Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

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 backgro...

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Bibliographic Details
Main Authors: Apyan, Aram, 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, Nahn, Steven, Paus, Christoph M. E., Ralph, Duncan Kelley, Rudolph, Matthew Scott, Stephans, George S. F., Velicanu, Dragos Alexandru, Wenger, Edward Allen, Wyslouch, Boleslaw, Yoon, A. S., Zanetti, Marco, Bauer, Gerry P, Ma, Teng, Roland, Christof E, Stoeckli, Fabian, Sung, Kevin Kai Hong, Yilmaz, Yetkin, Luckey Jr, P David, Roland, Gunther M, Sumorok, Konstanty C, Wolf, Roger, Yang, Mingming, Wyslouch, Victoria
Other Authors: Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Format: Article
Language:en_US
Published: American Physical Society 2013
Online Access:http://hdl.handle.net/1721.1/82520
https://orcid.org/0000-0002-3831-9071
https://orcid.org/0000-0003-3106-4894
https://orcid.org/0000-0001-6332-5839
https://orcid.org/0000-0001-8983-2169
https://orcid.org/0000-0002-1260-777X
https://orcid.org/0000-0002-9418-6656
https://orcid.org/0000-0002-6047-4211
https://orcid.org/0000-0003-3681-0649
https://orcid.org/0000-0002-0869-5631
https://orcid.org/0000-0002-1136-6900
Description
Summary: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.

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