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Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network
Baringer, Philip S. Bean, Alice Benelli, Gabriele Kenny, R. P., III Murray, Michael J. Noonan, Danny Sanders, Stephen J. Stringer, Robert W. Tinti, Gemma Wood, Jeffrey Scott
Baringer, Philip S.
Bean, Alice
Benelli, Gabriele
Kenny, R. P., III
Murray, Michael J.
Noonan, Danny
Sanders, Stephen J.
Stringer, Robert W.
Tinti, Gemma
Wood, Jeffrey Scott
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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 4.98ââfb(â1) 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 (EÌž(T)>40ââGeV) and total hadronic transverse energy (H(T)>120ââGeV), 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.
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This is the publisher's version, also available electronically from http://journals.aps.org/prd/abstract/10.1103/PhysRevD.87.072001.
Date
2013-04-02
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American Physical Society
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Citation
S. Chatrchyan et al. (CMS Collaboration). (2013). "Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network." Physical Review D, 87(7)072001. http://dx.doi.org/10.1103/PhysRevD.87.072001.