{"title":"小素数域上多元多项式的最优检验","authors":"Elad Haramaty, Amir Shpilka, M. Sudan","doi":"10.1137/120879257","DOIUrl":null,"url":null,"abstract":"We consider the problem of testing if a given function $f : \\F_q^n \\right arrow \\F_q$ is close to a $n$-variate degree $d$ polynomial over the finite field $\\F_q$ of $q$elements. The natural, low-query, test for this property would be to pick the smallest dimension $t = t_{q,d}\\approx d/q$ such that every function of degree greater than $d$reveals this aspect on {\\em some} $t$-dimensional affine subspace of $\\F_q^n$ and to test that $f$ when restricted to a {\\em random} $t$-dimensional affine subspace is a polynomial of degree at most $d$ on this subspace. Such a test makes only $q^t$ queries, independent of $n$. Previous works, by Alon et al.~\\cite{AKKLR}, and Kaufman and Ron~\\cite{KaufmanRon06} and Jutla et al.~\\cite{JPRZ04}, showed that this natural test rejected functions that were$\\Omega(1)$-far from degree $d$-polynomials with probability at least $\\Omega(q^{-t})$. (The initial work~\\cite{AKKLR} considered only the case of $q=2$, while the work~\\cite{JPRZ04}only considered the case of prime $q$. The results in \\cite{KaufmanRon06} hold for all fields.) Thus to get a constant probability of detecting functions that are at constant distance from the space of degree $d$ polynomials, the tests made $q^{2t}$ queries. Kaufman and Ron also noted that when $q$ is prime, then $q^t$ queries are necessary. Thus these tests were off by at least a quadratic factor from known lower bounds. Bhattacharyya et al.~\\cite{BKSSZ10} gave an optimal analysis of this test for the case of the binary field and showed that the natural test actually rejects functions that were $\\Omega(1)$-far from degree $d$-polynomials with probability$\\Omega(1)$. In this work we extend this result for all fields showing that the natural test does indeed reject functions that are $\\Omega(1)$-far from degree $d$ polynomials with$\\Omega(1)$-probability, where the constants depend only on $q$ the field size. Thus our analysis thus shows that this test is optimal (matches known lower bounds) when $q$ is prime. The main technical ingredient in our work is a tight analysis of the number of ``hyper planes'' (affine subspaces of co-dimension $1$) on which the restriction of a degree $d$polynomial has degree less than $d$. We show that the number of such hyper planes is at most $O(q^{t_{q,d}})$ -- which is tight to within constant factors.","PeriodicalId":326048,"journal":{"name":"2011 IEEE 52nd Annual Symposium on Foundations of Computer Science","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Optimal Testing of Multivariate Polynomials over Small Prime Fields\",\"authors\":\"Elad Haramaty, Amir Shpilka, M. Sudan\",\"doi\":\"10.1137/120879257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of testing if a given function $f : \\\\F_q^n \\\\right arrow \\\\F_q$ is close to a $n$-variate degree $d$ polynomial over the finite field $\\\\F_q$ of $q$elements. The natural, low-query, test for this property would be to pick the smallest dimension $t = t_{q,d}\\\\approx d/q$ such that every function of degree greater than $d$reveals this aspect on {\\\\em some} $t$-dimensional affine subspace of $\\\\F_q^n$ and to test that $f$ when restricted to a {\\\\em random} $t$-dimensional affine subspace is a polynomial of degree at most $d$ on this subspace. Such a test makes only $q^t$ queries, independent of $n$. Previous works, by Alon et al.~\\\\cite{AKKLR}, and Kaufman and Ron~\\\\cite{KaufmanRon06} and Jutla et al.~\\\\cite{JPRZ04}, showed that this natural test rejected functions that were$\\\\Omega(1)$-far from degree $d$-polynomials with probability at least $\\\\Omega(q^{-t})$. (The initial work~\\\\cite{AKKLR} considered only the case of $q=2$, while the work~\\\\cite{JPRZ04}only considered the case of prime $q$. The results in \\\\cite{KaufmanRon06} hold for all fields.) Thus to get a constant probability of detecting functions that are at constant distance from the space of degree $d$ polynomials, the tests made $q^{2t}$ queries. Kaufman and Ron also noted that when $q$ is prime, then $q^t$ queries are necessary. Thus these tests were off by at least a quadratic factor from known lower bounds. Bhattacharyya et al.