{"title":"Machine Learning in the Problem of Extrapolating Variational Calculations\u0000in Nuclear Physics","authors":"A. Mazur, R. E. Sharypov, A. M. Shirokov","doi":"10.55959/msu0579-9392.79.2430202","DOIUrl":"https://doi.org/10.55959/msu0579-9392.79.2430202","url":null,"abstract":"A modified machine learning method is proposed, utilizing an ensemble of artificial neural networks for the\u0000extrapolation of energies obtained in variational calculations, specifically in the No-core Shell Model (NCSM),\u0000to the case of the infinite basis. A new neural network topology is employed, and criteria for selecting both the\u0000data used for training and the trained neural networks for statistical analysis of the results are formulated.\u0000The approach is tested by extrapolating the deutron ground state energy in calculations with the Nijmegen II\u0000NN interaction and provides statistically significant results. This technique is applied to obtain extrapolated\u0000ground state energies of 6Li and 6He nuclei based on the NCSM calculations with Daejeon16 NN interaction.","PeriodicalId":399279,"journal":{"name":"Seriya 3: Fizika, Astronomiya","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}