Finding excesses in model parameter space
Abstract Simulation-based inference (SBI) makes it possible to infer the parameters of a model from high-dimensional low-level features of the observed events. In this work we show how this method can be used to establish the presence of a weak signal on top of an unknown background, to discard back...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-02-01
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| Series: | European Physical Journal C: Particles and Fields |
| Online Access: | https://doi.org/10.1140/epjc/s10052-025-13795-w |
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| _version_ | 1823861669526241280 |
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| author | Kierthika Chathirathas Torben Ferber Felix Kahlhoefer Alessandro Morandini |
| author_facet | Kierthika Chathirathas Torben Ferber Felix Kahlhoefer Alessandro Morandini |
| author_sort | Kierthika Chathirathas |
| collection | DOAJ |
| description | Abstract Simulation-based inference (SBI) makes it possible to infer the parameters of a model from high-dimensional low-level features of the observed events. In this work we show how this method can be used to establish the presence of a weak signal on top of an unknown background, to discard background events and to determine the signal properties. The key idea is to use SBI methods to identify events that are similar to each other in the sense that they agree on the inferred model parameters. We illustrate this method for the case of axion-like particles decaying to photons at beam-dump experiments. For poor detector resolution the diphoton mass cannot be reliably reconstructed, so there is no simple high-level observable that can be used to perform a bump hunt. Since the SBI methods do not require explicit high-level observables, they offer a promising alternative to increase the sensitivity to new physics. |
| format | Article |
| id | doaj-art-b49b830000f54f49b84f148474587a8a |
| institution | Kabale University |
| issn | 1434-6052 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | European Physical Journal C: Particles and Fields |
| spelling | doaj-art-b49b830000f54f49b84f148474587a8a2025-02-09T12:51:50ZengSpringerOpenEuropean Physical Journal C: Particles and Fields1434-60522025-02-0185212110.1140/epjc/s10052-025-13795-wFinding excesses in model parameter spaceKierthika Chathirathas0Torben Ferber1Felix Kahlhoefer2Alessandro Morandini3Institute for Astroparticle Physics (IAP), Karlsruhe Institute of Technology (KIT)Institute of Experimental Particle Physics (ETP), Karlsruhe Institute of Technology (KIT)Institute for Theoretical Particle Physics (TTP), Karlsruhe Institute of Technology (KIT)Institute for Astroparticle Physics (IAP), Karlsruhe Institute of Technology (KIT)Abstract Simulation-based inference (SBI) makes it possible to infer the parameters of a model from high-dimensional low-level features of the observed events. In this work we show how this method can be used to establish the presence of a weak signal on top of an unknown background, to discard background events and to determine the signal properties. The key idea is to use SBI methods to identify events that are similar to each other in the sense that they agree on the inferred model parameters. We illustrate this method for the case of axion-like particles decaying to photons at beam-dump experiments. For poor detector resolution the diphoton mass cannot be reliably reconstructed, so there is no simple high-level observable that can be used to perform a bump hunt. Since the SBI methods do not require explicit high-level observables, they offer a promising alternative to increase the sensitivity to new physics.https://doi.org/10.1140/epjc/s10052-025-13795-w |
| spellingShingle | Kierthika Chathirathas Torben Ferber Felix Kahlhoefer Alessandro Morandini Finding excesses in model parameter space European Physical Journal C: Particles and Fields |
| title | Finding excesses in model parameter space |
| title_full | Finding excesses in model parameter space |
| title_fullStr | Finding excesses in model parameter space |
| title_full_unstemmed | Finding excesses in model parameter space |
| title_short | Finding excesses in model parameter space |
| title_sort | finding excesses in model parameter space |
| url | https://doi.org/10.1140/epjc/s10052-025-13795-w |
| work_keys_str_mv | AT kierthikachathirathas findingexcessesinmodelparameterspace AT torbenferber findingexcessesinmodelparameterspace AT felixkahlhoefer findingexcessesinmodelparameterspace AT alessandromorandini findingexcessesinmodelparameterspace |