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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2406.01635 |
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| _version_ | 1866916272517677056 |
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| 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 |