In this paper we revisit a two-level discretization based on localized orthogonal
decomposition (LOD). It was originally proposed in [P. Henning, A. Målqvist, and D …

This article is concerned with the numerical solution of subspace optimization problems,
consisting of minimizing a smooth functional over the set of orthogonal projectors of fixed …

In this article, we present an overview of different a posteriori error analysis and post-
processing methods proposed in the context of nonlinear eigenvalue problems, eg arising in …

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 …

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 …

This paper addresses the numerical solution of nonlinear eigenvector problems such as the
Gross–Pitaevskii and Kohn–Sham equation arising in computational physics and chemistry …

Second-order flows in this paper refer to some artificial evolutionary differential equations
involving second-order time derivatives distinguished from gradient flows which are …

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 …

The ground states of Bose–Einstein condensates in a rotating frame can be described as
constrained minimizers of the Gross–Pitaevskii energy functional with an angular …

We establish an a priori error analysis for the lowest-order Raviart–Thomas finite element
discretization of the nonlinear Gross-Pitaevskii eigenvalue problem. Optimal convergence …