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Riemannian conjugate Sobolev gradients and their application to compute ground states of BECs
Yueshan Ai, Patrick Henning, Mahima Yadav and Sitong Yuan Journal of Computational and Applied Mathematics 473 116866 (2026) https://doi.org/10.1016/j.cam.2025.116866
Neural network acceleration of iterative methods for nonlinear Schrödinger eigenvalue problems
Daniel Peterseim, Jan-Frederik Pietschmann, Jonas Püschel and Kilian Rueß Journal of Computational and Applied Mathematics 485 117414 (2026) https://doi.org/10.1016/j.cam.2026.117414
A gradient flow model for the Gross-Pitaevskii problem: mathematical and numerical analysis
Tianyang Chu, Xiaoying Dai, Jing Wu and Aihui Zhou ESAIM: Mathematical Modelling and Numerical Analysis 60(3) 1297 (2026) https://doi.org/10.1051/m2an/2026034
Convergence of a Riemannian gradient method for the Gross–Pitaevskii energy functional in a rotating frame
Mixed finite elements for the Gross–Pitaevskii eigenvalue problem: a priori error analysis and guaranteed lower energy bound
Dietmar Gallistl, Moritz Hauck, Yizhou Liang and Daniel Peterseim IMA Journal of Numerical Analysis 45(3) 1320 (2025) https://doi.org/10.1093/imanum/drae048
Riemannian optimization methods for ground states of multicomponent Bose–Einstein condensates
A two level approach for simulating Bose–Einstein condensates by Localized Orthogonal Decomposition
Christian Döding, Patrick Henning, Johan Wärnegård, M. Picasso, A. Buffa, F. Nobile, S. Deparis, D. Kressner and J. Hesthaven ESAIM: Mathematical Modelling and Numerical Analysis 58(6) 2317 (2024) https://doi.org/10.1051/m2an/2024040
On the Convergence of Sobolev Gradient Flow for the Gross–Pitaevskii Eigenvalue Problem
Ziang Chen, Jianfeng Lu, Yulong Lu and Xiangxiong Zhang SIAM Journal on Numerical Analysis 62(2) 667 (2024) https://doi.org/10.1137/23M1552553
A Scalable Two-Level Domain Decomposition Eigensolver for Periodic Schrödinger Eigenstates in Anisotropically Expanding Domains