Probabilistic time integration for semi-explicit PDAEs

Abstract This paper deals with the application of probabilistic time integration methods to semi-explicit partial differential–algebraic equations of parabolic type and its semi-discrete counterparts, namely semi-explicit differential–algebraic equations of index 2. The proposed methods iteratively construct a probability distribution over the solution of deterministic problems, enhancing the information obtained from the numerical simulation. Within this paper, we examine the efficacy of the randomized versions of the implicit Euler method, the midpoint scheme, and exponential integrators of first and second order. By demonstrating the consistency and convergence properties of these solvers, we illustrate their utility in capturing the sensitivity of the solution to numerical errors. Our analysis establishes the theoretical validity of randomized time integration for constrained systems and offers insights into the calibration of probabilistic integrators for practical applications.

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Publication Details

Journal
Statistics and Computing
Published
2024-12-16
DOI
https://doi.org/10.1007/s11222-024-10543-0
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
0.00

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article

Probabilistic time integration for semi-explicit PDAEs

Robert Altmann, Alireza Moradi
Statistics and Computing
Numerical methods for differential equations
article

Probabilistic time integration for semi-explicit PDAEs

Robert Altmann, Alireza Moradi
article en

Abstract

Abstract This paper deals with the application of probabilistic time integration methods to semi-explicit partial differential–algebraic equations of parabolic type and its semi-discrete counterparts, namely semi-explicit differential–algebraic equations of index 2. The proposed methods iteratively construct a probability distribution over the solution of deterministic problems, enhancing the information obtained from the numerical simulation. Within this paper, we examine the efficacy of the randomized versions of the implicit Euler method, the midpoint scheme, and exponential integrators of first and second order. By demonstrating the consistency and convergence properties of these solvers, we illustrate their utility in capturing the sensitivity of the solution to numerical errors. Our analysis establishes the theoretical validity of randomized time integration for constrained systems and offers insights into the calibration of probabilistic integrators for practical applications.

Statistics and ComputingVol. 35(1)
Otto-von-Guericke-Universität Magdeburg (DE)
Deutsche Forschungsgemeinschaft, Otto von Guericke University Magdeburg
Openalex Percentile: Top 64%
Numerical methods for differential equations
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