Search for supersymmetry in events with opposite-sign dileptons and missing energy using an ANN

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 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 (E/T > 40GeV) and total hadronic transverse energy (HT > 120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observation, yielding limits in the context of the constrained mininal supersymmetric standard model and on a set of simplified models.

Link to 5/fb documentation in CDS


Figure Abbreviated Caption

Extrapolation factor Rext, as obtained from simulated events.
Left: The ANN output for the SM background (red bands) and SMS low E/T-low HT events (blue line). Right: Efficiency (red) and purity (blue) vs. the minimum ANN output value for SMS low E/T-low HT events in the signal region.
Data (black points with error bars) vs. simulated events (red bands) comparisons of the ANN output distributions in the various control regions. Top: The ANN output in the control region used to perform the extrapolation with systematic uncertainties included (left), and the ratio between data and simulated events (right) with both statistical (black error bars) and systematic (red bands) uncertainties shown. Bottom: The main control region is subdivided into the following two to perform cross-checks: tt enriched control region A (left), Z + jet enriched control region B (right) with systematic uncertainties included.
The distributions in seven input ANN variables for simulated SM background events (red shaded band showing combined statistical and systematic uncertainties) and SMS low-E/T low-HT events (blue histogram), normalized to the same number of events. The data are also shown for comparison (black points with error bars).
The ANN output for the data (black points) and the SM prediction based on control regions in data (gray band) in the signal region. The uncertainty on the SM prediction includes both statistical and systematic components
Distribution in E/T (top left) and HT (top right) for signal-like events (ANN output> 0.95) for data (blackpoints with error bars) and simulation (red shaded band). The E/T vs. HT distributions for signal-like events (ANN > 0.95) in data (bottom left) and simulation (bottom right); the regions to the right and up of the black line are the ones also explored by other CMS opposite-sign dilepton searches.
The 95% CL exclusion limits on the simplified model scenarios with the ANN analysis. The acceptance (fraction of events surviving event selection and candidate event selection) efficiency (fraction of events surviving ANN selection) (top) and 95% CL upper cross section limit (bottom) are shown for different gluino and neutralino masses. The region just below the diagonal is not considered due to inadequate initial state radiation modelling
Expected (blue) and observed (red) 95% CL exclusion limit for the ANN analysis (for ANN output > 0.95) in the CMSSM plane. The one s experimental error around the expected limit, and the one s theoretical error around the observed limit are also shown

Expected number of signal and background (bkg.) events in the signal region after the event and candidate event selection criteria are applied. The next-leading-order (NLO) cross section is used for the CMSSM benchmark point LM6 yield determination. The dataset resulting from the candidate event selection is used as input to the ANN. The uncertainties quoted are statistical only.
Seven event, lepton and jet related variables used for the ANN construction.The transverse mass MT is defined as Sqrt ( (Sum ET)^2 + (Sum pT)^2 where Sum ET and Sum pT represent the scalar and vector sums over the transverse momenta of all reconstructed jets and leptons.
Systematic uncertainties considered in the predicted background, along with their magnitude, and the impact they have on the final ANN output prediction when the signal selection requirement at 0.95 is applied.
Expected number of events for signal and SM background and for the ANN output greater than > 0.95. The NLO cross section is used for the CMSSM benchmark point LM6.
Systematic uncertainties on signal acceptance and efficiency.

-- NikiSaoulidou - 13-Aug-2012

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