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

Philip S Baringer; Alice Bean; Gabriele Benelli; R. P. Kenny; Michael J Murray; Danny Noonan; Stephen J Sanders; Robert W Stringer; Gemma Tinti; Jeffrey Scott Wood; S Chatrchyan; V Khachatryan; A. M Sirunyan; A Tumasyan; W Adam; E Aguilo; T Bergauer; M Dragicevic; Yasar Onel; CMS Collaboration

doi:10.1103/PhysRevD.87.072001

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

Journal article

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

Philip S Baringer, Alice Bean, Gabriele Benelli, R. P. Kenny, Michael J Murray, Danny Noonan, Stephen J Sanders, Robert W Stringer, Gemma Tinti, Jeffrey Scott Wood, …

Physical review. D. Particles and fields, Vol.87(7), 072001

04/02/2013

DOI: 10.1103/PhysRevD.87.072001

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Abstract

This is the publisher's version, also available electronically from http://journals.aps.org/prd/abstract/10.1103/PhysRevD.87.072001. 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 (E̸(T)>40 GeV) and total hadronic transverse energy (H(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.

Details

Title: Subtitle: Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network
Creators: Philip S Baringer
Alice Bean
Gabriele Benelli
R. P. Kenny
Michael J Murray
Danny Noonan
Stephen J Sanders
Robert W Stringer
Gemma Tinti
Jeffrey Scott Wood
S Chatrchyan
V Khachatryan
A. M Sirunyan
A Tumasyan
W Adam - Austrian Academy of Sciences
E Aguilo - Austrian Academy of Sciences
T Bergauer - Austrian Academy of Sciences
M Dragicevic - Austrian Academy of Sciences
Yasar Onel (Contributor) - Physics and Astronomy
CMS Collaboration
Resource Type: Journal article
Publication Details: Physical review. D. Particles and fields, Vol.87(7), 072001
DOI: 10.1103/PhysRevD.87.072001
ISSN: 0556-2821
eISSN: 1089-4918
Publisher: American Physical Society
Grant note: DOI: 10.13039/100000015, name: U.S. Department of Energy; DOI: 10.13039/100000001, name: National Science Foundation
Language: English
Date published: 04/02/2013
Academic Unit: Physics and Astronomy
Record Identifier: 9984428824202771

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