6 citations · 10 across the 5 of their papers we have counts for
5 papers
A novel perspective on crystal electromagnetic calorimeter design for the CEPC
Weizheng Song, Yang Zhang, Shengsen Sun +9
Crystal electromagnetic calorimeters (ECALs) are essential for high-precision measurements of electrons and photons in particle physics experiments. However, the conventional desig…
dN/dx Reconstruction with Deep Learning for High-Granularity TPCs
Guang Zhao, Yue Chang, Jinxian Zhang +8
Particle identification (PID) is essential for future particle physics experiments such as the Circular Electron-Positron Collider and the Future Circular Collider. A high-granular…
Photon reconstruction using the Hough transform in imaging calorimeters
Yang Zhang, Shengsen Sun, Weizheng Song +4
Photon reconstruction in calorimeters represents a crucial challenge in particle physics experiments, especially in high-density environments where shower overlapping probabilities…
Cluster Counting Algorithm for the CEPC Drift Chamber using LSTM and DGCNN
Zhefei Tian, Guang Zhao, Linghui Wu +7
The particle identification (PID) of hadrons plays a crucial role in particle physics experiments, especially in flavor physics and jet tagging. The cluster-counting method, which…
Peak finding algorithm for cluster counting with domain adaptation
Guang Zhao, Linghui Wu, Francesco Grancagnolo +3
Cluster counting in drift chamber is the most promising breakthrough in particle identification (PID) technique in particle physics experiment. Reconstruction algorithm is one of t…