Energy Preserving Parametric Multi-symplectic Methods for the Gross-Pitaevskii Equation

Abstract The multi-symplectic structure and energy conservation are inherent properties of the Gross-Pitaevskii equation. In this paper, we propose classical multi-symplectic Runge-Kutta methods and parametric multi-symplectic Runge-Kutta methods for the one-dimensional Gross-Pitaevskii equation. The parametric methods not only inherit the multi-symplectic structure and quadratic invariants of the classical methods, but also achieve energy conservation in a weaker sense by introducing an additional parameter. Numerical experiments verify the effectiveness of the proposed methods. Mathematics Subject Classification (2020) 65M06 · 65M12 · 65Z05 · 70H15

Authors

Institutions

Publication Details

Journal
Research Square
Published
2026-11-02
DOI
https://doi.org/10.21203/rs.3.rs-11093804/v1
Primary Topic
Numerical methods for differential equations
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Energy Preserving Parametric Multi-symplectic Methods for the Gross-Pitaevskii Equation

Futuan Li, Linghua Kong, Rong Gao
1 links
Research Square
Numerical methods for differential equations
preprint

Energy Preserving Parametric Multi-symplectic Methods for the Gross-Pitaevskii Equation

Futuan Li, Linghua Kong, Rong Gao
preprint en

Abstract

Abstract The multi-symplectic structure and energy conservation are inherent properties of the Gross-Pitaevskii equation. In this paper, we propose classical multi-symplectic Runge-Kutta methods and parametric multi-symplectic Runge-Kutta methods for the one-dimensional Gross-Pitaevskii equation. The parametric methods not only inherit the multi-symplectic structure and quadratic invariants of the classical methods, but also achieve energy conservation in a weaker sense by introducing an additional parameter. Numerical experiments verify the effectiveness of the proposed methods. Mathematics Subject Classification (2020) 65M06 · 65M12 · 65Z05 · 70H15

Research Square
Beijing Normal-Hong Kong Baptist University (CN), Jiangxi Normal University (CN)
Numerical methods for differential equations
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.

Laika access coming soon