G. Lasche, R. Coldwell, J. Nobel, A. C. Rester, J. Trombka
{"title":"Spectral analysis in high radiation space backgrounds with robust fitting","authors":"G. Lasche, R. Coldwell, J. Nobel, A. C. Rester, J. Trombka","doi":"10.1109/CHERBS.1997.660246","DOIUrl":null,"url":null,"abstract":"An advanced derivative of ROBFIT spectral analysis software is tested for its ability to fit spectra from space. The approach, which emphasizes the background shape function, is uniquely suited to the identification of weak-strength nuclides in high-radiation environments, and for analyses in which a suitable off-source background spectrum may not be available. Compared to earlier analysis using on-source/off-source subtraction, all data from SN 1987A were combined and reanalyzed with significant improvement in results.","PeriodicalId":197895,"journal":{"name":"Conference on the High Energy Radiation Background in Space. Workshop Record","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on the High Energy Radiation Background in Space. Workshop Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CHERBS.1997.660246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
An advanced derivative of ROBFIT spectral analysis software is tested for its ability to fit spectra from space. The approach, which emphasizes the background shape function, is uniquely suited to the identification of weak-strength nuclides in high-radiation environments, and for analyses in which a suitable off-source background spectrum may not be available. Compared to earlier analysis using on-source/off-source subtraction, all data from SN 1987A were combined and reanalyzed with significant improvement in results.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
