Reinforcement Learning Configuration Interaction

07 July 2021, Version 3
This content is a preprint and has not undergone peer review at the time of posting.

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.

Keywords

Reinforcement Learning
Strong Correlation
Machine Learning
Quantum Chemistry
Electronic Structure
Computational Chemistry

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.