Scalable multi-task learning for particle collision event reconstruction with heterogeneous graph neural networks

The growing luminosity frontier at the Large Hadron Collider is challenging the reconstruction and analysis of particle collision events. Increased particle multiplicities are straining latency and storage requirements at the data acquisition stage, while new complications are emerging, including hi...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	William Sutcliffe, Marta Calvi, Simone Capelli, Jonas Eschle, Julián García Pardiñas, Abhijit Mathad, Azusa Uzuki, Nicola Serra
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	IOP Publishing 2025-01-01
Σειρά:	Machine Learning: Science and Technology
Θέματα:	heterogeneous graph neural networks multi-task learning graph pruning particle physics particle collision event reconstruction scalable
Διαθέσιμο Online:	https://doi.org/10.1088/2632-2153/ae22be
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