Muon Identification using Neural Networks With the Muon Telescope Detector at STAR

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dc.citation.firstpage192en_US
dc.citation.journalTitleNuclear Physics Aen_US
dc.citation.lastpage194en_US
dc.citation.volumeNumber982en_US
dc.contributor.authorSTAR Collaborationen_US
dc.date.accessioned2021-10-19T15:35:19Zen_US
dc.date.available2021-10-19T15:35:19Zen_US
dc.date.issued2019en_US
dc.description.abstractThe installation of the Muon Telescope Detector (MTD) at STAR allows a measurement of the dimuon (μ+μ−) production in heavy-ion collisions over a large invariant mass range for the first time. Data has been collected with the MTD from Au+Au collisions at sNN=200GeV and from p+p collisions at s=200GeV. These two datasets allow for new opportunities to measure the dimuon invariant mass spectra at STAR. Before any dimuon measurements can be made, muons must be identified. This contribution presents muon identification employing deep neural networks (DNN) and compares it with other multi-variate techniques. Applications of the DNN technique for data-driven purity measurements are discussed.en_US
dc.identifier.citationSTAR Collaboration. "Muon Identification using Neural Networks With the Muon Telescope Detector at STAR." <i>Nuclear Physics A,</i> 982, (2019) Elsevier: 192-194. https://doi.org/10.1016/j.nuclphysa.2018.10.036.en_US
dc.identifier.digital1-s2-0-S0375947418303178-mainen_US
dc.identifier.doihttps://doi.org/10.1016/j.nuclphysa.2018.10.036en_US
dc.identifier.urihttps://hdl.handle.net/1911/111557en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.titleMuon Identification using Neural Networks With the Muon Telescope Detector at STARen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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