Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/10680
Title: Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network
Authors: CMS Collaboration
Issue Date: 2013
Publisher: American Physical Society
Abstract: In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4: 98 fb(-1) of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (E-T > 40 GeV) and total hadronic transverse energy (HT > 120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified models. DOI: 10.1103/PhysRevD.87.072001
URI: https://doi.org/10.1103/PhysRevD.87.072001
https://hdl.handle.net/10680
ISSN: 2470-0010
2470-0029
Appears in Collections:WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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