Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network
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 4.98fb-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 (E̸T>40GeV) and total hadronic transverse energy (HT>120GeV), 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.
- Publication:
-
Physical Review D
- Pub Date:
- April 2013
- DOI:
- 10.1103/PhysRevD.87.072001
- arXiv:
- arXiv:1301.0916
- Bibcode:
- 2013PhRvD..87g2001C
- Keywords:
-
- 12.60.Jv;
- 13.85.Rm;
- 14.80.Ly;
- Supersymmetric models;
- Limits on production of particles;
- Supersymmetric partners of known particles;
- High Energy Physics - Experiment
- E-Print:
- Replaced with published version. Added journal reference and DOI