20 citations · 67 across the 8 of their papers we have counts for
4 papers · 1 filter
Inverting cosmic ray propagation by Convolutional Neural Networks
Yue-Lin Sming Tsai, Yi-Lun Chung, Qiang Yuan +1
We propose a machine learning method to investigate the propagation of cosmic rays based on the precisely measured spectra of the primary and secondary cosmic ray nuclei of Li, Be,…
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…
A More Natural Composite Higgs Model
Hsin-Chia Cheng, Yi Chung
Composite Higgs models provide an attractive solution to the hierarchy problem. However, many realistic models suffer from tuning problems in the Higgs potential. There are often l…
Sensitivity Reach on the Heavy Neutral Leptons and -Neutrino Mixing at the HL-LHC
Kingman Cheung, Yi-Lun Chung, Hiroyuki Ishida +1
The model of heavy neutral leptons (HNLs) is one of the well-motivated models beyond the standard model (BSM) from both theoretical and phenomenological point of views. It is an in…