R&D of the EM Calorimeter Energy Calibration with Machine Learning based on the low-level features of the Cluster

R&D of the EM Calorimeter Energy Calibration with Machine Learning based on the low-level features of the Cluster

We have developed an energy calibration method using machine learning for the ILC electromagnetic (EM) calorimeter (ECAL), a sampling calorimeter consisting of Silicon-Tungsten layers. In this method, we use a deep neural network (DNN) for a regression to determine the energy of incident EM particle...

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Bibliographic Details
Main Authors: Morimasa Suzuna, Iwasaki Masako, Suehara Taikan, Tanaka Junichi, Saito Masahiko, Nagahara Hajime, Nakashima Yuta, Takemura Noriko, Nakano Takashi
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:EPJ Web of Conferences
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2024/25/epjconf_lcws2024_03012.pdf
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https://www.epj-conferences.org/articles/epjconf/pdf/2024/25/epjconf_lcws2024_03012.pdf

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