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 inverse femtobarns 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 (missing ET > 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 mininal supersymmetric standard model and on a set of simplified models.
Highlights
One of the most natural extensions of the standard model (SM) of particle physics is supersymmetry (SUSY) [1,2,3,4,5,6,7,8]
A search for supersymmetry in events with two opposite-sign leptons in the final state and with the use of an artificial neural network has been presented, using the 2011 data set collected with the Compact Muon Solenoid (CMS) experiment
This search is complementary to the ones already published by the CMS Collaboration and yields comparable exclusion limits for high-E6 T, high-HT SUSY models
Summary
One of the most natural extensions of the standard model (SM) of particle physics is supersymmetry (SUSY) [1,2,3,4,5,6,7,8]. With the successful 2011 LHC run, an integrated luminosity of 4:98 fbÀ1 in collisions at 7 TeV center-of-mass energy has been collected with the Compact Muon Solenoid (CMS) experiment This data set is used to search for the presence of SUSY particles in events with two opposite-sign leptons (electrons and muons) in the final state, utilizing an artificial neural network (ANN). For SUSY models that yield events with large E6 T, the ANN’s performance is comparable to the data analyses using large E6 T and HT For such models the additional power of a multivariate technique is not required to discriminate between new physics and the SM backgrounds. The SMS is fully described by the following parameters: the masses of the gluino (mg~), and the LSP (mLSP), along with the neutralino mass in the gluino decay which is set to mX~ 02 1⁄4 ðmg~ þ mLSPÞ=2
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