Matches in SemOpenAlex for { <https://semopenalex.org/work/W2967331320> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W2967331320 endingPage "194" @default.
- W2967331320 startingPage "192" @default.
- W2967331320 abstract "The installation of the muon telescope detector opened new possibilities for studying dimuon production at STAR. However, backgrounds from hadron punch-through and weak decays of pions and kaons make the identification of primary muons challenging. In this paper we present a study of shallow and deep neural networks trained as classifiers for the purpose of muon identification using information from the muon telescope detector at STAR. The performance of shallow neural networks is presented as a function of the number of neurons in their hidden layer. A hyperparameter optimization for determining the optimal deep neural network classifier architecture is presented. The optimized deep neural network is compared with shallow neural networks, boosted decision trees, likelihood ratios, and traditional cut-based PID techniques. The superiority of the deep neural network based muon identification technique is demonstrated and compared with traditional PID through the measurement of the $phi$ meson and the $psi(2S)$ in p+p collisions at $sqrt{s}$ = 200 GeV. The deep neural network based PID simultaneously provides higher signal efficiency, signal-to-background ratio, and significance of the $phi$ peak compared to traditional PID techniques. Finally, a deep neural network assisted technique for measuring the muon purity in data is presented and discussed." @default.
- W2967331320 created "2019-08-22" @default.
- W2967331320 creator A5022263754 @default.
- W2967331320 date "2019-02-01" @default.
- W2967331320 modified "2023-09-27" @default.
- W2967331320 title "Muon Identification using Neural Networks With the Muon Telescope Detector at STAR" @default.
- W2967331320 cites W2128158076 @default.
- W2967331320 cites W2169165406 @default.
- W2967331320 cites W2181986281 @default.
- W2967331320 cites W2237223844 @default.
- W2967331320 cites W2297591535 @default.
- W2967331320 doi "https://doi.org/10.1016/j.nuclphysa.2018.10.036" @default.
- W2967331320 hasPublicationYear "2019" @default.
- W2967331320 type Work @default.
- W2967331320 sameAs 2967331320 @default.
- W2967331320 citedByCount "0" @default.
- W2967331320 crossrefType "journal-article" @default.
- W2967331320 hasAuthorship W2967331320A5022263754 @default.
- W2967331320 hasBestOaLocation W29673313201 @default.
- W2967331320 hasConcept C108583219 @default.
- W2967331320 hasConcept C109214941 @default.
- W2967331320 hasConcept C11413529 @default.
- W2967331320 hasConcept C120665830 @default.
- W2967331320 hasConcept C121332964 @default.
- W2967331320 hasConcept C154945302 @default.
- W2967331320 hasConcept C185544564 @default.
- W2967331320 hasConcept C205334942 @default.
- W2967331320 hasConcept C206094082 @default.
- W2967331320 hasConcept C2780848835 @default.
- W2967331320 hasConcept C41008148 @default.
- W2967331320 hasConcept C44870925 @default.
- W2967331320 hasConcept C50644808 @default.
- W2967331320 hasConcept C94915269 @default.
- W2967331320 hasConceptScore W2967331320C108583219 @default.
- W2967331320 hasConceptScore W2967331320C109214941 @default.
- W2967331320 hasConceptScore W2967331320C11413529 @default.
- W2967331320 hasConceptScore W2967331320C120665830 @default.
- W2967331320 hasConceptScore W2967331320C121332964 @default.
- W2967331320 hasConceptScore W2967331320C154945302 @default.
- W2967331320 hasConceptScore W2967331320C185544564 @default.
- W2967331320 hasConceptScore W2967331320C205334942 @default.
- W2967331320 hasConceptScore W2967331320C206094082 @default.
- W2967331320 hasConceptScore W2967331320C2780848835 @default.
- W2967331320 hasConceptScore W2967331320C41008148 @default.
- W2967331320 hasConceptScore W2967331320C44870925 @default.
- W2967331320 hasConceptScore W2967331320C50644808 @default.
- W2967331320 hasConceptScore W2967331320C94915269 @default.
- W2967331320 hasLocation W29673313201 @default.
- W2967331320 hasLocation W29673313202 @default.
- W2967331320 hasLocation W29673313203 @default.
- W2967331320 hasLocation W29673313204 @default.
- W2967331320 hasOpenAccess W2967331320 @default.
- W2967331320 hasPrimaryLocation W29673313201 @default.
- W2967331320 hasRelatedWork W1965779136 @default.
- W2967331320 hasRelatedWork W1997576036 @default.
- W2967331320 hasRelatedWork W2011020689 @default.
- W2967331320 hasRelatedWork W2024166584 @default.
- W2967331320 hasRelatedWork W2044799652 @default.
- W2967331320 hasRelatedWork W2088464312 @default.
- W2967331320 hasRelatedWork W2891108282 @default.
- W2967331320 hasRelatedWork W3166586169 @default.
- W2967331320 hasRelatedWork W4235206588 @default.
- W2967331320 hasRelatedWork W4321099759 @default.
- W2967331320 hasVolume "982" @default.
- W2967331320 isParatext "false" @default.
- W2967331320 isRetracted "false" @default.
- W2967331320 magId "2967331320" @default.
- W2967331320 workType "article" @default.