2023/04/21 by B. D’Anzi, G. Chiarello, D'Anzi, Brunella +29
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #FOS: Physical sciences #Fractal and DNA sequence analysis #High Energy Physics - Experiment (hep-ex) #Instrumentation and Detectors (physics.ins-det) #Particle Detector Development and Performance #Radiation Detection and Scintillator Technologies
paper · pdf · doi:10.48550/arxiv.2304.10806
openalex publication_date 2023/04/21 · openalex created_date 2023/04/25 · openalex updated_date 2026/07/28
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.