{"title":"基于不可靠项的可译码概率群测试的改进界","authors":"Sarthak Jain, Martina Cardone, S. Mohajer","doi":"10.1109/ITW55543.2023.10161616","DOIUrl":null,"url":null,"abstract":"This work uses non-adaptive probabilistic group testing to find a set of L defective items out of n items. In contrast to traditional group testing, in the considered setup each item can hide itself (or become inactive) during any given test with probability 1−α and is active with probability α. The authors of [Cheraghchi et al.] proposed an efficiently decodable probabilistic group testing scheme which requires $O\\left( {\\frac{{L\\log (n)}}{{{\\alpha ^3}}}} \\right)$ tests for the per-instance scenario (where the group testing matrix works for any arbitrary, but fixed, set of L defective items) and $O\\left( {\\frac{{{L^2}\\log (n/L)}}{{{\\alpha ^3}}}} \\right)$ tests for the universal scenario (where the same group testing matrix works for all possible defective sets of L items). The contribution of this work is two-fold: (i) with a slight modification in the construction of the group testing matrix proposed by [Cheraghchi et al.], the corresponding bounds on the number of sufficient tests are improved to $O\\left( {\\frac{{L\\log (n)}}{{{\\alpha ^2}}}} \\right)$ and $O\\left( {\\frac{{{L^2}\\log (n/L)}}{{{\\alpha ^2}}}} \\right)$ for the per-instance and universal scenarios respectively, while still using their efficient decoding method; and (ii) it is shown that the same bounds also hold for the fixed pool-size probabilistic group testing scenario, where in every test a fixed number of items are included for testing.","PeriodicalId":439800,"journal":{"name":"2023 IEEE Information Theory Workshop (ITW)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Improved Bounds For Efficiently Decodable Probabilistic Group Testing With Unreliable Items\",\"authors\":\"Sarthak Jain, Martina Cardone, S. Mohajer\",\"doi\":\"10.1109/ITW55543.2023.10161616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work uses non-adaptive probabilistic group testing to find a set of L defective items out of n items. In contrast to traditional group testing, in the considered setup each item can hide itself (or become inactive) during any given test with probability 1−α and is active with probability α. The authors of [Cheraghchi et al.] proposed an efficiently decodable probabilistic group testing scheme which requires $O\\\\left( {\\\\frac{{L\\\\log (n)}}{{{\\\\alpha ^3}}}} \\\\right)$ tests for the per-instance scenario (where the group testing matrix works for any arbitrary, but fixed, set of L defective items) and $O\\\\left( {\\\\frac{{{L^2}\\\\log (n/L)}}{{{\\\\alpha ^3}}}} \\\\right)$ tests for the universal scenario (where the same group testing matrix works for all possible defective sets of L items). The contribution of this work is two-fold: (i) with a slight modification in the construction of the group testing matrix proposed by [Cheraghchi et al.], the corresponding bounds on the number of sufficient tests are improved to $O\\\\left( {\\\\frac{{L\\\\log (n)}}{{{\\\\alpha ^2}}}} \\\\right)$ and $O\\\\left( {\\\\frac{{{L^2}\\\\log (n/L)}}{{{\\\\alpha ^2}}}} \\\\right)$ for the per-instance and universal scenarios respectively, while still using their efficient decoding method; and (ii) it is shown that the same bounds also hold for the fixed pool-size probabilistic group testing scenario, where in every test a fixed number of items are included for testing.\",\"PeriodicalId\":439800,\"journal\":{\"name\":\"2023 IEEE Information Theory Workshop (ITW)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Information Theory Workshop (ITW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITW55543.2023.10161616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Information Theory Workshop (ITW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITW55543.2023.10161616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Bounds For Efficiently Decodable Probabilistic Group Testing With Unreliable Items
This work uses non-adaptive probabilistic group testing to find a set of L defective items out of n items. In contrast to traditional group testing, in the considered setup each item can hide itself (or become inactive) during any given test with probability 1−α and is active with probability α. The authors of [Cheraghchi et al.] proposed an efficiently decodable probabilistic group testing scheme which requires $O\left( {\frac{{L\log (n)}}{{{\alpha ^3}}}} \right)$ tests for the per-instance scenario (where the group testing matrix works for any arbitrary, but fixed, set of L defective items) and $O\left( {\frac{{{L^2}\log (n/L)}}{{{\alpha ^3}}}} \right)$ tests for the universal scenario (where the same group testing matrix works for all possible defective sets of L items). The contribution of this work is two-fold: (i) with a slight modification in the construction of the group testing matrix proposed by [Cheraghchi et al.], the corresponding bounds on the number of sufficient tests are improved to $O\left( {\frac{{L\log (n)}}{{{\alpha ^2}}}} \right)$ and $O\left( {\frac{{{L^2}\log (n/L)}}{{{\alpha ^2}}}} \right)$ for the per-instance and universal scenarios respectively, while still using their efficient decoding method; and (ii) it is shown that the same bounds also hold for the fixed pool-size probabilistic group testing scenario, where in every test a fixed number of items are included for testing.