Abstract

We present two new data structures for computing values of an n-variate polynomial P of degree at most d over a finite field of q elements. Assuming that d divides q-1, our first data structure relies on (d+1)^{n+2} tabulated values of P to produce the value of P at any of the q^n points using O(nqd^2) arithmetic operations in the finite field. Assuming that s divides d and d / s divides q-1, our second data structure assumes that P satisfies a degree-separability condition and relies on (d/s+1)^{n+s} tabulated values to produce the value of P at any point using Oleft( nq^ssqright) arithmetic operations. Our data structures are based on generalizing upper-bound constructions due to Mockenhaupt and Tao (Duke Math J 121(1):35–74, 2004), Saraf and Sudan (Anal PDE 1(3):375–379, 2008) and Dvir (Incidence theorems and their applications, 2012. arXiv:1208.5073) for Kakeya sets in finite vector spaces from linear to higher-degree polynomial curves. As an application we show that the new data structures enable a faster algorithm for computing integer-valued fermionants, a family of self-reducible polynomial functions introduced by Chandrasekharan and Wiese (Partition functions of strongly correlated electron systems as fermionants, 2011. arXiv:1108.2461v1) that captures numerous fundamental algebraic and combinatorial functions such as the determinant, the permanent, the number of Hamiltonian cycles in a directed multigraph, as well as certain partition functions of strongly correlated electron systems in statistical physics. In particular, a corollary of our main theorem for fermionants is that the permanent of an mtimes m integer matrix with entries bounded in absolute value by a constant can be computed in time 2^{m-Omega left( sqrt{m/log log m}right) }, improving an earlier algorithm of Björklund (in: Proceedings of the 15th SWAT, vol 17, pp 1–11, 2016) that runs in time 2^{m-Omega left( sqrt{m/log m}right) }.

Highlights

  • The protagonist of this paper is the following task

  • As an application we show that the new data structures enable a faster algorithm for computing integer-valued fermionants, a family of self-reducible polynomial functions introduced by Chandrasekharan and Wiese (Partition functions of strongly correlated electron systems as fermionants, 2011. arXiv:1108.2461v1)

  • The study of data structures that enable fast “polynomial evaluation” queries for multivariate polynomials was initiated by Kedlaya and Umans [12] for polynomials with bounded individual variable degrees, motivated by applications to fast polynomial factorization

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Summary

Introduction

We want an efficient representation of an n-variate degree-d polynomial P over a finite field Fq of order q, that permits us to evaluate P on arbitrary points a ∈ Fqn. What kind of resource trade-offs can be achieved between space (for representing P) and query time (for computing P(a) at a given a)?. We can set K = Fqn , put all evaluations in a sorted array, and assuming constant-time random access, we achieve O(n) query time. When K is this small, we are only aware of brute-force (nO(d)-time) algorithms to evaluate the polynomial in any other point. Between these two extremes, we seek constructions for sets K that suffice for evaluating P at any point outside K in time that scales sub-exponentially in d. Our motivation is to accelerate the best known algorithms for canonical #P-hard problems (cf. Sect. 1.2)

Polynomial Evaluation Based on Generalized Kakeya Sets
Fermionants
Organisation of the Paper
Generalized Kakeya Sets in Finite Vector Spaces
Polynomial Evaluation
Proof of Theorem 1
Proof of Theorem 2
Self-Reducibility of the Fermionant
Proof of Theorem 3
Proof of Corollary 1
Full Text
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