Abstract

An inclusive search for supersymmetry (SUSY) using the razor variables is performed using a data sample of proton-proton collisions corresponding to an integrated luminosity of 35.9 fb−1, collected with the CMS experiment in 2016 at a center-of-mass energy of sqrt{s}=13 TeV. The search looks for an excess of events with large transverse energy, large jet multiplicity, and large missing transverse momentum. The razor kinematic variables are sensitive to large mass differences between the parent particle and the invisible particles of a decay chain and help to identify the presence of SUSY particles. The search covers final states with zero or one charged lepton and features event categories divided according to the presence of a high transverse momentum hadronically decaying W boson or top quark, the number of jets, the number of b-tagged jets, and the values of the razor kinematic variables, in order to separate signal from background for a broad range of SUSY signatures. The addition of the boosted W boson and top quark categories within the analysis further increases the sensitivity of the search, particularly to signal models with large mass splitting between the produced gluino or squark and the lightest SUSY particle. The analysis is interpreted using simplified models of R-parity conserving SUSY, focusing on gluino pair production and top squark pair production. Limits on the gluino mass extend to 2.0 TeV, while limits on top squark mass reach 1.14 TeV.

Highlights

  • Background modelingThe main background processes in the search regions (SRs) considered are W( ν)+jets, Z(νν)+jets, tt, and quantum chromodynamics (QCD) multijet production

  • To give a characteristic example, for squark pair production with a squark mass of 1000 GeV and a neutralino mass of 100 GeV, we find that the overlap of signal events falling in the most sensitive tail regions of the razor kinematic variables and of other kinematic variables used in alternative searches described in ref. [32] is 50–70%

  • Other background processes are generated at next-to-leading order (NLO) with MadGraph5 amc@nlo 2.2.2 [65] (W+jets, s-channel single top quark, ttW, ttZ processes) or with powheg v2.0 [70,71,72], both interfaced with pythia V8.205

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Summary

The CMS detector and object reconstruction

The CMS detector consists of a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Physics objects are defined using the particle-flow (PF) algorithm [49], which aims to reconstruct and identify each individual particle in an event using an optimized combination of information from the various elements of the CMS detector. Jets are clustered from PF candidates using the anti-kT algorithm [50, 51] with a distance parameter of 0.4. Large-radius jets used for identifying Lorentz-boosted W bosons and top quarks are clustered using the anti-kT algorithm with a distance parameter of 0.8. Jet mass is computed using the soft-drop algorithm [56], and is required to be between 65–105 and 105–210 GeV for W bosons and top quarks, respectively. Photon candidates are reconstructed from energy clusters in the ECAL [63] and identified based on the transverse shower width, the hadronic to electromagnetic energy ratio in the HCAL and ECAL, and isolation. Photons are used in the estimation of Z → νν+jets backgrounds, and are required to have |η| < 2.5 and pT > 185 or 80 GeV for the non-boosted or boosted categories, respectively

Simulation
Analysis strategy and event categorization
Background modeling
The QCD multijet background
Background modeling in boosted event categories
Multijet background estimation in the boosted categories
Validating the background estimation with closure tests in boosted categories
Systematic uncertainties
Results and interpretation
Summary
Full Text
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