Nothing Special   »   [go: up one dir, main page]

CERN Accelerating science

If you experience any problem watching the video, click the download button below
Download Embed
Preprint
Report number arXiv:2411.03685
Title Enhancing Energy Resolution and Particle Identification via Chromatic Calorimetry: A Concept Validation Study
Author(s) Arora, Devanshi (CERN ; Shizuoka U., Hamamatsu) ; Salomoni, Matteo (CERN ; Milan Bicocca U.) ; Haddad, Yacine (Northeastern U.) ; Frank, Isabel (CERN ; Munich U.) ; Martinazzoli, Loris (CERN ; Milan Bicocca U.) ; Pizzichemi, Marco (CERN ; Milan Bicocca U.) ; Doser, Michael (CERN) ; Owari, Masaki (Shizuoka U., Hamamatsu) ; Auffray, Etiennette (CERN)
Document contact Contact: arXiv
Imprint 2024-11-06
Number of pages 4
Subject category hep-ex ; Particle Physics - Experiment ; physics.ins-det ; Detectors and Experimental Techniques
Abstract In particle physics, homogeneous calorimeters are used to measure the energy of particles as they interact with the detector material. Although not as precise as trackers or muon detectors, these calorimeters provide valuable insights into the properties of particles by analyzing their energy deposition patterns. Recent advances in material science, notably in nanomaterial scintillators with tunable emission bandwidths, have led to the proposal of the chromatic calorimetry concept. This proposed concept aims to track electromagnetic or hadronic shower progression within a module, enhancing particle identification and energy resolution by layering scintillators with different emission wavelengths. The idea is to use the emission spectra of the inorganic scintillators to reconstruct the shower progression. Our study validates this proposed concept using inorganic scintillators strategically stacked by decreasing emission wavelength. Using electrons and pions with up to 100 GeV, we achieved analytical discrimination and longitudinal shower measurement. This proof of concept underscores chromatic calorimetry's potential for broader applications.
Other source Inspire
Copyright/License preprint: (License: arXiv nonexclusive-distrib 1.0)



 


 Record created 2024-12-10, last modified 2024-12-11


Fulltext:
Download fulltext
PDF