Transparent boundary condition and its high frequency approximation for the Schr\"odinger equation on a rectangular computational domain

TL;DR

This paper develops and analyzes a spectral method-based numerical scheme for implementing transparent boundary conditions in the Schrödinger equation, including high frequency approximations and corner conditions, with stability and convergence demonstrated through numerical tests.

Contribution

It introduces a spectral discretization combined with Padé-based TBC implementation and corner conditions for the Schrödinger equation, advancing boundary treatment accuracy and efficiency.

Findings

Effective boundary maps with corner conditions improve stability.

Numerical tests confirm convergence and stability.

High frequency approximation enhances boundary condition accuracy.

Abstract

This paper addresses the numerical implementation of the transparent boundary condition (TBC) and its various approximations for the free Schr\"odinger equation on a rectangular computational domain. In particular, we consider the exact TBC and its spatially local approximation under high frequency assumption along with an appropriate corner condition. For the spatial discretization, we use a Legendre-Galerkin spectral method where Lobatto polynomials serve as the basis. Within variational formalism, we first arrive at the time-continuous dynamical system using spatially discrete form of the initial boundary-value problem incorporating the boundary conditions. This dynamical system is then discretized using various time-stepping methods, namely, the backward-differentiation formula of order 1 and 2 (i.e., BDF1 and BDF2, respectively) and the trapezoidal rule (TR) to obtain a fully discrete system. Next, we extend this approach to the novel Pad\'e based implementation of the TBC presented by Yadav and Vaibhav [arXiv:2403.07787(2024)]. Finally, several numerical tests are presented to demonstrate the effectiveness of the boundary maps (incorporating the corner conditions) where we study the stability and convergence behavior empirically.