Particle identification with the cluster counting technique for the IDEA drift chamber
Abstract
IDEA (Innovative Detector for an Electron-positron Accelerator) is a general-purpose detector concept, designed to study electron-positron collisions in a wide energy range from a very large circular leptonic collider. Its drift chamber is designed to provide an efficient tracking, a high precision momentum measurement and an excellent particle identification by exploiting the application of the cluster counting technique. To investigate the potential of the cluster counting techniques on physics events, a simulation of the ionization clusters generation is needed, therefore we developed an algorithm which can use the energy deposit information provided by Geant4 toolkit to reproduce, in a fast and convenient way, the clusters number distribution and the cluster size distribution. The results obtained confirm that the cluster counting technique allows to reach a resolution 2 times better than the traditional dE/dx method. A beam test has been performed during November 2021 at CERN on the H8 to validate the simulations results, to define the limiting effects for a fully efficient cluster counting and to count the number of electron clusters released by an ionizing track at a fixed as a function of the track angle. The simulation and the beam test results will be described briefly in this issue.
Cite
@article{arxiv.2211.04220,
title = {Particle identification with the cluster counting technique for the IDEA drift chamber},
author = {Claudio Caputo and Gianluigi Chiarello and Alessandro Corvaglia and Federica Cuna and Brunella D'Anzi and Nicola De Filippis and Walaa Elmetenawee and Edoardo Gorini and Francesco Grancagnolo and Matteo Greco and Sergei Gribanov and Kurtis Johnson and Alessandro Miccoli and Marco Panareo and Alexander Popov and Margherita Primavera and Angela Taliercio and Giovanni Francesco Tassielli and Andrea Ventura and Shuiting Xin},
journal= {arXiv preprint arXiv:2211.04220},
year = {2022}
}
Comments
2 pages, 4 figures, Proceedings of: PM2021