Multilevel Picard approximation algorithm for semilinear partial integro-differential equations and its complexity analysis

Ariel Neufeld*, Sizhou Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we introduce a multilevel Picard approximation algorithm for semilinear parabolic partial integro-differential equations (PIDEs). We prove that the numerical approximation scheme converges to the unique viscosity solution of the PIDE under consideration. To that end, we derive a Feynman-Kac representation for the unique viscosity solution of the semilinear PIDE, extending the classical Feynman-Kac representation for linear PIDEs. Furthermore, we show that the algorithm does not suffer from the curse of dimensionality, i.e., the computational complexity of the algorithm is bounded polynomially in the dimension d and the reciprocal of the prescribed accuracy ε. We also provide a numerical example in up to 10,000 dimensions to demonstrate its applicability.

Original languageEnglish
JournalStochastics and Partial Differential Equations: Analysis and Computations
DOIs
Publication statusAccepted/In press - 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

ASJC Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Applied Mathematics

Keywords

  • Feynman-Kac representation
  • Monte Carlo methods
  • Multilevel Picard approximation
  • Nonlinear PIDE
  • Overcoming the curse of dimensionality

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