STI Publications - View Publication Form #21724

Back to Search Results Print
Publication Information
Title The optimal use of segmentation for sampling calorimeters
Abstract One of the key design choices of any sampling calorimeter is how fine to make the longitudinal and transverse segmentation. To inform this choice, we study the impact of calorimeter segmentation on energy reconstruction. To ensure that the trends are due entirely to hardware and not to a sub?optimal use of segmentation, we deploy deep neural networks to perform the reconstruction. These networks make use of all available information by representing the calorimeter as a point cloud. To demonstrate our approach, we simulate a detector similar to the forward calorimeter system intended for use in the ePIC detector, which will operate at the upcoming Electron Ion Collider. We find that for the energy estimation of isolated charged pion showers, relatively fine longitudinal segmentation is key to achieving an energy resolution that is better than 10% across the full phase space. These results provide a valuable benchmark for ongoing EIC detector optimizations and may also inform fu
Author(s) Fernando Torales-Acosta, Bishnu Karki, Piyush Karande, Aaron Angerami, Miguel Arratia, Kenneth Barish, Ryan Milton, Sebastian Moran Vasquez, Benjamin Nachman, Anshuman Sinha
Publication Date June 2024
Document Type Journal Article
Primary Institution Lawrence Livermore National Laboratory, Livermore, CA
Affiliation Exp Nuclear Physics / Experimental Halls / Hall B
Funding Source Nuclear Physics (NP)
Proprietary? No
This publication conveys Technical Science Results
Document Numbers
JLAB Number: JLAB-PHY-24-4090 OSTI Number: 2376903
LANL Number: arXiv:2310.04442 Other Number: DOE/OR/23177-7530
Associated with an experiment No
Associated with EIC No
Supported by Jefferson Lab LDRD Funding No
Journal Article
Journal Name Journal of Instrumentation
Refereed No
Volume 19
Issue
Page(s) P06002
Attachments/Datasets/DOI Link
Document(s)
2310.04442v1.pdf (STI Document)
2310.04442v1.pdf (Accepted Manuscript)
DOI Link
Dataset(s) (none)
Back to Search Results Print