Semi-discrete heat equations with variable coefficients and the parametrix method

We develop a parametrix approach for constructing solutions and establishing grid-size independent estimates for semi-discrete heat equations with variable coefficients. While the classical continuous setting benefits from Gaussian estimates of the constant coefficient heat kernel, such estimates are not available in the semi-discrete context. To address this complication, we derive estimates involving products of heavy-tailed Lorentz (also known as Cauchy) probability densities. These Lorentzian estimates provide a sufficient handle on certain iterated convolutions involving Bessel functions, enabling us to achieve convergence of the parametrix approach.

Publication Details

Journal
arXiv (Cornell University)
Published
2025-06-23
Primary Topic
Numerical methods in inverse problems
Type
article
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article

Semi-discrete heat equations with variable coefficients and the parametrix method

arXiv (Cornell University)
Numerical methods in inverse problems
article

Semi-discrete heat equations with variable coefficients and the parametrix method

article en

Abstract

We develop a parametrix approach for constructing solutions and establishing grid-size independent estimates for semi-discrete heat equations with variable coefficients. While the classical continuous setting benefits from Gaussian estimates of the constant coefficient heat kernel, such estimates are not available in the semi-discrete context. To address this complication, we derive estimates involving products of heavy-tailed Lorentz (also known as Cauchy) probability densities. These Lorentzian estimates provide a sufficient handle on certain iterated convolutions involving Bessel functions, enabling us to achieve convergence of the parametrix approach.

arXiv (Cornell University)
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Numerical methods in inverse problems
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