180 citations · 659 across the 17 of their papers we have counts for
5 papers · 1 filter
Importance and construction of features in identifying new physics signals with deep learning
Chang-Wei Loh, Rui Zhang, Yong-Heng Xu +7
Advances in machine learning have led to an emergence of new paradigms in the analysis of large data which could assist traditional approaches in the search for new physics amongst…
Kaon Distribution Amplitude from Lattice QCD and the Flavor SU(3) Symmetry
Jiunn-Wei Chen, Luchang Jin, Huey-Wen Lin +6
We present the first lattice-QCD calculation of the kaon distribution amplitude using the large-momentum effective theory (LaMET) approach. The momentum-smearing technique has been…
Deep Learning the Effects of Photon Sensors on the Event Reconstruction Performance in an Antineutrino Detector
Chang-Wei Loh, Zhi-Qiang Qian, You-Hang Liu +5
We provide a fast approach incorporating the usage of deep learning for evaluating the effects of photon sensors in an antineutrino detector on the event reconstruction performance…
Slow Liquid Scintillator Candidates for MeV-scale Neutrino Experiments
Ziyi Guo, Minfang Yeh, Rui Zhang +4
Slow liquid scintillator Cherenkov detectors have been proposed as part of several future neutrino experiments because they can provide both directionality and energy measurements.…
Light Attenuation Length of High Quality Linear Alkyl Benzene as Liquid Scintillator Solvent for the JUNO Experiment
Hai-Bo Yang, De-Wen Cao, Chang-Wei Loh +8
The Jiangmen Underground Neutrino Observatory (JUNO) is a multipurpose neutrino experiment with a 20 kt liquid scintillator detector designed to determine the neutrino mass hierarc…