121 citations · 232 across the 18 of their papers we have counts for
7 papers · 1 filter
Application of Quantum Machine Learning in a Higgs Physics Study at the CEPC
Abdualazem Fadol, Qiyu Sha, Yaquan Fang +5
Machine learning has blossomed in recent decades and has become essential in many fields. It significantly solved some problems in particle physics -- particle reconstruction, even…
Does Lorentz-symmetric design boost network performance in jet physics?
Congqiao Li, Huilin Qu, Sitian Qian +5
In the deep learning era, improving the neural network performance in jet physics is a rewarding task as it directly contributes to more accurate physics measurements at the LHC. R…
The physics case for neutrino-neutrino collisions
Sitian Qian, Tianyi Yang, Sen Deng +6
Addressing the mass origin and properties of neutrinos is of strong interest to particle physics, baryogenesis and cosmology. Popular explanations involve physics beyond the standa…
The physics case for a neutrino lepton collider in light of the CDF W mass measurement
Tianyi Yang, Sitian Qian, Sen Deng +6
We propose a neutrino lepton collider where the neutrino beam is generated from TeV scale muon decays. Such a device would allow for a precise measurement of the W mass based on si…
Particle Transformer for Jet Tagging
Huilin Qu, Congqiao Li, Sitian Qian
Jet tagging is a critical yet challenging classification task in particle physics. While deep learning has transformed jet tagging and significantly improved performance, the lack…
An Efficient Lorentz Equivariant Graph Neural Network for Jet Tagging
Shiqi Gong, Qi Meng, Jue Zhang +6
Deep learning methods have been increasingly adopted to study jets in particle physics. Since symmetry-preserving behavior has been shown to be an important factor for improving th…
Boosted tau lepton as a microscope and macroscope
Sitian Qian, Zhe Guan, Sen Deng +9
Anomalies from the LHCb lepton flavour universality and Fermilab muon anomalous magnetic momentum, show tantalizing hints of possible new physics from the lepton sectors. Due to it…