Self-Similar Factor Approximants

TL;DR

This paper introduces self-similar factor approximants, a new method for reconstructing functions from asymptotic expansions, which generalizes and improves upon existing approximants like Pade and exponential types.

Contribution

The paper develops a novel class of self-similar factor approximants that unify and extend previous approximants, offering superior accuracy and broader applicability.

Findings

Exact reproduction of a wide class of functions including transcendental functions.

Significantly more accurate than traditional Pade approximants for complex functions.

Demonstrated effectiveness through multiple illustrative examples.

Abstract

The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving a novel type of approximants. The derivation is based on the self-similar approximation theory, which presents the passage from one approximant to another as the motion realized by a dynamical system with the property of group self-similarity. The derived approximants, because of their form, are named the self-similar factor approximants. These complement the obtained earlier self-similar exponential approximants and self-similar root approximants. The specific feature of the self-similar factor approximants is that their control functions, providing convergence of the computational algorithm, are completely defined from the accuracy-through-order conditions. These approximants contain the Pade approximants as a particular case, and in some limit they can be reduced to the self-similar exponential approximants previously introduced by two of us. It is proved that the self-similar factor approximants are able to reproduce exactly a wide class of functions which include a variety of transcendental functions. For other functions, not pertaining to this exactly reproducible class, the factor approximants provide very accurate approximations, whose accuracy surpasses significantly that of the most accurate Pade approximants. This is illustrated by a number of examples showing the generality and accuracy of the factor approximants even when conventional techniques meet serious difficulties.