{"title":"Quantum Speed-ups for String Synchronizing Sets, Longest Common Substring, and \\(k\\) -mismatch Matching","authors":"Ce Jin, Jakob Nogler","doi":"10.1145/3672395","DOIUrl":null,"url":null,"abstract":"<p><i>Longest Common Substring (LCS)</i> is an important text processing problem, which has recently been investigated in the quantum query model. The decision version of this problem, <i>LCS with threshold \\(d\\)</i>, asks whether two length-\\(n\\) input strings have a common substring of length \\(d\\). The two extreme cases, \\(d=1\\) and \\(d=n\\), correspond respectively to Element Distinctness and Unstructured Search, two fundamental problems in quantum query complexity. However, the intermediate case \\(1\\ll d\\ll n\\) was not fully understood.</p><p>We show that the complexity of LCS with threshold \\(d\\) smoothly interpolates between the two extreme cases up to \\(n^{o(1)}\\) factors:\n<p><ul><li><p>LCS with threshold \\(d\\) has a quantum algorithm in \\(n^{2/3+o(1)}/d^{1/6}\\) query complexity and time complexity, and requires at least \\(\\Omega(n^{2/3}/d^{1/6})\\) quantum query complexity.</p></li></ul></p></p><p>Our result improves upon previous upper bounds \\(\\tilde{O}(\\min\\{n/d^{1/2},n^{2/3}\\})\\) (Le Gall and Seddighin ITCS 2022, Akmal and Jin SODA 2022), and answers an open question of Akmal and Jin.</p><p>Our main technical contribution is a quantum speed-up of the powerful <i>String Synchronizing Set</i> technique introduced by Kempa and Kociumaka (STOC 2019). It consistently samples \\(n/\\tau^{1-o(1)}\\) synchronizing positions in the string depending on their length-\\(\\Theta(\\tau)\\) contexts, and each synchronizing position can be reported by a quantum algorithm in \\(\\tilde{O}(\\tau^{1/2+o(1)})\\) time. Our quantum string synchronizing set also yields a near-optimal LCE data structure in the quantum setting.</p><p>As another application of our quantum string synchronizing set, we study the <i>\\(k\\)-mismatch Matching</i> problem, which asks if the pattern has an occurrence in the text with at most \\(k\\) Hamming mismatches. Using a structural result of Charalampopoulos, Kociumaka, and Wellnitz (FOCS 2020), we obtain:\n<p><ul><li><p>\\(k\\)-mismatch matching has a quantum algorithm with \\(k^{3/4}n^{1/2+o(1)}\\) query complexity and \\(\\tilde{O}(kn^{1/2})\\) time complexity. We also observe a non-matching quantum query lower bound of \\(\\Omega(\\sqrt{kn})\\).</p></li></ul></p></p>","PeriodicalId":50922,"journal":{"name":"ACM Transactions on Algorithms","volume":"9 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Algorithms","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3672395","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Longest Common Substring (LCS) is an important text processing problem, which has recently been investigated in the quantum query model. The decision version of this problem, LCS with threshold \(d\), asks whether two length-\(n\) input strings have a common substring of length \(d\). The two extreme cases, \(d=1\) and \(d=n\), correspond respectively to Element Distinctness and Unstructured Search, two fundamental problems in quantum query complexity. However, the intermediate case \(1\ll d\ll n\) was not fully understood.
We show that the complexity of LCS with threshold \(d\) smoothly interpolates between the two extreme cases up to \(n^{o(1)}\) factors:
LCS with threshold \(d\) has a quantum algorithm in \(n^{2/3+o(1)}/d^{1/6}\) query complexity and time complexity, and requires at least \(\Omega(n^{2/3}/d^{1/6})\) quantum query complexity.
Our result improves upon previous upper bounds \(\tilde{O}(\min\{n/d^{1/2},n^{2/3}\})\) (Le Gall and Seddighin ITCS 2022, Akmal and Jin SODA 2022), and answers an open question of Akmal and Jin.
Our main technical contribution is a quantum speed-up of the powerful String Synchronizing Set technique introduced by Kempa and Kociumaka (STOC 2019). It consistently samples \(n/\tau^{1-o(1)}\) synchronizing positions in the string depending on their length-\(\Theta(\tau)\) contexts, and each synchronizing position can be reported by a quantum algorithm in \(\tilde{O}(\tau^{1/2+o(1)})\) time. Our quantum string synchronizing set also yields a near-optimal LCE data structure in the quantum setting.
As another application of our quantum string synchronizing set, we study the \(k\)-mismatch Matching problem, which asks if the pattern has an occurrence in the text with at most \(k\) Hamming mismatches. Using a structural result of Charalampopoulos, Kociumaka, and Wellnitz (FOCS 2020), we obtain:
\(k\)-mismatch matching has a quantum algorithm with \(k^{3/4}n^{1/2+o(1)}\) query complexity and \(\tilde{O}(kn^{1/2})\) time complexity. We also observe a non-matching quantum query lower bound of \(\Omega(\sqrt{kn})\).
期刊介绍:
ACM Transactions on Algorithms welcomes submissions of original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis. Most welcome are new algorithms and data structures, new and improved analyses, and complexity results. Specific areas of computation covered by the journal include
combinatorial searches and objects;
counting;
discrete optimization and approximation;
randomization and quantum computation;
parallel and distributed computation;
algorithms for
graphs,
geometry,
arithmetic,
number theory,
strings;
on-line analysis;
cryptography;
coding;
data compression;
learning algorithms;
methods of algorithmic analysis;
discrete algorithms for application areas such as
biology,
economics,
game theory,
communication,
computer systems and architecture,
hardware design,
scientific computing