot n}]\\)</span> cannot be computed by a one-tape Turing machine (with an additional one-way read-only input tape) running in time <i>N</i><sup>1.01</sup>, 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 <span>\\(\\text {MCSP}[2^{\\mu _{2}\\cdot n}]\\)</span> in time <i>N</i><sup>1.99</sup>, for some constant <i>μ</i><sub>2</sub> > <i>μ</i><sub>1</sub>. (2) A non-deterministic (or parity) branching program of size <span>\\(o(N^{1.5}/\\log N)\\)</span> 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 <span>\\(N^{1.5-o\\left (1\\right )}\\)</span>. 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 <span>\\(\\widetilde {O}(\\sqrt {N})\\)</span> secure against read-once polynomial-size non-deterministic branching programs on <i>N</i>-bit inputs. (2) Any read-once co-non-deterministic branching program computing MCSP must have size at least <span>\\(2^{\\widetilde {\\Omega }(N)}\\)</span>.</p>","PeriodicalId":22832,"journal":{"name":"Theory of Computing Systems","volume":"223 ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"One-Tape Turing Machine and Branching Program Lower Bounds for MCSP\",\"authors\":\"Mahdi Cheraghchi, Shuichi Hirahara, Dimitrios Myrisiotis, Yuichi Yoshida\",\"doi\":\"10.1007/s00224-022-10113-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>For a size parameter <span>\\\\(s:\\\\mathbb {N}\\\\to \\\\mathbb {N}\\\\)</span>, the Minimum Circuit Size Problem (denoted by MCSP[<i>s</i>(<i>n</i>)]) is the problem of deciding whether the minimum circuit size of a given function <i>f</i> : {0,1}<sup><i>n</i></sup> →{0,1} (represented by a string of length <i>N</i> := 2<sup><i>n</i></sup>) is at most a threshold <i>s</i>(<i>n</i>). 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 <i>μ</i><sub>1</sub> > 0, if <span>\\\\(\\\\text {MCSP}[2^{\\\\mu _{1}\\\\cdot n}]\\\\)</span> cannot be computed by a one-tape Turing machine (with an additional one-way read-only input tape) running in time <i>N</i><sup>1.01</sup>, 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 <span>\\\\(\\\\text {MCSP}[2^{\\\\mu _{2}\\\\cdot n}]\\\\)</span> in time <i>N</i><sup>1.99</sup>, for some constant <i>μ</i><sub>2</sub> > <i>μ</i><sub>1</sub>. (2) A non-deterministic (or parity) branching program of size <span>\\\\(o(N^{1.5}/\\\\log N)\\\\)</span> 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 <span>\\\\(N^{1.5-o\\\\left (1\\\\right )}\\\\)</span>. 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 <span>\\\\(\\\\widetilde {O}(\\\\sqrt {N})\\\\)</span> secure against read-once polynomial-size non-deterministic branching programs on <i>N</i>-bit inputs. (2) Any read-once co-non-deterministic branching program computing MCSP must have size at least <span>\\\\(2^{\\\\widetilde {\\\\Omega }(N)}\\\\)</span>.</p>\",\"PeriodicalId\":22832,\"journal\":{\"name\":\"Theory of Computing Systems\",\"volume\":\"223 \",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-12-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory of Computing Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s00224-022-10113-9\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory of Computing Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00224-022-10113-9","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
One-Tape Turing Machine and Branching Program Lower Bounds for MCSP
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 \(2^{\widetilde {\Omega }(N)}\).
期刊介绍:
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