Abstract
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.
Content
Reinforcement Learning Configuration Interaction
Working Paper
Authors
- Joshua Goings
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University of Washington
, - Hang Hu ,
- Chao Yang ,
- Xiaosong Li
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The content is available under CC BY 4.0 License
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DOI
Funding
Basic Energy Sciences
DE-SC0021100
From Accurate Variational Relativistic Electronic Structure Theory to Practical Applications in Heavy-Element Chemistry
Directorate for Computer & Information Science & Engineering
1663636
SI2-SSI: Sustainable Open-Source Quantum Dynamics and Spectroscopy Software
Author’s competing interest statement
No conflict of interest
Keywords
Reinforcement Learning
Strong Correlation
Machine Learning
Quantum Chemistry
Electronic Structure
Computational Chemistry
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This content is an early or alternative research output and has not been peer-reviewed at the time of posting.