Local discontinuous Galerkin method for the Backward Feynman-Kac Equation

TL;DR

This paper develops a local discontinuous Galerkin method to efficiently and accurately solve the 2D backward Feynman-Kac equation, addressing singularities and demonstrating optimal convergence through theoretical analysis and numerical experiments.

Contribution

The paper introduces a novel LDG scheme for the backward Feynman-Kac equation, including stability and convergence proofs, and explores the impact of numerical flux choices on performance.

Findings

The semi-discrete scheme achieves optimal convergence rate of O(h^{k+1}).

The fully discrete scheme attains convergence rate of O(h^{k+1} + τ^{min{2-α, γδ}}).

Numerical experiments confirm the scheme's efficiency and accuracy.

Abstract

Anomalous diffusions are ubiquitous in nature, whose functional distributions are governed by the backward Feynman-Kac equation. In this paper, the local discontinuous Galerkin (LDG) method is used to solve the 2D backward Feynman-Kac equation in a rectangular domain. The spatial semi-discrete LDG scheme of the equivalent form (obtained by Laplace transform) of the original equation is established. After discussing the properties of the fractional substantial calculus, the stability and optimal convergence rates $O(h^{k+1})$ of the semi-discrete scheme are proved by choosing an appropriate generalized numerical flux. The $L1$ scheme on the graded meshes is used to deal with the weak singularity of the solution near the initial time. Based on the theoretical results of a semi-discrete scheme, we investigate the stability and convergence of the fully discrete scheme, which shows the optimal convergence rates $O(h^{k+1}+\tau^{\min\{2-\alpha,\gamma\delta\}})$. Numerical experiments are carried out to show the efficiency and accuracy of the proposed scheme. In addition, we also verify the effect of the central numerical flux on the convergence rates and the condition number of the coefficient matrix.