Exponential node clustering at singularities for rational approximation, quadrature, and PDEs

TL;DR

This paper demonstrates that exponential clustering of poles near singularities significantly improves the convergence rates of rational approximations, quadrature, and PDE solutions, with theoretical backing from potential theory and contour integrals.

Contribution

It introduces the tapering of exponential clustering density to double convergence rates and connects this to advanced quadrature formulas through contour integral analysis.

Findings

Tapered exponential clustering enhances convergence.

Theoretical explanation via Hermite contour integral and potential theory.

Application to quadrature formulas improves accuracy.

Abstract

Rational approximations of functions with singularities can converge at a root-exponential rate if the poles are exponentially clustered. We begin by reviewing this effect in minimax, least-squares, and AAA approximations on intervals and complex domains, conformal mapping, and the numerical solution of Laplace, Helmholtz, and biharmonic equations by the "lightning" method. Extensive and wide-ranging numerical experiments are involved. We then present further experiments showing that in all of these applications, it is advantageous to use exponential clustering whose density on a logarithmic scale is not uniform but tapers off linearly to zero near the singularity. We give a theoretical explanation of the tapering effect based on the Hermite contour integral and potential theory, showing that tapering doubles the rate of convergence. Finally we show that related mathematics applies to the relationship between exponential (not tapered) and doubly exponential (tapered) quadrature formulas. Here it is the Gauss--Takahasi--Mori contour integral that comes into play.