63 citations · 298 across the 25 of their papers we have counts for
5 papers · 1 filter
Learning to Identify Semi-Visible Jets
Taylor Faucett, Shih-Chieh Hsu, Daniel Whiteson
We train a network to identify jets with fractional dark decay (semi-visible jets) using the pattern of their low-level jet constituents, and explore the nature of the information…
Exploring the Universality of Hadronic Jet Classification
Kingman Cheung, Yi-Lun Chung, Shih-Chieh Hsu +1
The modeling of jet substructure significantly differs between Parton Shower Monte Carlo (PSMC) programs. Despite this, we observe that machine learning classifiers trained on diff…
Probing highly collimated photon-jets with deep learning
Xiaocong Ai, Shih-Chieh Hsu, Ke Li +1
Many extensions of the standard model (SM) predict the existence of axion-like particles and/or dark Higgs in the sub-GeV scale. Two new sub-GeV particles, a scalar and a pseudosca…
Identifying the Quantum Properties of Hadronic Resonances using Machine Learning
Jakub Filipek, Shih-Chieh Hsu, John Kruper +2
With the great promise of deep learning, discoveries of new particles at the Large Hadron Collider (LHC) may be imminent. Following the discovery of a new Beyond the Standard model…
Disentangling Boosted Higgs Boson Production Modes with Machine Learning
Yi-Lun Chung, Shih-Chieh Hsu, Benjamin Nachman
Higgs Bosons produced via gluon-gluon fusion (ggF) with large transverse momentum () are sensitive probes of physics beyond the Standard Model. However, high Higgs Boson…