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Reinforcement_Learning_Configuration_Interaction.pdf (3.85 MB)

Reinforcement Learning Configuration Interaction

preprint
revised on 03.05.2021, 23:55 and posted on 05.05.2021, 12:25 by Joshua Goings, Hang Hu, Chao Yang, Xiaosong Li
A reinforcement learning algorithm is developed for the selected configuration interaction problem. We explore how reinforcement learning can obtain compact wave functions at near full configuration interaction accuracy.

Funding

From Accurate Variational Relativistic Electronic Structure Theory to Practical Applications in Heavy-Element Chemistry

Basic Energy Sciences

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SI2-SSI: Sustainable Open-Source Quantum Dynamics and Spectroscopy Software

Directorate for Computer & Information Science & Engineering

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History

Email Address of Submitting Author

jjgoings@uw.edu

Institution

University of Washington

Country

United States

ORCID For Submitting Author

0000-0002-2817-1966

Declaration of Conflict of Interest

No conflict of interest

Licence

Exports