A Critical Evaluation and Modification of the Padé–Laplace Method for Deconvolution of Viscoelastic Spectra

Abstract

This paper shows that using the Padé–Laplace (PL) method for deconvolution of multi-exponential functions (stress relaxation of polymers) can produce ill-conditioned systems of equations. Analysis of different sets of generated data points from known multi-exponential functions indicates that by increasing the level of Padé approximants, the condition number of a matrix whose entries are coefficients of a Taylor series in the Laplace space grows rapidly. When higher levels of Padé approximants need to be computed to achieve stable modes for separation of exponentials, the problem of generating matrices with large condition numbers becomes more pronounced. The analysis in this paper discusses the origin of ill-posedness of the PL method and it was shown that ill-posedness may be regularized by reconstructing the system of equations and using singular value decomposition (SVD) for computation of the Padé table. Moreover, it is shown that after regularization, the PL method can deconvolute the exponential decays even when the input parameter of the method is out of its optimal range.

Metallicity in the Dissipative Hubbard-Holstein Model: Markovian and Non-Markovian Tensor-Network Methods for Open Quantum Many-Body Systems

“…19 we approximate the correlation function Eq. ( 61) via the Laplace-Pade method [163]. It can be seen that already three complex exponentials suffice to reproduce the correlation function fairly well.…”

“…for any square-integrable function with arbitrary precision by increasing P . The decomposition can be obtained, for instance, with the Laplace-Pade method [163], yielding a set of parameters ω p , g p and κ p . In this work, we will deal with the case P = 1, corresponding to the case of a Lorentzian spectral density.…”