Using Machine Learning to Find New Density Functionals

• URL: http://arxiv.org/abs/2112.05554v1
• Date: Sat, 4 Dec 2021 00:49:26 GMT
• Title: Using Machine Learning to Find New Density Functionals
• Authors: Bhupalee Kalita and Kieron Burke
• Abstract summary: This draft is a part of the "Roadmap on Machine Learning in Electronic Structure" to be published in Electronic Structure (EST) We briefly discuss the status of this field and point out some current and future challenges. We also talk about how state-of-the-art science and technology tools can help overcome these challenges.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Machine learning has now become an integral part of research and innovation. The field of machine learning density functional theory has continuously expanded over the years while making several noticeable advances. We briefly discuss the status of this field and point out some current and future challenges. We also talk about how state-of-the-art science and technology tools can help overcome these challenges. This draft is a part of the "Roadmap on Machine Learning in Electronic Structure" to be published in Electronic Structure (EST).

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