HIGHLIGHTS
- who: L. Ng et al. from the DepartmentState University, Tallahassee, Florida, USA have published the paper: Deep learning exotic hadrons, in the Journal: (JOURNAL) of 17/05/2022
- what: The authors develop and benchmark a systematic approach to apply DNNs as a model-independent tool to analyze and interpret experimental data. The authors focus on the J=u03c8p invariant mass distribution reported by the LHCb. The authors determine the probability of each of the classes of interest, given the experimental uncertainties and resolution.
SUMMARY
Many hadron candidates that deviate from the . . .
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