NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry-Reference-Cited by-同舟云学术

NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry

Published:2023-11-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
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Author:

Wu Yangjun¹²^ORCID,Guo Chu³^ORCID,Fan Yi⁴^ORCID,Zhou Pengyu¹²^ORCID,Shang Honghui⁴^ORCID

Affiliation:

1. Institute of Computing Technology, Beijing, China

2. University of Chinese Academy of Sciences, Beijing, China

3. Hunan Normal University, Changshang, China

4. University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581784.3607061

Reference43 articles.

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3. Ireneusz W Bulik , Thomas M Henderson , and Gustavo E Scuseria . Can single-reference coupled cluster theory describe static correlation? Journal of chemical theory and computation, 11(7):3171--3179 , 2015 . Ireneusz W Bulik, Thomas M Henderson, and Gustavo E Scuseria. Can single-reference coupled cluster theory describe static correlation? Journal of chemical theory and computation, 11(7):3171--3179, 2015.

4. Density matrix formulation for quantum renormalization groups

5. Density-matrix algorithms for quantum renormalization groups

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