{"@context":"http://schema.org","@id":"https://doi.org/10.17182/hepdata.116281.v1","@reverse":{"isBasedOn":[{"@type":"ScholarlyArticle","identifier":{"@type":"PropertyValue","propertyID":"URL","value":"https://inspirehep.net/literature/2016054"}},{"@id":"https://doi.org/10.1088/1748-0221/17/07/P07023","@type":"JournalArticle"}]},"@type":"Dataset","additionalType":"Collection","author":{"@type":"Organization","name":"CMS Collaboration"},"creator":{"@type":"Organization","name":"CMS Collaboration"},"datePublished":"2022","description":"A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons.   The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs.   This algorithm leads to a significantly improved performance compared with the previously used one.   For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets.   Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes.   The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.","hasPart":[{"@id":"https://doi.org/10.17182/hepdata.116281.v1/t1","@type":"Dataset","description":"Decay mode confusion matrix. 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