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We propose a new normalized Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem based on an energy inner product that depends on time through the density of the flow itself. The gradient flow is well-defined and converges to…

Numerical Analysis · Mathematics 2020-04-03 Patrick Henning , Daniel Peterseim

We study the convergences of three projected Sobolev gradient flows to the ground state of the Gross-Pitaevskii eigenvalue problem. They are constructed as the gradient flows of the Gross-Pitaevskii energy functional with respect to the…

Numerical Analysis · Mathematics 2023-11-30 Ziang Chen , Jianfeng Lu , Yulong Lu , Xiangxiong Zhang

This article deals with the stationary Gross-Pitaevskii non-linear eigenvalue problem in the presence of a rotating magnetic field that is used to model macroscopic quantum effects such as Bose-Einstein condensates (BECs). In this regime,…

Numerical Analysis · Mathematics 2025-12-19 Pascal Heid , Paul Houston , Benjamin Stamm , Thomas P. Wihler

We propose a positivity preserving finite element discretization for the nonlinear Gross-Pitaevskii eigenvalue problem. The method employs mass lumping techniques, which allow to transfer the uniqueness up to sign and positivity properties…

Numerical Analysis · Mathematics 2024-05-28 Moritz Hauck , Yizhou Liang , Daniel Peterseim

This paper studies the $J$-method of [E. Jarlebring, S. Kvaal, W. Michiels. SIAM J. Sci. Comput. 36-4:A1978-A2001, 2014] for nonlinear eigenvector problems in a general Hilbert space framework. This is the basis for variational…

Numerical Analysis · Mathematics 2020-12-10 Robert Altmann , Patrick Henning , Daniel Peterseim

In this paper we improve traditional steepest descent methods for the direct minimization of the Gross-Pitaevskii (GP) energy with rotation at two levels. We first define a new inner product to equip the Sobolev space $H^1$ and derive the…

Quantum Gases · Physics 2010-06-01 Ionut Danaila , Parimah Kazemi

We present an effective adaptive procedure for the numerical approximation of the steady-state Gross-Pitaevskii equation. Our approach is solely based on energy minimization, and consists of a combination of gradient flow iterations and…

Numerical Analysis · Mathematics 2020-01-16 Pascal Heid , Benjamin Stamm , Thomas P. Wihler

We study the regularity in weighted Sobolev spaces of Schr\"{o}dinger-type eigenvalue problems, and we analyse their approximation via a discontinuous Galerkin (dG) $hp$ finite element method. In particular, we show that, for a class of…

Numerical Analysis · Mathematics 2019-12-17 Yvon Maday , Carlo Marcati

This paper develops and analyzes a semi-discrete and a fully discrete finite element method for a one-dimensional quasilinear parabolic stochastic partial differential equation (SPDE) which describes the stochastic mean curvature flow for…

Numerical Analysis · Mathematics 2013-03-26 Xiaobing Feng , Yukun Li , Andreas Prohl

We establish an a priori error analysis for the lowest-order Raviart-Thomas finite element discretisation of the nonlinear Gross-Pitaevskii eigenvalue problem. Optimal convergence rates are obtained for the primal and dual variables as well…

Numerical Analysis · Mathematics 2024-02-12 Dietmar Gallistl , Moritz Hauck , Yizhou Liang , Daniel Peterseim

This paper concerns the mathematical and numerical analysis of the $L^2$ 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…

Numerical Analysis · Mathematics 2025-11-03 Tianyang Chu , Xiaoying Dai , Jing Wu , Aihui Zhou

We study the approximation by a semi-discrete finite-volume scheme of the Gross-Pitaevskii equation with time-dependent potential in two dimensions, performing a two-point flux approximation scheme in space. We rigorously analyze the error…

Numerical Analysis · Mathematics 2025-09-11 Quentin Chauleur

We compute the ground state $u$ of the Gross--Pitaevskii equation (GPE) via Wasserstein gradient descent in diffeomorphism space. We represent the density $\rho=u^2$ as the push-forward of a fixed reference measure through a parameterized…

Numerical Analysis · Mathematics 2026-03-17 Xiangxiong Zhang , Haomin Zhou

In this paper, we present a systematic study on the ground state computation of quantum droplets in homonuclear Bose-Bose mixtures, governed by the extended Gross-Pitaevskii equations (eGPEs) with Lee-Huang-Yang (LHY) corrections. This…

Quantum Gases · Physics 2026-04-02 Wei Liu , Limin Xu

In this article, we propose a unified framework for preconditioned Riemannian gradient (P-RG) methods to minimize Gross-Pitaevskii (GP) energy functionals with rotation on a Riemannian manifold. This framework enables comprehensive analysis…

Numerical Analysis · Mathematics 2026-04-03 Zixu Feng , Qinglin Tang

We develop and analyse finite volume methods for the Poisson problem with boundary conditions involving oblique derivatives. We design a generic framework, for finite volume discretisations of such models, in which internal fluxes are not…

Numerical Analysis · Mathematics 2019-08-12 Jerome Droniou , Matej Medla , Karol Mikula

Divergence-free discontinuous Galerkin (DG) finite element methods offer a suitable discretization for the pointwise divergence-free numerical solution of Borrvall and Petersson's model for the topology optimization of fluids in Stokes flow…

Numerical Analysis · Mathematics 2022-02-22 Ioannis P. A. Papadopoulos

We present an effective numerical procedure, which is based on the computational scheme from [Heid et al., arXiv:1906.06954], for the numerical approximation of excited states of Schr\"odingers equation. In particular, this procedure…

Numerical Analysis · Mathematics 2021-09-16 Pascal Heid

This paper investigates the numerical approximation of ground states of rotating Bose-Einstein condensates. This problem requires the minimization of the Gross-Pitaevskii energy $E$ on a Hilbert manifold $\mathbb{S}$. To find a…

Numerical Analysis · Mathematics 2025-03-19 Patrick Henning , Mahima Yadav

We perform numerical analysis of a nonlinear gradient flow, which can be regarded as a parabolic minimal surface problem or a regularised total variation flow, using the gradient discretisation method (GDM). GDM is a unified convergence…

Numerical Analysis · Mathematics 2026-04-21 Jerome Droniou , Kim-Ngan Le , Huateng Zhu
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