Generalized convolution quadrature based on the trapezoidal rule

Abstract We present a novel generalized convolution quadrature (gCQ) method that accurately approximates convolution integrals. During the late 1980s, Lubich introduced convolution quadrature techniques, which have now emerged as a prevalent methodology in this field. However, these techniques were limited to constant time stepping, and only in the last decade gCQ based on the implicit Euler and Runge–Kutta methods have been developed, allowing for variable time stepping. In this paper, we introduce and analyze a new gCQ method based on the trapezoidal rule. Crucial for the analysis is the connection to a new modified divided difference formula that we establish. Numerical experiments demonstrate the effectiveness of our method in achieving highly accurate and reliable results.

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Publication Details

Journal
IMA Journal of Numerical Analysis
Published
2025-11-22
DOI
https://doi.org/10.1093/imanum/draf141
Primary Topic
Mathematical functions and polynomials
Type
article
Field-Weighted Citation Impact
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article

Generalized convolution quadrature based on the trapezoidal rule

Matteo Ferrari, Lehel Banjai
IMA Journal of Numerical Analysis
Mathematical functions and polynomials
article

Generalized convolution quadrature based on the trapezoidal rule

Matteo Ferrari, Lehel Banjai
article en

Abstract

Abstract We present a novel generalized convolution quadrature (gCQ) method that accurately approximates convolution integrals. During the late 1980s, Lubich introduced convolution quadrature techniques, which have now emerged as a prevalent methodology in this field. However, these techniques were limited to constant time stepping, and only in the last decade gCQ based on the implicit Euler and Runge–Kutta methods have been developed, allowing for variable time stepping. In this paper, we introduce and analyze a new gCQ method based on the trapezoidal rule. Crucial for the analysis is the connection to a new modified divided difference formula that we establish. Numerical experiments demonstrate the effectiveness of our method in achieving highly accurate and reliable results.

IMA Journal of Numerical Analysis
University of Vienna (AT), Maxwell Institute for Mathematical Sciences (GB)
Openalex Percentile: Top 15%
Mathematical functions and polynomials
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