{"title":"单调NC^1的相关界","authors":"Benjamin Rossman","doi":"10.4230/LIPIcs.CCC.2015.392","DOIUrl":null,"url":null,"abstract":"This paper gives the first correlation bounds under product distributions, including the uniform distribution, against the class mNC1 of polynomial-size O(log n)-depth monotone circuits. Our main theorem, proved using the pathset complexity framework introduced in [56], shows that the average-case k-CYCLE problem (on Erdos-Renyi random graphs with an appropriate edge density) is [EQUATION] hard for mNC1. Combining this result with O'Donnell's hardness amplification theorem [43], we obtain an explicit monotone function of n variables (in the class mSAC1) which is [EQUATION] hard for mNC1 under the uniform distribution for any desired constant e > 0. This bound is nearly best possible, since every monotone function has agreement [EQUATION] with some function in mNC1 [44]. \n \nOur correlation bounds against mNC1 extend smoothly to non-monotone NC1 circuits with a bounded number of negation gates. Using Holley's monotone coupling theorem [30], we prove the following lemma: with respect to any product distribution, if a balanced monotone function f is [EQUATION] hard for monotone circuits of a given size and depth, then f is [EQUATION] hard for (non-monotone) circuits of the same size and depth with at most t negation gates. We thus achieve a lower bound against NC1 circuits with [EQUATION] log n negation gates, improving the previous record of 1/6 log log n [7]. Our bound on negations is \"half\" optimal, since ⌈log(n + 1)⌉ negation gates are known to be fully powerful for NC1 [3, 21].","PeriodicalId":246506,"journal":{"name":"Cybersecurity and Cyberforensics Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Correlation Bounds Against Monotone NC^1\",\"authors\":\"Benjamin Rossman\",\"doi\":\"10.4230/LIPIcs.CCC.2015.392\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper gives the first correlation bounds under product distributions, including the uniform distribution, against the class mNC1 of polynomial-size O(log n)-depth monotone circuits. Our main theorem, proved using the pathset complexity framework introduced in [56], shows that the average-case k-CYCLE problem (on Erdos-Renyi random graphs with an appropriate edge density) is [EQUATION] hard for mNC1. Combining this result with O'Donnell's hardness amplification theorem [43], we obtain an explicit monotone function of n variables (in the class mSAC1) which is [EQUATION] hard for mNC1 under the uniform distribution for any desired constant e > 0. This bound is nearly best possible, since every monotone function has agreement [EQUATION] with some function in mNC1 [44]. \\n \\nOur correlation bounds against mNC1 extend smoothly to non-monotone NC1 circuits with a bounded number of negation gates. Using Holley's monotone coupling theorem [30], we prove the following lemma: with respect to any product distribution, if a balanced monotone function f is [EQUATION] hard for monotone circuits of a given size and depth, then f is [EQUATION] hard for (non-monotone) circuits of the same size and depth with at most t negation gates. We thus achieve a lower bound against NC1 circuits with [EQUATION] log n negation gates, improving the previous record of 1/6 log log n [7]. Our bound on negations is \\\"half\\\" optimal, since ⌈log(n + 1)⌉ negation gates are known to be fully powerful for NC1 [3, 21].\",\"PeriodicalId\":246506,\"journal\":{\"name\":\"Cybersecurity and Cyberforensics Conference\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cybersecurity and Cyberforensics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4230/LIPIcs.CCC.2015.392\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cybersecurity and Cyberforensics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4230/LIPIcs.CCC.2015.392","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper gives the first correlation bounds under product distributions, including the uniform distribution, against the class mNC1 of polynomial-size O(log n)-depth monotone circuits. Our main theorem, proved using the pathset complexity framework introduced in [56], shows that the average-case k-CYCLE problem (on Erdos-Renyi random graphs with an appropriate edge density) is [EQUATION] hard for mNC1. Combining this result with O'Donnell's hardness amplification theorem [43], we obtain an explicit monotone function of n variables (in the class mSAC1) which is [EQUATION] hard for mNC1 under the uniform distribution for any desired constant e > 0. This bound is nearly best possible, since every monotone function has agreement [EQUATION] with some function in mNC1 [44].
Our correlation bounds against mNC1 extend smoothly to non-monotone NC1 circuits with a bounded number of negation gates. Using Holley's monotone coupling theorem [30], we prove the following lemma: with respect to any product distribution, if a balanced monotone function f is [EQUATION] hard for monotone circuits of a given size and depth, then f is [EQUATION] hard for (non-monotone) circuits of the same size and depth with at most t negation gates. We thus achieve a lower bound against NC1 circuits with [EQUATION] log n negation gates, improving the previous record of 1/6 log log n [7]. Our bound on negations is "half" optimal, since ⌈log(n + 1)⌉ negation gates are known to be fully powerful for NC1 [3, 21].