10-15 March 2019
Steinmatte conference center
Europe/Zurich timezone

Deep Learning applied to hit classification for BESIII drift chamber

Not scheduled
20m
Steinmatte conference center

Steinmatte conference center

Hotel Allalin, Saas Fee, Switzerland https://allalin.ch/conference/
Poster Track 2: Data Analysis - Algorithms and Tools Poster Session

Speakers

Ms Yao Zhang (Institute of High Energy Physics, China) Prof. Ye Yuan (Institute of High Energy Physics, China)

Description

Drift chamber is the main tracking detector for high energy physics experiment like BESIII. Due to the high luminosity and high beam intensity, drift chamber is suffer from the background from the beam and electronics which represent a computing challenge to the reconstruction software. Deep learning developments in the last few years have shown tremendous improvements in the analysis of data especially for object classification. Here we present a first study of deep learning architectures applied to BESIII drift chamber real data to make the hit classification of the background and signal.

Primary authors

Ms Yao Zhang (Institute of High Energy Physics, China) Prof. Ye Yuan (Institute of High Energy Physics, China) Ms Qiumei Ma (Institute of High Energy Physics, China)

Presentation materials

Peer reviewing

Paper