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Univariate Ideal Membership Parameterized by Rank, Degree, and Number of Generators

Published 31 Aug 2018 in cs.DS | (1808.10787v2)

Abstract: Let F[X]\mathbb{F}[X] be the polynomial ring over the variables X=x1,x2,…,xnX={x_1,x_2, \ldots, x_n}. An ideal I=⟨p1(x1),…,pn(xn)⟩I=\langle p_1(x_1), \ldots, p_n(x_n)\rangle generated by univariate polynomials pi(xi)i=1<sup>n{p_i(x_i)}_{i=1}<sup>n is a \emph{univariate ideal}. We study the ideal membership problem for the univariate ideals and show the following results. \item Let f(X)∈F[ℓ1,…,ℓr]f(X)\in\mathbb{F}[\ell_1, \ldots, \ell_r] be a (low rank) polynomial given by an arithmetic circuit where ℓi:1≤i≤r\ell_i : 1\leq i\leq r are linear forms, and I=⟨p1(x1),…,pn(xn)⟩I=\langle p_1(x_1), \ldots, p_n(x_n)\rangle be a univariate ideal. Given α⃗∈F<sup>n\vec{\alpha}\in {\mathbb{F}}<sup>n, the (unique) remainder f(X)(modI)f(X) \pmod I can be evaluated at α⃗\vec{\alpha} in deterministic time d<sup>O(r)⋅</sup>poly(n)d<sup>{O(r)}\cdot</sup> poly(n), where d=max⁡deg⁡(f),deg⁡(p1)…,deg⁡(pn)d=\max{\deg(f),\deg(p_1)\ldots,\deg(p_n)}. This yields an n<sup>O(r)n<sup>{O(r)} algorithm for minimum vertex cover in graphs with rank-rr adjacency matrices. It also yields an n<sup>O(r)n<sup>{O(r)} algorithm for evaluating the permanent of a n×nn\times n matrix of rank rr, over any field F\mathbb{F}. Over Q\mathbb{Q}, an algorithm of similar run time for low rank permanent is due to Barvinok[Bar96] via a different technique. \item Let f(X)∈F[X]f(X)\in\mathbb{F}[X] be given by an arithmetic circuit of degree kk (kk treated as fixed parameter) and I=⟨p1(x1),…,pn(xn)⟩I=\langle p_1(x_1), \ldots, p_n(x_n)\rangle. We show in the special case when I=⟨x1<sup>e1,</sup>…,xn<sup>en⟩I=\langle x_1<sup>{e_1},</sup> \ldots, x_n<sup>{e_n}\rangle, we obtain a randomized O<sup>∗(4.08<sup>k)O<sup>*(4.08<sup>k) algorithm that uses poly(n,k)poly(n,k) space. \item Given f(X)∈F[X]f(X)\in\mathbb{F}[X] by an arithmetic circuit and I=⟨p1(x1),…,pk(xk)⟩I=\langle p_1(x_1), \ldots, p_k(x_k) \rangle, membership testing is W[1]W[1]-hard, parameterized by kk. The problem is MINI[1]MINI[1]-hard in the special case when I=⟨x1<sup>e1,</sup>…,xk<sup>ek⟩I=\langle x_1<sup>{e_1},</sup> \ldots, x_k<sup>{e_k}\rangle.

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