SearcharxivSearch

arXiv · 1808.10787

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

Abstract

Let $\mathbb{F}[X]$ be the polynomial ring over the variables $X=\{x_1,x_2, \ldots, x_n\}$. An ideal $I=\langle p_1(x_1), \ldots, p_n(x_n)\rangle$ generated by univariate polynomials $\{p_i(x_i)\}_{i=1}^n$ is a \emph{univariate ideal}. We study the ideal membership problem for the univariate ideals and show the following results. \item Let $f(X)\in\mathbb{F}[\ell_1, \ldots, \ell_r]$ be a (low rank) polynomial given by an arithmetic circuit where $\ell_i : 1\leq i\leq r$ are linear forms, and $I=\langle p_1(x_1), \ldots, p_n(x_n)\rangle$ be a univariate ideal. Given $\vec{\alpha}\in {\mathbb{F}}^n$, the (unique) remainder $f(X) \pmod I$ can be evaluated at $\vec{\alpha}$ in deterministic time $d^{O(r)}\cdot poly(n)$, where $d=\max\{\deg(f),\deg(p_1)\ldots,\deg(p_n)\}$. This yields an $n^{O(r)}$ 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 $n\times n$ matrix of rank $r$, over any field $\mathbb{F}$. Over $\mathbb{Q}$, an algorithm of similar run time for low rank permanent is due to Barvinok[Bar96] via a different technique. \item Let $f(X)\in\mathbb{F}[X]$ be given by an arithmetic circuit of degree $k$ ($k$ treated as fixed parameter) and $I=\langle p_1(x_1), \ldots, p_n(x_n)\rangle$. We show in the special case when $I=\langle x_1^{e_1}, \ldots, x_n^{e_n}\rangle$, we obtain a randomized $O^*(4.08^k)$ algorithm that uses $poly(n,k)$ space. \item Given $f(X)\in\mathbb{F}[X]$ by an arithmetic circuit and $I=\langle p_1(x_1), \ldots, p_k(x_k) \rangle$, membership testing is $W[1]$-hard, parameterized by $k$. The problem is $MINI[1]$-hard in the special case when $I=\langle x_1^{e_1}, \ldots, x_k^{e_k}\rangle$.

Explore related subjects

Keep this discovery

BibTeXRIS

V. Arvind, Abhranil Chatterjee, Rajit Datta, Partha Mukhopadhyay. 2018-08-31. Univariate Ideal Membership Parameterized by Rank, Degree, and Number of Generators. https://arxiv.org/abs/1808.10787

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Quasi-Monte Carlo Beyond Hardy-Krause II: $(1 + \varepsilon)n$ Samples Suffice

Numerical integration studies how well one can estimate the integral of a function $f$ over $[0,1)^d$ using $n$ sample points. The two classical methods, Monte Carlo (MC) and quasi-Monte Carlo (QMC), have complementary strengths and weaknesses, and a fundamental question is to design an approach that combines the benefits of both. Recently, building on the transference principle in discrepancy theory, Bansal and Jiang~\cite{BJ25a} gave a randomized QMC method that bridges MC and QMC guarantees using only i.i.d.\ samples. Their method also goes beyond the classical Koksma--Hlawka inequality: it achieves integration error $\widetilde{O}_d(\sigma_{\mathsf{SO}}(f)/n)$, where the smoothed-out variation $\sigma_{\mathsf{SO}}(f)$ can be substantially smaller than the Hardy--Krause variation that governs the classical bound. However, their algorithm requires $n^2$ i.i.d.\ samples as input, and this quadratic blowup is inherent to any method based on the transference principle. In this work, we bypass the quadratic blowup: for any constant $\varepsilon > 0$, we show that $(1+\varepsilon)n$ i.i.d.\ samples suffice to both obtain the beyond-Hardy--Krause guarantee of~\cite{BJ25a}, resolving an open problem posed there, and to produce low-discrepancy point sequences. Our algorithms are variants of the online Haar-thinning method of Dwivedi, Feldheim, Gurel-Gurevich, and Ramdas~\cite{DFG+19}.

cs.DS

Single-Exponential Algorithms and a Polynomial Kernel for Strong Connectivity Augmentation

Strong Connectivity Augmentation (SCA) asks whether a directed acyclic graph can be made strongly connected by adding at most $k$ prescribed links whose total weight is within a given budget. Klinkby, Misra, and Saurabh (SODA 2021) gave an $O^*(2^{O(k\log k)})$-time algorithm and asked whether the problem admits a single-exponential parameterized algorithm and a polynomial kernel. We answer both questions affirmatively: SCA can be solved in $O^*(9^k)$ time and admits a polynomial kernel with $O(k^4)$ vertices and $O(k^{16})$ bits. For unweighted SCA, we obtain $O^*(4^k)$ time and a kernel with $O(k^3)$ vertices. Our algorithms are based on a particularly simple reduction to Strongly Connected Spanning Subgraph with two edge costs.

cs.DS