10 papers
Learning from all particles in high-energy collisions
Yongfeng Zhu, Yuexin Wang, Hao Liang +5
Particle colliders stand as an irreplaceable pillar of inquiry for exploring the fundamental building blocks of matter and forces of the Universe, yet fully decoding complex collis…
Evaluation of PID Performance at CEPC and Optimization with Combined dN/dx and Time-of-Flight Data
Dian Yu, Houqian Ding, Yongfeng Zhu +3
Charged-hadron identification (PID) is a critical requirement for the physics program of the Circular Electron-Positron Collider (CEPC). The baseline detector relies on ionization…
Hadronic decay branching ratio measurements of the Higgs boson at future colliders using the Holistic Approach
Jianfeng Jiang, Yongfeng Zhu, Chao Yang +1
Accurately measuring the properties of the Higgs boson is one of the primary physics objectives of the high-energy frontier. By incorporating the inclusive information of all recon…
Prospect for measurement of CP-violating parameters of at the Tera Z factory
Hengyu Wang, Hanhua Cui, Yongfeng Zhu +8
transition is a critical flavor-changing neutral current (FCNC) process that could be used to probe CP violation (CPV) and new physics (NP). We quantify the anticipated…
Deep-learning jet flavor tagging for precision hadronic Higgs measurements at future Higgs factories
Xinzhu Wang, Yifan Zhu, Chunxiang Zhu +5
Precise measurements of Higgs decays into quarks and gluons are essential for probing the Yukawa couplings of the Higgs boson and testing the flavor structure of the Standard Model…
BigBang-Proton Technical Report: Next-Word-Prediction is Scientific Multitask Learner
Hengkui Wu, Liujiang Liu, Jihua He +23
We introduce BigBang-Proton, a unified sequence-based architecture for auto-regressive language modeling pretrained on cross-scale, cross-structure, cross-discipline real-world sci…