An efficient Fourier spectral algorithm for the Bogoliubov-de Gennes excitation eigenvalue problem
Yu Li, Zhixuan Li, Manting Xie, Yong Zhang

TL;DR
This paper introduces a fast, stable Fourier spectral algorithm for solving the Bogoliubov-de Gennes eigenvalue problem in spin-1 Bose-Einstein condensates, enabling efficient analysis of elementary excitations in large-scale systems.
Contribution
It develops a matrix-free, FFT-accelerated spectral method with a stable bi-orthogonal iterative solver for large eigenvalue problems in BECs, with rigorous analysis and extensive numerical validation.
Findings
The algorithm achieves spectral accuracy and efficiency.
It effectively computes excitation spectra in 1-3 dimensions.
The solver is memory-efficient and suitable for large-scale problems.
Abstract
In this paper, we propose an efficient Fourier spectral algorithm for an eigenvalue problem, that is, the Bogoliubov-de Gennes (BdG) equation arsing from spin-1 Bose-Einstein condensates (BEC) to describe the elementary/collective excitations around the mean-field ground state. The BdG equation is essentially a constrained eigenvalue/eigenfunction system. Firstly, we investigate its analytical properties, including exact eigenpairs, generalized nullspace, and bi-orthogonality of eigenspaces. Secondly, by combining the standard Fourier spectral method for spatial discretization and a stable Gram-Schmidt bi-orthogonal algorithm, we develop a subspace iterative solver for such a large-scale dense eigenvalue problem, and it proves to be numerically stable, efficient, and accurate. Our solver is matrix-free and the operator-function evaluation is accelerated by discrete Fast Fourier…
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Taxonomy
TopicsCold Atom Physics and Bose-Einstein Condensates · Quantum Information and Cryptography · Numerical methods for differential equations
