NNQS-Transformer: An Efficient and Scalable Neural Network Quantum States Approach for Ab Initio Quantum Chemistry

Neural network quantum state (NNQS) has emerged as a promising candidate for quantum many-body problems, but its practical applications are often hindered by the high cost of sampling and local energy calculation. We develop a high-performance NNQS method for ab initio electronic structure calculati...

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Bibliographic Details

Published in:	International Conference for High Performance Computing, Networking, Storage and Analysis (Online) pp. 1 - 14
Main Authors:	Wu, Yangjun, Guo, Chu, Fan, Yi, Zhou, Pengyu, Shang, Honghui
Format:	Conference Proceeding
Language:	English
Published:	ACM 11.11.2023
Subjects:	Artificial neural networks autoregressive sampling Costs Graphics processing units High performance computing many-body Schrödinger equation neural network quantum state Quantum chemistry Scalability Technological innovation transformer based architecture
ISSN:	2167-4337
Online Access:	Get full text
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