~\\\\cite{BKSSZ10} gave an optimal analysis of this test for the case of the binary field and showed that the natural test actually rejects functions that were $\\\\Omega(1)$-far from degree $d$-polynomials with probability$\\\\Omega(1)$. In this work we extend this result for all fields showing that the natural test does indeed reject functions that are $\\\\Omega(1)$-far from degree $d$ polynomials with$\\\\Omega(1)$-probability, where the constants depend only on $q$ the field size. Thus our analysis thus shows that this test is optimal (matches known lower bounds) when $q$ is prime. The main technical ingredient in our work is a tight analysis of the number of ``hyper planes'' (affine subspaces of co-dimension $1$) on which the restriction of a degree $d$polynomial has degree less than $d$. We show that the number of such hyper planes is at most $O(q^{t_{q,d}})$ -- which is tight to within constant factors.\",\"PeriodicalId\":326048,\"journal\":{\"name\":\"2011 IEEE 52nd Annual Symposium on Foundations of Computer Science\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 52nd Annual Symposium on Foundations of Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1137/120879257\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 52nd Annual Symposium on Foundations of Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/120879257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Testing of Multivariate Polynomials over Small Prime Fields
We consider the problem of testing if a given function $f : \F_q^n \right arrow \F_q$ is close to a $n$-variate degree $d$ polynomial over the finite field $\F_q$ of $q$elements. The natural, low-query, test for this property would be to pick the smallest dimension $t = t_{q,d}\approx d/q$ such that every function of degree greater than $d$reveals this aspect on {\em some} $t$-dimensional affine subspace of $\F_q^n$ and to test that $f$ when restricted to a {\em random} $t$-dimensional affine subspace is a polynomial of degree at most $d$ on this subspace. Such a test makes only $q^t$ queries, independent of $n$. Previous works, by Alon et al.~\cite{AKKLR}, and Kaufman and Ron~\cite{KaufmanRon06} and Jutla et al.~\cite{JPRZ04}, showed that this natural test rejected functions that were$\Omega(1)$-far from degree $d$-polynomials with probability at least $\Omega(q^{-t})$. (The initial work~\cite{AKKLR} considered only the case of $q=2$, while the work~\cite{JPRZ04}only considered the case of prime $q$. The results in \cite{KaufmanRon06} hold for all fields.) Thus to get a constant probability of detecting functions that are at constant distance from the space of degree $d$ polynomials, the tests made $q^{2t}$ queries. Kaufman and Ron also noted that when $q$ is prime, then $q^t$ queries are necessary. Thus these tests were off by at least a quadratic factor from known lower bounds. Bhattacharyya et al.~\cite{BKSSZ10} gave an optimal analysis of this test for the case of the binary field and showed that the natural test actually rejects functions that were $\Omega(1)$-far from degree $d$-polynomials with probability$\Omega(1)$. In this work we extend this result for all fields showing that the natural test does indeed reject functions that are $\Omega(1)$-far from degree $d$ polynomials with$\Omega(1)$-probability, where the constants depend only on $q$ the field size. Thus our analysis thus shows that this test is optimal (matches known lower bounds) when $q$ is prime. The main technical ingredient in our work is a tight analysis of the number of ``hyper planes'' (affine subspaces of co-dimension $1$) on which the restriction of a degree $d$polynomial has degree less than $d$. We show that the number of such hyper planes is at most $O(q^{t_{q,d}})$ -- which is tight to within constant factors.