Overcoming the curse of dimensionality in the numerical approximation of Allen–Cahn partial differential equations via truncated full-history recursive multilevel Picard approximations


Date

2020-12-16

Publication Type

Journal Article

ETH Bibliography

yes

Citations

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Data

Abstract

One of the most challenging problems in applied mathematics is the approximate solution of nonlinear partial differential equations (PDEs) in high dimensions. Standard deterministic approximation methods like finite differences or finite elements suffer from the curse of dimensionality in the sense that the computational effort grows exponentially in the dimension. In this work we overcome this difficulty in the case of reaction–diffusion type PDEs with a locally Lipschitz continuous coervice nonlinearity (such as Allen–Cahn PDEs) by introducing and analyzing truncated variants of the recently introduced full-history recursive multilevel Picard approximation schemes.

Publication status

published

Editor

Book title

Volume

28 (4)

Pages / Article No.

197 - 222

Publisher

De Gruyter

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Parabolic partial differential equations; Multilevel Picard approximations; Feynman-Kac representation; Curse of dimensionality; Numerical analysis; Applied stochastic analysis; 60H30; 65C05; 65M75

Organisational unit

02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics check_circle
03874 - Hungerbühler, Norbert / Hungerbühler, Norbert check_circle

Notes

It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.

Funding

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