Monotone Mixed Finite Difference Scheme for Monge-Amp\`ere Equation
Yangang Chen, Justin W. L. Wan, Jessey Lin

TL;DR
This paper introduces a monotone mixed finite difference scheme for the 2D Monge-Ampère equation, combining standard and semi-Lagrangian discretizations to ensure convergence and improve accuracy.
Contribution
It develops a novel mixed discretization approach that guarantees monotonicity, reduces computational cost, and achieves higher convergence rates for solving the Monge-Ampère equation.
Findings
Second order convergence with standard stencil
Up to first order convergence with mixed scheme
Reduced computational cost compared to pure semi-Lagrangian scheme
Abstract
In this paper, we propose a monotone mixed finite difference scheme for solving the two-dimensional Monge-Amp\`ere equation. In order to accomplish this, we convert the Monge-Amp\`ere equation to an equivalent Hamilton-Jacobi-Bellman (HJB) equation. Based on the HJB formulation, we apply the standard 7-point stencil discretization, which is second order accurate, to the grid points wherever monotonicity holds, and apply semi-Lagrangian wide stencil discretization elsewhere to ensure monotonicity on the entire computational domain. By dividing the admissible control set into six regions and optimizing the sub-problem in each region, the computational cost of the optimization problem at each grid point is reduced from to when the standard 7-point stencil discretization is applied and to otherwise, where the discretized control set is . We prove that our…
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