{"title":"SwdFold:基于最优传输理论的重权重和展开方法","authors":"Chu-Cheng Pan, Xiang Dong, Yu-Chang Sun, Ao-Yan Cheng, Ao-Bo Wang, Yu-Xuan Hu, Hao Cai","doi":"arxiv-2406.01635","DOIUrl":null,"url":null,"abstract":"High-energy physics experiments rely heavily on precise measurements of\nenergy and momentum, yet face significant challenges due to detector\nlimitations, calibration errors, and the intrinsic nature of particle\ninteractions. Traditional unfolding techniques have been employed to correct\nfor these distortions, yet they often suffer from model dependency and\nstability issues. We present a novel method, SwdFold, which utilizes the\nprinciples of optimal transport to provide a robust, model-independent\nframework to estimate the probability density ratio for data unfolding. It not\nonly unfold the toy experimental event by reweighted simulated data\ndistributions closely with true distributions but also maintains the integrity\nof physical features across various observables. We can expect it can enable\nmore reliable predictions and comprehensive analyses as a high precision\nreweighting and unfolding tool in high-energy physics.","PeriodicalId":501065,"journal":{"name":"arXiv - PHYS - Data Analysis, Statistics and Probability","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory\",\"authors\":\"Chu-Cheng Pan, Xiang Dong, Yu-Chang Sun, Ao-Yan Cheng, Ao-Bo Wang, Yu-Xuan Hu, Hao Cai\",\"doi\":\"arxiv-2406.01635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-energy physics experiments rely heavily on precise measurements of\\nenergy and momentum, yet face significant challenges due to detector\\nlimitations, calibration errors, and the intrinsic nature of particle\\ninteractions. Traditional unfolding techniques have been employed to correct\\nfor these distortions, yet they often suffer from model dependency and\\nstability issues. We present a novel method, SwdFold, which utilizes the\\nprinciples of optimal transport to provide a robust, model-independent\\nframework to estimate the probability density ratio for data unfolding. It not\\nonly unfold the toy experimental event by reweighted simulated data\\ndistributions closely with true distributions but also maintains the integrity\\nof physical features across various observables. We can expect it can enable\\nmore reliable predictions and comprehensive analyses as a high precision\\nreweighting and unfolding tool in high-energy physics.\",\"PeriodicalId\":501065,\"journal\":{\"name\":\"arXiv - PHYS - Data Analysis, Statistics and Probability\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - PHYS - Data Analysis, Statistics and Probability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2406.01635\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Data Analysis, Statistics and Probability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2406.01635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory
High-energy physics experiments rely heavily on precise measurements of
energy and momentum, yet face significant challenges due to detector
limitations, calibration errors, and the intrinsic nature of particle
interactions. Traditional unfolding techniques have been employed to correct
for these distortions, yet they often suffer from model dependency and
stability issues. We present a novel method, SwdFold, which utilizes the
principles of optimal transport to provide a robust, model-independent
framework to estimate the probability density ratio for data unfolding. It not
only unfold the toy experimental event by reweighted simulated data
distributions closely with true distributions but also maintains the integrity
of physical features across various observables. We can expect it can enable
more reliable predictions and comprehensive analyses as a high precision
reweighting and unfolding tool in high-energy physics.