{"title":"AC0 Unpredictability","authors":"Emanuele Viola","doi":"10.1145/3442362","DOIUrl":null,"url":null,"abstract":"We prove that for every distribution D on n bits with Shannon entropy ≥ n − a, at most O(2da logd+1g)/γ5 of the bits Di can be predicted with advantage γ by an AC0 circuit of size g and depth D that is a function of all of the bits of D except Di. This answers a question by Meir and Wigderson, who proved a corresponding result for decision trees. We also show that there are distributions D with entropy ≥ n − O(1) such that any subset of O(n/ log n) bits of D on can be distinguished from uniform by a circuit of depth 2 and size poly(n). This separates the notions of predictability and distinguishability in this context.","PeriodicalId":198744,"journal":{"name":"ACM Transactions on Computation Theory (TOCT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Computation Theory (TOCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3442362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We prove that for every distribution D on n bits with Shannon entropy ≥ n − a, at most O(2da logd+1g)/γ5 of the bits Di can be predicted with advantage γ by an AC0 circuit of size g and depth D that is a function of all of the bits of D except Di. This answers a question by Meir and Wigderson, who proved a corresponding result for decision trees. We also show that there are distributions D with entropy ≥ n − O(1) such that any subset of O(n/ log n) bits of D on can be distinguished from uniform by a circuit of depth 2 and size poly(n). This separates the notions of predictability and distinguishability in this context.