Fast algorithm for periodic density fitting for Bloch waves
Abstract
We propose an efficient algorithm for density fitting of Bloch waves for Hamiltonian
operators with periodic potential. The algorithm is based on column selection and
random Fourier projection of the orbital functions. The computational cost of the
algorithm scales as $\mathcal{O}\bigl(N_{\text{grid}} N^2 + N_{\text{grid}} NK \log
(NK)\bigr)$, where $N_{\text{grid}}$ is number of spatial grid points, $K$ is the
number of sampling $k$-points in first Brillouin zone, and $N$ is the number of bands
under consideration. We validate the algorithm by numerical examples in both two and
three dimensions.
Type
Journal articlePermalink
https://hdl.handle.net/10161/14050Collections
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Show full item recordScholars@Duke
Jianfeng Lu
Professor of Mathematics
Jianfeng Lu is an applied mathematician interested in mathematical analysis and algorithm
development for problems from computational physics, theoretical chemistry, materials
science and other related fields.More specifically, his current research focuses include:Electronic
structure and many body problems; quantum molecular dynamics; multiscale modeling
and analysis; rare events and sampling techniques.

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