A gradient flow model for the Gross--Pitaevskii problem: Mathematical and numerical analysis

This paper concerns the mathematical and numerical analysis of the L2 normalized gradient flow model for the Gross--Pitaevskii eigenvalue problem, which has been widely used to design the numerical schemes for the computation of the ground state of the Bose--Einstein condensate. We first provide the mathematical analysis for the model, including the well-posedness and the asymptotic behavior of the solution. Then we propose a normalized implicit-explicit fully discrete numerical scheme for the gradient flow model, and give some numerical analysis for the scheme, including the well-posedness and optimal convergence of the approximation. Some numerical experiments are provided to validate the theory.

Authors

Publication Details

Journal
ESAIM. Mathematical modelling and numerical analysis
Published
2026-04-17
DOI
https://doi.org/10.1051/m2an/2026034
Primary Topic
Cold Atom Physics and Bose-Einstein Condensates
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A gradient flow model for the Gross--Pitaevskii problem: Mathematical and numerical analysis

Jing Wu, Xiaoying Dai, Tianyang Chu, Aihui Zhou
ESAIM. Mathematical modelling and numerical analysis
Cold Atom Physics and Bose-Einstein Condensates
article

A gradient flow model for the Gross--Pitaevskii problem: Mathematical and numerical analysis

Jing Wu, Xiaoying Dai, Tianyang Chu, Aihui Zhou
article en

Abstract

This paper concerns the mathematical and numerical analysis of the L2 normalized gradient flow model for the Gross--Pitaevskii eigenvalue problem, which has been widely used to design the numerical schemes for the computation of the ground state of the Bose--Einstein condensate. We first provide the mathematical analysis for the model, including the well-posedness and the asymptotic behavior of the solution. Then we propose a normalized implicit-explicit fully discrete numerical scheme for the gradient flow model, and give some numerical analysis for the scheme, including the well-posedness and optimal convergence of the approximation. Some numerical experiments are provided to validate the theory.

ESAIM. Mathematical modelling and numerical analysis
National Natural Science Foundation of China
Openalex Percentile: Top 99%
Cold Atom Physics and Bose-Einstein Condensates
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.