9 papers
Learning transferable event representations for charmed baryon physics at BESIII
Kaixuan Huang, Yangu Li, Junpeng Zhao +6
Deep learning has become an essential tool in high-energy physics, where the ability to learn transferable event representations can significantly improve model generalization acro…
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…
Conceptual Design of a Novel Highly Granular Crystal Electromagnetic Calorimeter for Future Higgs Factories
Baohua Qi, Fangyi Guo, Shu Li +9
Next-generation high-energy electron-positron colliders, operating as Higgs factories, require an unprecedented jet energy resolution for precision measurements of Higgs and Z/W bo…
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…
The CEPC Clock Issue and Finetuning of the Circumference
Dou Wang, Jie Gao, Jianchun Wang +13
The CEPC clock issue is related with the RF frequency coordination between the various accelerator systems and may affect the operation modes of both the accelerator and the detect…