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          <dc:title>Univariate Ideal Membership Parameterized by Rank, Degree, and Number of Generators</dc:title>
          <dc:creator>Arvind, V.</dc:creator>
          <dc:creator>Chatterjee, Abhranil</dc:creator>
          <dc:creator>Datta, Rajit</dc:creator>
          <dc:creator>Mukhopadhyay, Partha</dc:creator>
          <dc:subject>Combinatorial Nullstellensatz</dc:subject>
          <dc:subject>Ideal Membership</dc:subject>
          <dc:subject>Parametric Hardness</dc:subject>
          <dc:subject>Low Rank Permanent</dc:subject>
          <dc:description>Let F[X] be the polynomial ring over the variables X={x_1,x_2, ..., x_n}. An ideal I= &lt;p_1(x_1), ..., p_n(x_n)&gt; generated by univariate polynomials {p_i(x_i)}_{i=1}^n is a univariate ideal. We study the ideal membership problem for the univariate ideals and show the following results.
- Let f(X) in F[l_1, ..., l_r] be a (low rank) polynomial given by an arithmetic circuit where l_i : 1 &lt;= i &lt;= r are linear forms, and I=&lt;p_1(x_1), ..., p_n(x_n)&gt; be a univariate ideal. Given alpha in F^n, the (unique) remainder f(X) mod I can be evaluated at alpha in deterministic time d^{O(r)} * poly(n), where d=max {deg(f),deg(p_1)...,deg(p_n)}. This yields a randomized n^{O(r)} algorithm for minimum vertex cover in graphs with rank-r adjacency matrices. It also yields an n^{O(r)} algorithm for evaluating the permanent of a n x n matrix of rank r, over any field F. Over Q, an algorithm of similar run time for low rank permanent is due to Barvinok [Barvinok, 1996] via a different technique.
- Let f(X)in F[X] be given by an arithmetic circuit of degree k (k treated as fixed parameter) and I=&lt;p_1(x_1), ..., p_n(x_n)&gt;. We show that in the special case when I=&lt;x_1^{e_1}, ..., x_n^{e_n}&gt;, we obtain a randomized O^*(4.08^k) algorithm that uses poly(n,k) space.
- Given f(X)in F[X] by an arithmetic circuit and I=&lt;p_1(x_1), ..., p_k(x_k)&gt;, membership testing is W[1]-hard, parameterized by k. The problem is MINI[1]-hard in the special case when I=&lt;x_1^{e_1}, ..., x_k^{e_k}&gt;.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>V. Arvind and Abhranil Chatterjee and Rajit Datta and Partha Mukhopadhyay</dc:contributor>
          <dc:date>2018</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 122, 38th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2018)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.FSTTCS.2018.7</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-99068</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2018.7</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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