{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-learning-and-the-schrodinger-equation","title":"Deep learning and the Schrödinger equation","arxiv_id":"1702.01361","date":"2017-02-05","proceeding":null,"authors":["Kyle Mills","Michael Spanner","Isaac Tamblyn"],"abstract":"We have trained a deep (convolutional) neural network to predict the\nground-state energy of an electron in four classes of confining two-dimensional\nelectrostatic potentials. On randomly generated potentials, for which there is\nno analytic form for either the potential or the ground-state energy, the\nneural network model was able to predict the ground-state energy to within\nchemical accuracy, with a median absolute error of 1.49 mHa. We also\ninvestigate the performance of the model in predicting other quantities such as\nthe kinetic energy and the first excited-state energy of random potentials.","url_abs":"http://arxiv.org/abs/1702.01361v3","url_pdf":"http://arxiv.org/pdf/1702.01361v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-learning-and-the-schrodinger-equation","repo_url":"https://github.com/DavorPenzar/diplomski","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}