{"title":"SOS lower bound for exact planted clique","authors":"Shuo Pang","doi":"10.4230/LIPIcs.CCC.2021.26","DOIUrl":null,"url":null,"abstract":"We prove a SOS degree lower bound for the planted clique problem on the Erdös-Rényi random graph G(n, 1/2). The bound we get is degree d = Ω(ϵ2 log n/ log log n) for clique size ω = n1/2−ϵ, which is almost tight. This improves the result of [5] for the \"soft\" version of the problem, where the family of the equality-axioms generated by x1 + ... + xn = ω is relaxed to one inequality x1 + ... + xn ≥ ω. As a technical by-product, we also \"naturalize\" certain techniques that were developed and used for the relaxed problem. This includes a new way to define the pseudo-expectation, and a more robust method to solve out the coarse diagonalization of the moment matrix.","PeriodicalId":336911,"journal":{"name":"Proceedings of the 36th Computational Complexity Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 36th Computational Complexity Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4230/LIPIcs.CCC.2021.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
We prove a SOS degree lower bound for the planted clique problem on the Erdös-Rényi random graph G(n, 1/2). The bound we get is degree d = Ω(ϵ2 log n/ log log n) for clique size ω = n1/2−ϵ, which is almost tight. This improves the result of [5] for the "soft" version of the problem, where the family of the equality-axioms generated by x1 + ... + xn = ω is relaxed to one inequality x1 + ... + xn ≥ ω. As a technical by-product, we also "naturalize" certain techniques that were developed and used for the relaxed problem. This includes a new way to define the pseudo-expectation, and a more robust method to solve out the coarse diagonalization of the moment matrix.