Algorithms for asymptotic extrapolation∗ Joris van der Hoeven CNRS, Département de Mathématiques Bâtiment 425 Université Paris-Sud 91405 Orsay Cedex France Email:
[email protected] Web: http://www.math.u-psud.fr/~vdhoeven December 9, 2008 Consider a power series f ∈ R[[ z]] , which is obtained by a precise mathematical construction. For instance, f might be the solution to some differential or functional initial value problem or the diagonal of the solution to a partial differential equation. In cases when no suitable method is beforehand for determining the asymptotics of the coefficients fn, but when many such coefficients can be computed with high accuracy, it would be useful if a plausible asymptotic expansion for fn could be guessed automatically. In this paper, we will present a general scheme for the design of such “asymptotic extrapolation algorithms”. Roughly speaking, using discrete differentiation and tech- niques from automatic asymptotics, we strip off the terms of the asymptotic expansion one by one. The knowledge of more terms of the asymptotic expansion will then allow us to approximate the coefficients in the expansion with high accuracy. Keywords: extrapolation, asymptotic expansion, algorithm, guessing A.M.S. subject classification: 41A05, 41A60, 65B05, 68W30 1. Introduction Consider an infinite sequence f0,f1 , of real numbers. If f0,f1 , are the coefficients of a formal power series f R[[ z]] , then it is well-known [Pól37, Wil04, FS96] that a lot of information about the behaviour∈ of f near its dominant singularity can be obtained from the asymptotic behaviour of the sequence f0,f1 , . However, if f is the solution to some complicated equation, then it can be hard to compute the asymptotic behaviour using formal methods.