تقرير
The Mass-ive Issue: Anomaly Detection in Jet Physics
| العنوان: | The Mass-ive Issue: Anomaly Detection in Jet Physics |
|---|---|
| المؤلفون: | Golling, Tobias, Nobe, Takuya, Proios, Dimitrios, Raine, John Andrew, Sengupta, Debajyoti, Voloshynovskiy, Slava, Arguin, Jean-Francois, Martin, Julien Leissner, Pilette, Jacinthe, Gupta, Debottam Bakshi, Farbin, Amir |
| سنة النشر: | 2023 |
| المجموعة: | High Energy Physics - Phenomenology |
| مصطلحات موضوعية: | High Energy Physics - Phenomenology |
| الوصف: | In the hunt for new and unobserved phenomena in particle physics, attention has turned in recent years to using advanced machine learning techniques for model independent searches. In this paper we highlight the main challenge of applying anomaly detection to jet physics, where preserving an unbiased estimator of the jet mass remains a critical piece of any model independent search. Using Variational Autoencoders and multiple industry-standard anomaly detection metrics, we demonstrate the unavoidable nature of this problem. Comment: 6 pages, 5 figures. Accepted at Third Workshop on Machine Learning and the Physical Sciences (NeurIPS 2020) |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2303.14134 |
| رقم الأكسشن: | edsarx.2303.14134 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |