SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Pan, Chu-Cheng, Dong, Xiang, Sun, Yu-Chang, Cheng, Ao-Yan, Wang, Ao-Bo, Hu, Yu-Xuan, Cai, Hao
Formato:	Preprint
Publicado:	2024
Materias:	Data Analysis, Statistics and Probability High Energy Physics - Experiment
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

_version_	1866916272517677056
author	Pan, Chu-Cheng Dong, Xiang Sun, Yu-Chang Cheng, Ao-Yan Wang, Ao-Bo Hu, Yu-Xuan Cai, Hao
author_facet	Pan, Chu-Cheng Dong, Xiang Sun, Yu-Chang Cheng, Ao-Yan Wang, Ao-Bo Hu, Yu-Xuan Cai, Hao
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2406_01635
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory Pan, Chu-Cheng Dong, Xiang Sun, Yu-Chang Cheng, Ao-Yan Wang, Ao-Bo Hu, Yu-Xuan Cai, Hao Data Analysis, Statistics and Probability High Energy Physics - Experiment 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.
title	SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory
topic	Data Analysis, Statistics and Probability High Energy Physics - Experiment
url	https://arxiv.org/abs/2406.01635

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