{"title":"傅里叶-熵-影响猜想的一个新界","authors":"Xiao Han","doi":"10.1007/s00493-024-00133-z","DOIUrl":null,"url":null,"abstract":"<p>In this paper, we prove that the Fourier entropy of an <i>n</i>-dimensional boolean function <i>f</i> can be upper-bounded by <span>\\(O(I(f)+ \\sum \\limits _{k\\in [n]}I_k(f)\\log \\frac{1}{I_k(f)})\\)</span>, where <i>I</i>(<i>f</i>) is its total influence and <span>\\(I_k(f)\\)</span> is the influence of the <i>k</i>-th coordinate. There is no strict quantitative relationship between our bound with the known bounds for the Fourier-Min-Entropy-Influence conjecture <span>\\(O(I(f)\\log I(f))\\)</span> and <span>\\(O(I(f)^2)\\)</span>. The proof is elementary and uses iterative bounds on moments of Fourier coefficients over different levels to estimate the Fourier entropy as its derivative.</p>","PeriodicalId":50666,"journal":{"name":"Combinatorica","volume":"69 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Bound for the Fourier-Entropy-Influence Conjecture\",\"authors\":\"Xiao Han\",\"doi\":\"10.1007/s00493-024-00133-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this paper, we prove that the Fourier entropy of an <i>n</i>-dimensional boolean function <i>f</i> can be upper-bounded by <span>\\\\(O(I(f)+ \\\\sum \\\\limits _{k\\\\in [n]}I_k(f)\\\\log \\\\frac{1}{I_k(f)})\\\\)</span>, where <i>I</i>(<i>f</i>) is its total influence and <span>\\\\(I_k(f)\\\\)</span> is the influence of the <i>k</i>-th coordinate. There is no strict quantitative relationship between our bound with the known bounds for the Fourier-Min-Entropy-Influence conjecture <span>\\\\(O(I(f)\\\\log I(f))\\\\)</span> and <span>\\\\(O(I(f)^2)\\\\)</span>. The proof is elementary and uses iterative bounds on moments of Fourier coefficients over different levels to estimate the Fourier entropy as its derivative.</p>\",\"PeriodicalId\":50666,\"journal\":{\"name\":\"Combinatorica\",\"volume\":\"69 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Combinatorica\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s00493-024-00133-z\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Combinatorica","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s00493-024-00133-z","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS","Score":null,"Total":0}
A New Bound for the Fourier-Entropy-Influence Conjecture
In this paper, we prove that the Fourier entropy of an n-dimensional boolean function f can be upper-bounded by \(O(I(f)+ \sum \limits _{k\in [n]}I_k(f)\log \frac{1}{I_k(f)})\), where I(f) is its total influence and \(I_k(f)\) is the influence of the k-th coordinate. There is no strict quantitative relationship between our bound with the known bounds for the Fourier-Min-Entropy-Influence conjecture \(O(I(f)\log I(f))\) and \(O(I(f)^2)\). The proof is elementary and uses iterative bounds on moments of Fourier coefficients over different levels to estimate the Fourier entropy as its derivative.
期刊介绍:
COMBINATORICA publishes research papers in English in a variety of areas of combinatorics and the theory of computing, with particular emphasis on general techniques and unifying principles. Typical but not exclusive topics covered by COMBINATORICA are
- Combinatorial structures (graphs, hypergraphs, matroids, designs, permutation groups).
- Combinatorial optimization.
- Combinatorial aspects of geometry and number theory.
- Algorithms in combinatorics and related fields.
- Computational complexity theory.
- Randomization and explicit construction in combinatorics and algorithms.