Point-cloud ML models classify charm- and bottom-origin electrons at ~80% purity for 40% efficiency, outperforming a BDT baseline, with performance limited by intrinsic decay similarity.
Measurement of electrons from semileptonic heavy-flavor hadron decays in pp collisions at $\sqrt{s} = 2.76$ TeV
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abstract
The $p_{\rm T}$-differential production cross section of electrons from semileptonic decays of heavy-flavor hadrons has been measured at mid-rapidity in proton-proton collisions at $\sqrt{s} = 2.76$ TeV in the transverse momentum range 0.5 < $p_{\rm T}$ < 12 GeV/$c$ with the ALICE detector at the LHC. The analysis was performed using minimum bias events and events triggered by the electromagnetic calorimeter. Predictions from perturbative QCD calculations agree with the data within the theoretical and experimental uncertainties.
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Heavy-Flavor Electron Classification Using Hadronic Environment as Point Cloud
Point-cloud ML models classify charm- and bottom-origin electrons at ~80% purity for 40% efficiency, outperforming a BDT baseline, with performance limited by intrinsic decay similarity.