{"title":"Computing the QRPA Level Density with the Finite Amplitude Method","authors":"Antonio Bjelčić, Nicolas Schunck","doi":"arxiv-2409.07644","DOIUrl":null,"url":null,"abstract":"We describe a new algorithm to calculate the vibrational nuclear level\ndensity of an atomic nucleus. Fictitious perturbation operators that probe the\nresponse of the system are generated by drawing their matrix elements from some\nprobability distribution function. We use the Finite Amplitude Method to\nexplicitly compute the response for each such sample. With the help of the\nKernel Polynomial Method, we build an estimator of the vibrational level\ndensity and provide the upper bound of the relative error in the limit of\ninfinitely many random samples. The new algorithm can give accurate estimates\nof the vibrational level density. Since it is based on drawing multiple samples\nof perturbation operators, its computational implementation is naturally\nparallel and scales like the number of available processing units.","PeriodicalId":501573,"journal":{"name":"arXiv - PHYS - Nuclear Theory","volume":"401 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Nuclear Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.07644","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
We describe a new algorithm to calculate the vibrational nuclear level
density of an atomic nucleus. Fictitious perturbation operators that probe the
response of the system are generated by drawing their matrix elements from some
probability distribution function. We use the Finite Amplitude Method to
explicitly compute the response for each such sample. With the help of the
Kernel Polynomial Method, we build an estimator of the vibrational level
density and provide the upper bound of the relative error in the limit of
infinitely many random samples. The new algorithm can give accurate estimates
of the vibrational level density. Since it is based on drawing multiple samples
of perturbation operators, its computational implementation is naturally
parallel and scales like the number of available processing units.