{"title":"Linear Space Data Structures for Finite Groups with Constant Query-Time","authors":"Bireswar Das, Anant Kumar, Shivdutt Sharma, Dhara Thakkar","doi":"10.1007/s00453-024-01212-9","DOIUrl":null,"url":null,"abstract":"<div><p>A finite group of order <i>n</i> can be represented by its Cayley table. In the word-RAM model the Cayley table of a group of order <i>n</i> can be stored using <span>\\(O(n^2)\\)</span> words and can be used to answer a multiplication query in constant time. It is interesting to ask if we can design a data structure to store a group of order <i>n</i> that uses <span>\\(o(n^2)\\)</span> space but can still answer a multiplication query in constant time. Das et al. (J Comput Syst Sci 114:137–146, 2020) showed that for any finite group <i>G</i> of order <i>n</i> and for any <span>\\(\\delta \\in [1/\\log {n}, 1]\\)</span>, a data structure can be constructed for <i>G</i> that uses <span>\\(O(n^{1+\\delta }/\\delta )\\)</span> space and answers a multiplication query in time <span>\\(O(1/\\delta )\\)</span>. Farzan and Munro (ISSAC, 2006) gave an information theoretic lower bound of <span>\\(\\Omega (n)\\)</span> on the number of words to store a group of order <i>n</i>. We design a constant query-time data structure that can store any finite group using <i>O</i>(<i>n</i>) words where <i>n</i> is the order of the group. Since our data structure achieves the information theoretic lower bound and answers queries in constant time, it is optimal in both space usage and query-time. A crucial step in the process is essentially to design linear space and constant query-time data structures for nonabelian simple groups. The data structures for nonabelian simple groups are designed using a lemma that we prove using the Classification Theorem for Finite Simple Groups.</p></div>","PeriodicalId":50824,"journal":{"name":"Algorithmica","volume":"86 6","pages":"1979 - 2025"},"PeriodicalIF":0.9000,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithmica","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s00453-024-01212-9","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
A finite group of order n can be represented by its Cayley table. In the word-RAM model the Cayley table of a group of order n can be stored using \(O(n^2)\) words and can be used to answer a multiplication query in constant time. It is interesting to ask if we can design a data structure to store a group of order n that uses \(o(n^2)\) space but can still answer a multiplication query in constant time. Das et al. (J Comput Syst Sci 114:137–146, 2020) showed that for any finite group G of order n and for any \(\delta \in [1/\log {n}, 1]\), a data structure can be constructed for G that uses \(O(n^{1+\delta }/\delta )\) space and answers a multiplication query in time \(O(1/\delta )\). Farzan and Munro (ISSAC, 2006) gave an information theoretic lower bound of \(\Omega (n)\) on the number of words to store a group of order n. We design a constant query-time data structure that can store any finite group using O(n) words where n is the order of the group. Since our data structure achieves the information theoretic lower bound and answers queries in constant time, it is optimal in both space usage and query-time. A crucial step in the process is essentially to design linear space and constant query-time data structures for nonabelian simple groups. The data structures for nonabelian simple groups are designed using a lemma that we prove using the Classification Theorem for Finite Simple Groups.
期刊介绍:
Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential.
Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming.
In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.