Testing Polynomials over General Fields

In this work we fill the knowledge gap concerning testing polynomials over finite fields. As previous works show, when the cardinality of the field, $q$, is sufficiently larger than the degree bound, $d$, then the number of queries sufficient for testing is polynomial or even linear in $d$. On the o...

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Published inSIAM journal on computing Vol. 36; no. 3; pp. 779 - 802
Main Authors Kaufman, Tali, Ron, Dana
Format Journal Article
LanguageEnglish
Published Philadelphia Society for Industrial and Applied Mathematics 01.01.2006
Subjects
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ISSN0097-5397
1095-7111
DOI10.1137/S0097539704445615

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Abstract In this work we fill the knowledge gap concerning testing polynomials over finite fields. As previous works show, when the cardinality of the field, $q$, is sufficiently larger than the degree bound, $d$, then the number of queries sufficient for testing is polynomial or even linear in $d$. On the other hand, when $q=2$ then the number of queries, both sufficient and necessary, grows exponentially with $d$. Here we study the intermediate case where $2 < q = O(d)$ and show a smooth transition between the two extremes. Specifically, let $p$ be the characteristic of the field (so that $p$ is prime and $q = p^s$ for some integer $s \geq 1$). Then the number of queries performed by the test grows like $\ell\cdot q^{2\ell+1}$, where $\ell = \big\lceil \frac{d+1}{q-q/p}\big\rceil $. Furthermore, $q^{\Omega(\ell)}$ queries are necessary when $q = O(d)$. The test itself provides a unifying view of the tests for these two extremes: it considers random affine subspaces of dimension $\ell$ and verifies that the function restricted to the selected subspaces is a polynomial of degree at most $d$. Viewed in the context of coding theory, our result shows that Reed-Muller codes over general fields (usually referred to as generalized Reed-Muller (GRM) codes) are locally testable. In the course of our analysis we provide a characterization of small-weight words that span the code. Such a characterization was previously known only when the field size is a prime or is sufficiently large, in which case the minimum-weight words span the code.
AbstractList In this work we fill the knowledge gap concerning testing polynomials over finite fields. As previous works show, when the cardinality of the field, $q$, is sufficiently larger than the degree bound, $d$, then the number of queries sufficient for testing is polynomial or even linear in $d$. On the other hand, when $q=2$ then the number of queries, both sufficient and necessary, grows exponentially with $d$. Here we study the intermediate case where $2 < q = O(d)$ and show a smooth transition between the two extremes. Specifically, let $p$ be the characteristic of the field (so that $p$ is prime and $q = p^s$ for some integer $s \geq 1$). Then the number of queries performed by the test grows like $\ell\cdot q^{2\ell+1}$, where $\ell = \big\lceil \frac{d+1}{q-q/p}\big\rceil $. Furthermore, $q^{\Omega(\ell)}$ queries are necessary when $q = O(d)$. The test itself provides a unifying view of the tests for these two extremes: it considers random affine subspaces of dimension $\ell$ and verifies that the function restricted to the selected subspaces is a polynomial of degree at most $d$. Viewed in the context of coding theory, our result shows that Reed-Muller codes over general fields (usually referred to as generalized Reed-Muller (GRM) codes) are locally testable. In the course of our analysis we provide a characterization of small-weight words that span the code. Such a characterization was previously known only when the field size is a prime or is sufficiently large, in which case the minimum-weight words span the code.
Author Kaufman, Tali
Ron, Dana
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10.1145/226643.226652
10.1109/TIT.2005.856958
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10.1016/0022-0000(93)90044-W
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10.1007/s00453-001-0078-7
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Snippet In this work we fill the knowledge gap concerning testing polynomials over finite fields. As previous works show, when the cardinality of the field, $q$, is...
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SubjectTerms Algorithms
Coding theory
Computer science
Polynomials
Queries
Title Testing Polynomials over General Fields
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