Russo, G. (2024) Searches for Anomalies in hadronic final states with GNNs in ATLAS. Il nuovo cimento C, 47 (3). pp. 1-4. ISSN 1826-9885
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Abstract
Graph neural networks are a promising technique for Anomaly Detection whenever it is possible to express detector information in the form of a graph. In our approach, graphs can be used to represent heavy resonance boson jets as interconnected topocluster nodes. By leveraging graph information and message passing, the network can identify unexpected signals deviating from the Standard Model.
| Item Type: | Article |
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| Subjects: | 500 Scienze naturali e Matematica > 530 Fisica |
| Depositing User: | Marina Spanti |
| Date Deposited: | 29 Jul 2024 14:08 |
| Last Modified: | 29 Jul 2024 14:08 |
| URI: | http://eprints.bice.rm.cnr.it/id/eprint/23062 |
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