Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network
Author(s)Apyan, Aram; Bauer, Gerry P.; Bendavid, Joshua L.; Busza, Wit; Butz, Erik M.; Cali, Ivan Amos; Chan, M.; Dutta, Valentina; Gomez-Ceballos, Guillelmo; Goncharov, Maxim; Kim, Y.; Klute, Markus; Krajczar, Krisztian F.; Levin, Andrew Michael; Luckey, P. David; Ma, T.; Nahn, Steven; Paus, Christoph M. E.; Ralph, Duncan Kelley; Roland, Christof E.; Roland, Gunther M.; Rudolph, Matthew Scott; Stephans, George S. F.; Stockli, F.; Sumorok, Konstanty C.; Sung, K.; Velicanu, Dragos Alexandru; Wenger, Edward Allen; Wolf, R.; Wyslouch, Boleslaw; Yang, M.; Yilmaz, Y.; Yoon, A. S.; Zanetti, Marco; Zhukova, Victoria; ... Show more Show less
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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[superscript -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 (E̸[subscript T]>40 GeV) and total hadronic transverse energy (H[subscript T]>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.
DepartmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering; Massachusetts Institute of Technology. Department of Physics; Massachusetts Institute of Technology. School of Science
Physical Review D
American Physical Society
Chatrchyan, S., V. Khachatryan, A. M. Sirunyan, A. Tumasyan, W. Adam, E. Aguilo, T. Bergauer, et al. “Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network.” Physical Review D 87, no. 7 (April 2013).
Final published version