GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter

We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Neural Networks (GNNs) and directly analyzes the hits in each HGCAL endcap. The ML algorithm is trained to predict cluster...

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Detalles Bibliográficos
Autores principales: Bhattacharya, Saptaparna, Chernyavskaya, Nadezda, Ghosh, Saranya, Gray, Lindsey, Kieseler, Jan, Klijnsma, Thomas, Long, Kenneth, Nawaz, Raheel, Pedro, Kevin, Pierini, Maurizio, Pradhan, Gauri, Qasim, Shah Rukh, Viazlo, Oleksander, Zehetner, Philipp
Lenguaje:eng
Publicado: 2022
Materias:
Particle Physics - Experiment
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/2438/1/012090
http://cds.cern.ch/record/2803236

Internet

https://dx.doi.org/10.1088/1742-6596/2438/1/012090
http://cds.cern.ch/record/2803236

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