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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…
Observation of and at =4.600 GeV
M. Ablikim, M. N. Achasov, S. Ahmed +427
Using a data sample collected with the BESIII detector operating at the BEPCII storage ring at a center-of-mass energy of GeV, we search for the production of $e^{…
Precision Study of Decay Dynamics
BESIII Collaboration, M. Ablikim, M. N. Achasov +431
Using a low background data sample of , events, which are 2 orders of magnitude larger than those from the pr…
Branching fraction measurement of and search for
BESIII Collaboration, M. Ablikim, M. N. Achasov +441
Using a sample of events collected with the BESIII detector at the BEPCII collider, we study the decays of and . The br…
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…
Cosmogenic neutron production at Daya Bay
Daya Bay Collaboration, F. P. An, A. B. Balantekin +197
Neutrons produced by cosmic ray muons are an important background for underground experiments studying neutrino oscillations, neutrinoless double beta decay, dark matter, and other…