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Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning
March 12, 2024, 4:45 a.m. | He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao
cs.LG updates on arXiv.org arxiv.org
Abstract: Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a lower cost scaling than the prevailing Kohn-Sham DFT, which is increasingly desired for contemporary molecular research. However, its accuracy is limited by the kinetic energy density functional, which is notoriously hard to approximate for non-periodic molecular systems. Here we propose M-OFDFT, an OFDFT approach capable of solving molecular systems using a deep learning functional model. We build the essential non-locality into the …
abstract accuracy arxiv chemistry cost cs.lg deep learning energy free functional however physics.chem-ph quantum quantum chemistry research scaling stat.ml systems theory type
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