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https://hdl.handle.net/2445/192647| Title: | Deep learning exotic hadrons |
| Author: | Ng, L. Bibrzycki, Ł Nys, J. Fernandez-Ramirez, César Pillon, Alessandro Mathieu, Vicent Rasmusson, A. J. Szczepaniak, Adam Pawel |
| Keywords: | Quarks Partícules (Matèria) Quarks Particles |
| Issue Date: | 17-May-2022 |
| Publisher: | American Physical Society |
| Abstract: | We perform the first amplitude analysis of experimental data using deep neural networks to determine the nature of an exotic hadron. Specifically, we study the line shape of the Pc(4312) signal reported by the LHCb collaboration, and we find that its most likely interpretation is that of a virtual state. This method can be applied to other near-threshold resonance candidates. |
| Note: | Reproducció del document publicat a: https://doi.org/10.1103/PhysRevD.105.L091501 |
| It is part of: | Physical Review D, 2022, vol. 105, num. 9, p. L091501-1-L091501-6 |
| URI: | https://hdl.handle.net/2445/192647 |
| Related resource: | https://doi.org/10.1103/PhysRevD.105.L091501 |
| ISSN: | 1550-7998 |
| Appears in Collections: | Articles publicats en revistes (Física Quàntica i Astrofísica) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 725660.pdf | 573.32 kB | Adobe PDF | View/Open |
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