Solving Fokker-Planck equations using the zeros of Fokker-Planck operators and the Feynman-Kac formula

Fuente: arXiv
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Main Authors: Mandal, Pinak, Apte, Amit
Format: Preprint
Published: 2024
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author Mandal, Pinak
Apte, Amit
author_facet Mandal, Pinak
Apte, Amit
contents First we show that physics-informed neural networks are not suitable for a large class of parabolic partial differential equations including the Fokker-Planck equation. Then we devise an algorithm to compute solutions of the Fokker-Planck equation using the zeros of Fokker-Planck operator and the Feynman-Kac formula. The resulting algorithm is mesh-free, highly parallelizable and able to compute solutions pointwise, thus mitigating the curse of dimensionality in a practical sense. We analyze various nuances of this algorithm that are determined by the drift term in the Fokker-Planck equation. We work with problems ranging in dimensions from 2 to 10. We demonstrate that this algorithm requires orders of magnitude fewer trajectories for each point in space when compared to Monte-Carlo. We also prove that under suitable conditions the error that is caused by letting some trajectories (associated with the Feynman-Kac expectation) escape our domain of knowledge is proportional to the fraction of trajectories that escape.
format Preprint
id arxiv_https___arxiv_org_abs_2401_01292
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Solving Fokker-Planck equations using the zeros of Fokker-Planck operators and the Feynman-Kac formula
Mandal, Pinak
Apte, Amit
Analysis of PDEs
First we show that physics-informed neural networks are not suitable for a large class of parabolic partial differential equations including the Fokker-Planck equation. Then we devise an algorithm to compute solutions of the Fokker-Planck equation using the zeros of Fokker-Planck operator and the Feynman-Kac formula. The resulting algorithm is mesh-free, highly parallelizable and able to compute solutions pointwise, thus mitigating the curse of dimensionality in a practical sense. We analyze various nuances of this algorithm that are determined by the drift term in the Fokker-Planck equation. We work with problems ranging in dimensions from 2 to 10. We demonstrate that this algorithm requires orders of magnitude fewer trajectories for each point in space when compared to Monte-Carlo. We also prove that under suitable conditions the error that is caused by letting some trajectories (associated with the Feynman-Kac expectation) escape our domain of knowledge is proportional to the fraction of trajectories that escape.
title Solving Fokker-Planck equations using the zeros of Fokker-Planck operators and the Feynman-Kac formula
topic Analysis of PDEs
url https://arxiv.org/abs/2401.01292