Sparse interpolation over finite fields via low-order roots of unity Andrew Arnold Mark Giesbrecht Cheriton School of Computer Science Cheriton School of Computer Science University of Waterloo University of Waterloo
[email protected] [email protected] Daniel S. Roche Computer Science Department United States Naval Academy
[email protected] August 21, 2018 Abstract We present a new Monte Carlo algorithm for the interpolation of a straight-line program as a sparse polynomial f over an arbitrary finite field of size q. We assume a priori bounds D and T are given on the degree and number of terms of f. The approach presented in this paper is a hybrid of the diversified and recursive interpolation algorithms, the two previous fastest known probabilistic methods for this problem. By making effective use of the information contained in the coefficients themselves, this new algorithm improves on the bit complexity of previous methods by a “soft-Oh” factor of T , log D, or log q. 1 Introduction arXiv:1401.4744v2 [cs.SC] 2 May 2014 Let Fq be a finite field of size q and consider a “sparse” polynomial t ei F f = i=1 ciz ∈ q[z], (1.1) P where the c1,...,ct ∈ Fq are nonzero and the exponents e1,...,et ∈ Z≥0 are distinct. Suppose f is provided as a straight-line program, a simple branch-free program which evaluates f at any point (see below for a formal definition). Suppose also that we are given an upper bound D on the degree of f and an upper bound T on the number of non-zero terms t of f.