Cluster counting algorithms for particle identification at future colliders
High Energy Physics - Experiment
2023-04-24 v1 Instrumentation and Detectors
Abstract
Recognition of electron peaks and primary ionization clusters in real data-driven waveform signals is the main goal of research for the usage of the cluster counting technique in particle identification at future colliders. The state-of-the-art open-source algorithms fail in finding the cluster distribution Poisson behavior even in low-noise conditions. In this work, we present cutting-edge algorithms and their performance to search for electron peaks and identify ionization clusters in experimental data using the latest available computing tools and physics knowledge.
Cite
@article{arxiv.2304.10806,
title = {Cluster counting algorithms for particle identification at future colliders},
author = {Brunella D'Anzi and Gianluigi Chiarello and Alessandro Corvaglia and Nicola De Filippis and Walaa Elmetenawee and Francesco De Santis and Edoardo Gorini and Francesco Grancagnolo and Marcello Maggi and Alessandro Miccoli and Marco Panareo and Margherita Primavera and Andrea Ventura and Shuiting Xin and Fangyi Guo and Shuaiyi Liu},
journal= {arXiv preprint arXiv:2304.10806},
year = {2023}
}
Comments
6 pages, 12 figures, Proceedings of: ACAT2022