Review of energy reconstruction algorithms in the CMS Hadron Calorimeter

Energy reconstruction is a crucial step for all calorimeters, which takes the digitized signal as input, and outputs the energy of the sample of interest. This paper introduces different energy reconstruction algorithms used in the CMS hadron calorimeter during LHC Run 1 and Run 2, and compares their performance. A machine learning based algorithm is also presented, which shows improved performance.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-03-07
DOI
https://doi.org/10.1051/epjconf/202532000045/pdf
Primary Topic
Particle physics theoretical and experimental studies
Type
article
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article

Review of energy reconstruction algorithms in the CMS Hadron Calorimeter

Hui Wang
Springer Link (Chiba Institute of Technology)
Particle physics theoretical and experimental studies
article

Review of energy reconstruction algorithms in the CMS Hadron Calorimeter

Hui Wang
article en

Abstract

Energy reconstruction is a crucial step for all calorimeters, which takes the digitized signal as input, and outputs the energy of the sample of interest. This paper introduces different energy reconstruction algorithms used in the CMS hadron calorimeter during LHC Run 1 and Run 2, and compares their performance. A machine learning based algorithm is also presented, which shows improved performance.

Springer Link (Chiba Institute of Technology)
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Particle physics theoretical and experimental studies
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Review of energy reconstruction algorithms in the CMS Hadron Calorimeter — Hui Wang · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS