Rigorous uniform approximation of D-finite functions using Chebyshev expansions

TL;DR

This paper develops a rigorous method for uniform approximation of D-finite functions using Chebyshev expansions, combining classical techniques with validated error bounds to ensure accuracy and analyze complexity.

Contribution

It introduces a novel approach that leverages linear recurrence relations of Chebyshev coefficients for D-finite functions, enabling guaranteed approximations with complexity analysis.

Findings

Validated algorithms for uniform approximation with error bounds

Complexity analysis of the proposed methods

Effective use of recurrence relations for D-finite functions

Abstract

A wide range of numerical methods exists for computing polynomial approximations of solutions of ordinary differential equations based on Chebyshev series expansions or Chebyshev interpolation polynomials. We consider the application of such methods in the context of rigorous computing (where we need guarantees on the accuracy of the result), and from the complexity point of view. It is well-known that the order-n truncation of the Chebyshev expansion of a function over a given interval is a near-best uniform polynomial approximation of the function on that interval. In the case of solutions of linear differential equations with polynomial coefficients, the coefficients of the expansions obey linear recurrence relations with polynomial coefficients. Unfortunately, these recurrences do not lend themselves to a direct recursive computation of the coefficients, owing among other things to a lack of initial conditions. We show how they can nevertheless be used, as part of a validated process, to compute good uniform approximations of D-finite functions together with rigorous error bounds, and we study the complexity of the resulting algorithms. Our approach is based on a new view of a classical numerical method going back to Clenshaw, combined with a functional enclosure method.