arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2011.11917physics.comp-ph
收藏

Tensor-structured algorithm for reduced-order scaling large-scale Kohn-Sham density functional theory calculations

Chih-Chuen Lin, Phani Motamarri, Vikram Gavini

英文摘要:

We present a tensor-structured algorithm for efficient large-scale DFT calculations by constructing a Tucker tensor basis that is adapted to the Kohn-Sham Hamiltonian and localized in real-space. The proposed approach uses an additive separable approximation to the Kohn-Sham Hamiltonian and an $L_1$ localization technique to generate the 1-D localized functions that constitute the Tucker tensor basis. Numerical results show that the resulting Tucker tensor basis exhibits exponential convergence in the ground-state energy with increasing Tucker rank. Further, the proposed tensor-structured algorithm demonstrated sub-quadratic scaling with system size for both systems with and without a gap, and involving many thousands of atoms. This reduced-order scaling has also resulted in the proposed approach outperforming plane-wave DFT implementation for systems beyond 2,000 electrons.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