Description and stability of a RPC-based calorimeter in electromagnetic and hadronic shower environments

TL;DR

This paper evaluates the stability and response of a RPC-based calorimeter prototype in electromagnetic and hadronic environments, using detailed simulations and test beam data to ensure reliable performance predictions for future collider experiments.

Contribution

It develops and tunes a GEANT4-based digitization algorithm for the calorimeter, enabling accurate simulation of its response and stability under various operational conditions.

Findings

Detector efficiency is minimally affected by temperature and inhomogeneities.

Simulation accurately predicts detector response across different shower types.

Stability analysis supports future use of the technology in large-scale experiments.

Abstract

The CALICE Semi-Digital Hadron Calorimeter technological prototype completed in 2011 is a sampling calorimeter using Glass Resistive Plate Chamber (GRPC) detectors as the active medium. This technology is one of the two options proposed for the hadron calorimeter of the International Large Detector for the International Linear Collider. The prototype was exposed in 2015 to beams of muons, electrons, and pions of different energies at the CERN Super Proton Synchrotron. The use of this technology for future experiments requires a reliable simulation of its response that can predict its performance. GEANT4 combined with a digitization algorithm was used to simulate the prototype. It describes the full path of the signal: showering, gas avalanches, charge induction, and hit triggering. The simulation was tuned using muon tracks and electromagnetic showers for accounting for detector inhomogeneity and tested on hadronic showers collected in the test beam. This publication describes developments of the digitization algorithm. It is used to predict the stability of the detector performance against various changes in the data-taking conditions, including temperature, pressure, magnetic field, GRPC width variations, and gas mixture variations. These predictions are confronted with test beam data and provide an attempt to explain the detector properties. The data-taking conditions such as temperature and potential detector inhomogeneities affect energy density measurements but have a small impact on detector efficiency.