Efficient finite element methods for semiclassical nonlinear Schrödinger equations with random potentials

In this paper, we propose two time-splitting finite element methods to solve the semiclassical nonlinear Schrödinger equation (NLSE) with random potentials. We then introduce a multiscale method to reduce the degrees of freedom in the physical space. We construct multiscale basis functions by solving optimization problems and rigorously analyze the corresponding time-splitting multiscale reduced methods for the semiclassical NLSE with random potentials. We provide the L2 error estimate of the proposed methods and show that they achieve second-order accuracy in both spatial and temporal spaces and an almost first-order convergence rate in the random space. Additionally, we introduce the proper orthogonal decomposition method to reduce the computational cost of constructing basis functions for solving random NLSEs. Finally, we carry out several 1D and 2D numerical examples to validate the convergence of our methods and investigate wave propagation behaviors in the NLSE with random potentials.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-17
DOI
https://doi.org/10.1051/m2an/2025072/pdf
Primary Topic
Advanced Mathematical Modeling in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient finite element methods for semiclassical nonlinear Schrödinger equations with random potentials

Springer Link (Chiba Institute of Technology)
Advanced Mathematical Modeling in Engineering
article

Efficient finite element methods for semiclassical nonlinear Schrödinger equations with random potentials

article en

Abstract

In this paper, we propose two time-splitting finite element methods to solve the semiclassical nonlinear Schrödinger equation (NLSE) with random potentials. We then introduce a multiscale method to reduce the degrees of freedom in the physical space. We construct multiscale basis functions by solving optimization problems and rigorously analyze the corresponding time-splitting multiscale reduced methods for the semiclassical NLSE with random potentials. We provide the L2 error estimate of the proposed methods and show that they achieve second-order accuracy in both spatial and temporal spaces and an almost first-order convergence rate in the random space. Additionally, we introduce the proper orthogonal decomposition method to reduce the computational cost of constructing basis functions for solving random NLSEs. Finally, we carry out several 1D and 2D numerical examples to validate the convergence of our methods and investigate wave propagation behaviors in the NLSE with random potentials.

Springer Link (Chiba Institute of Technology)
Peace, Justice and strong institutions
Openalex Percentile: Top 29%
Advanced Mathematical Modeling in Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.