Energy-adaptive Riemannian optimization on the Stiefel manifold
ESAIM: Mathematical Modelling and Numerical Analysis , Tome 56 (2022) no. 5, pp. 1629-1653

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. These problems characterize critical points of energy minimization problems on the infinite-dimensional Stiefel manifold. To efficiently compute minimizers, we propose a novel Riemannian gradient descent method induced by an energy-adaptive metric. Quantified convergence of the methods is established under suitable assumptions on the underlying problem. A non-monotone line search and the inexact evaluation of Riemannian gradients substantially improve the overall efficiency of the method. Numerical experiments illustrate the performance of the method and demonstrates its competitiveness with well-established schemes.

DOI : 10.1051/m2an/2022036
Classification : 65N25, 81Q10
Keywords: Riemannian optimization, Stiefel manifold, Kohn–Sham model, Gross–Pitaevskii eigenvalue problem, nonlinear eigenvector problem
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     author = {Altmann, Robert and Peterseim, Daniel and Stykel, Tatjana},
     title = {Energy-adaptive {Riemannian} optimization on the {Stiefel} manifold},
     journal = {ESAIM: Mathematical Modelling and Numerical Analysis },
     pages = {1629--1653},
     year = {2022},
     publisher = {EDP-Sciences},
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     doi = {10.1051/m2an/2022036},
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     zbl = {1502.65177},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/m2an/2022036/}
}
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Altmann, Robert; Peterseim, Daniel; Stykel, Tatjana. Energy-adaptive Riemannian optimization on the Stiefel manifold. ESAIM: Mathematical Modelling and Numerical Analysis , Tome 56 (2022) no. 5, pp. 1629-1653. doi: 10.1051/m2an/2022036

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