ICHEP 2024

Particle Identification Algorithms Based on Machine Learning for STCF

18 Jul 2024, 19:00

2h

Foyer Floor 2

Poster 11. Accelerator: Physics, Performance, and R&D for Future Facilities Poster Session 1

Speaker

Yuncong Zhai (Shandong University)

Description

The Super Tau-Charm Facility (STCF) is a new generation $e^{+}{e}^{-}$ collider designed for various physics topics in the $\tau$-charm energy region. The particle identification (PID), as one of the most fundemental tools in physics analysis, is crutial for achieving excellent physics performance. In this work, we present a powerful PID software based on ML techniques, including a global PID algorithm for charged particles combining information from all sub-detectors, a deep CNN taking Cherenkov detector inputs to discriminate charged hadrons, as well as a deep CNN discriminating neutral particles based on calorimeter responses. The preliminary results show the PID models has achieved excellent PID performance, greatly boosting the physics potential of STCF.

Presentation materials

ICHEP_Poster.pdf

ICHEP_Poster.pptx