{"title":"Neuromorphic improvement of the Weizsäecker formula","authors":"M. Dima","doi":"10.22323/1.429.0029","DOIUrl":null,"url":null,"abstract":"Yearly, nuclide mass data is fitted to improved versions of the Bethe-Weizsäecker formula. The present attempt at furthering the precision of this endeavor aims to reach beyond just precision, and obtain predictive capability about the \"Stability Island\" of nuclides. The method is to perform a fit to a recent improved liquid drop model with isotonic shift. The residuals are then fed to a neural network, with a number of \"feature\" quantities. The results are then discussed in view of their perspective to predict the \"Stability Island\".","PeriodicalId":262901,"journal":{"name":"Proceedings of The 6th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2022)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of The 6th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22323/1.429.0029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Yearly, nuclide mass data is fitted to improved versions of the Bethe-Weizsäecker formula. The present attempt at furthering the precision of this endeavor aims to reach beyond just precision, and obtain predictive capability about the "Stability Island" of nuclides. The method is to perform a fit to a recent improved liquid drop model with isotonic shift. The residuals are then fed to a neural network, with a number of "feature" quantities. The results are then discussed in view of their perspective to predict the "Stability Island".