Exotics Working group
CIEMAT group

The CDF Collaboration


Miguel Vidal (vidal@fnal.gov)

Oscar Gonzalez (oglez@fnal.gov)

P.0. Box 500, M.S. 318 (MADRID)
Batavia, Illinois 60510

Search for Gluino-Mediated Sbottom Production

Public Web Page

Using data collected with the CDF detector in the Run II of the Tevatron, we analyzed events containing two or more jets and missing transverse energy searching for the presence of physics beyond the Standard Model. At least one of the jets was required to be tagged as originating from a heavy-flavour quark in order to enhance the sensitivity to final states containing b-quarks. The analysis was optimized to search for the supersymmetric partner of the bottom quark produced from gluino decays. Preliminary results were obtained with 1.8 fb-1 of data. We constrain the cross section production to be less than 0.1 pb at 95% C.L.

- Basic Event Selection -
- Control Regions -
- Signal Regions -
- Systematics Uncertainties -
- Limits -
Download plots in EPS format by clicking on the plot

Public Note

  • Publication Phys.Rev.Lett.102 121801,2009
  • Plots from publication

    In the present analysis we search for sbottom quarks produced though gluino decays. We look for the gluino pair production, where the gluino decays into bottom sbottom with the subsequent sbottom decay to a b-quark and the lightest neutralino. The neutralino is taken to be the Lightest Supersymetric particle (LSP) and R-parity conservation is assumed. Therefore, the gluino signature is 4 b-jets and large missing transverse energy (MET).

    For the this analysis we use 1.8 fb-1 of data from the inclusive MET trigger. We define two control regions, one pre-optimization region and two signal regions. In the two control regions predicted distributions are compare with those measured in data using single tagged events (using the SecVtx tagging algorithm). We then perform a counting experiment comparing the number of observed events with the number of expected backgrounds events.

    Feynman Diagrams


    Basic Event Selection :

    All the event processed in the analysis are required to have:

    • At least 2 Jets
    • MET > 70 GeV + cleanup cuts
    • ET > 25 GeV and |η| < 2.4
    • Leading Jet ET > 35 GeV
    • 1 Central Jet |η| < 0.9
    • Jet EM Fraction < 0.9


    Control Regions :

    To have the background contribution under control, i.e. understood, before "opening the box" we have followed a methodical procedure in three control regions. A QCD control region, a Lepton control region and a Pre-optimization control region. Furthermore, all events in the analysis have to fulfill some Pre-selection cuts The QCD control region was defined to estimate the multi-jet background following the Multijet Tag-Rate Estimator (MUTARE) Method and apply the prediction to the other control regions and finally to the signal region. The Lepton region permitted us to define a non-QCD environment with leptons in order to test our predictions in a completely different region to the signal one. Finally, the Pre-optimization region gave us the chance to test the background predictions in a signal-like environment.

  • QCD Region Plots

  • Lepton Region Plots

  • Pre-Optimization Region Plots


    Signal Regions :

    In order to reduce the background contribution we chose two SUSY signal points to perform a MC optimization cut study for each point. The two selected points are:

    • Large Δm Optimization: M(gluino) = 320 GeV/c2, M(sbottom) = 250 GeV/c2, M(neutralino) = 60 GeV/c2
    • Small Δm Optimization: M(gluino) = 300 GeV/c2, M(sbottom) = 280 GeV/c2, M(neutralino) = 60 GeV/c2
    The optimization process takes as a benchmark the Pre-optimization selection. Over this selection, signal over square root of background (S/sqrt(B)) distributions were studied as a function of the most discriminant variables in order to maximize the separation between signal and background. By applying the cuts suggested by the S/sqrt(B) distributions and repeating the optimization process we perform a step-by-step optimization procedure.

    The lists of the cuts for the two optimization regions are:

    Large Δm Optimization:
  • Lepton veto
  • At leats 3 jets
  • MET > 145 GeV
  • ΔΦ(MET,3j) >= 0.4
  • ET,2j >= 60 GeV
  • ET,3j >= 45 GeV
  • Small Δm Optimization:
  • Lepton veto
  • MET > 175 GeV
  • ΔΦ(MET,3j) >= 0.4
  • ET,2j >= 60 GeV
  • ET,3j <= 60 GeV
  • For the two different optimizations the agreement between SM prediction and the data is good.

    Large Delta-m Optimization Plots

    Small Delta-m Optimization Plots


    Systematics Uncertainties :

    We address systematic uncertainties from different sources:

    • Jet Energy Scale (JES): A systematic error in the calorimeter energy scale affect the total transverse energy on the jets. 1 sigma variations in the jet energy corrections are computed in order to estimate the uncertainty on the jet energy scale. The corresponding shift in the MET was also included.
    • b-tagging Scale Factor (SF): The Monte Carlo simulation has an efficiency for tagging 5% larger than in data. In order to take in account the uncertainty due to this difference in efficiency 1 sigma variations in the scale factor were applied.
    • Mistag Rate: The systematic error assigned to the tag rate matrix is 4.8% in estimating the negative tags with the tight b-tagger. This uncertainty is already taken into account the Mistag rate error.
    • Luminosity: The systematic uncertainty in the luminosity is taken to be 6%.
    • ISR/FSR: The uncertainty associated with the initial and final state radiation was evaluated by generating sample with more/less ISR/FSR according to the Joint Physics recommendation.
    • PDF: The PDF uncertainty has been determined that a 2% uncertainty on the acceptance due to the choice of the PDF is sufficient.
    • QCD Multijet Background: Since the method we are using have not been thoroughly checked and it is not clear how the prediction may behave in the optimized regions (which are small corners of the phase space), we assign a conservative 50% uncertainty in the prediction.
      We assume any other uncertainty related to the estimation of the QCD multijet background will be covered by this, except those due to the substraction of the non-QCD contribution to the taggable sample in the optimized regions.
    • Top-Pair Production cross section: We quote the uncertainty in the CDF measured value (11%) of the top-pair production cross section.
    • Single Top Production cross section: We quote the theoretical uncertainty in the single-top cross section (13%)
    • EWK Boson Production cross section: Although the cross section for Z and W production are known to a high precision, we are using the inclusive processes in Pythia to perform estimations of $Z/W$+multijet processes. Because of this, we estimate a 40% uncertainty in the predictions. In addition, this uncertainty is considered 100% correlated for all the Boson- and Diboson-production processes.


    Limits :

    Two different signal regions were optimized for the present analysis. In this two regions the number of observed events events are in good agreement with the expected events from the SM processes. We extracted a limit with 95% C.L.