Search for R-parity-violating supersymmetric particles in multi-jet final states produced in p–p collisions at s=13 TeV using the ATLAS detector at the LHC

Abstract

The ATLAS CollaborationResults of a search for gluino pair production with subsequent R-parity-violating decays to quarks are presented. This search uses 36.1 fb −1 of data collected by the ATLAS detector in proton-proton collisions with a center-of-mass energy of √ s = 13 TeV at the LHC. The analysis is performed using requirements on the number of jets and the number of jets tagged as containing a b-hadron as well as a topological observable formed by the scalar sum of masses of large-radius jets in the event. No significant excess above the expected Standard Model background is observed. Limits are set on the production of gluinos in models with the R-parity-violating decays of either the gluino itself (direct decay) or the neutralino produced in the R-parity-conserving gluino decay (cascade decay). In the gluino cascade decay model, gluino masses below 1850 GeV are excluded for 1000 GeV neutralino mass. For the gluino direct decay model, the 95% confidence level upper limit on the cross section times branching ratio varies between 0.80 fb at mg = 900 GeV and 0.011 fb at mg = 1800 GeV. 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector and the z-axis along the beam direction. The x-axis points toward the centre of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the beam pipe. The pseudorapidity η is defined in terms of the polar angle θ by η ≡ − ln[tan(θ/2)]. Analysis strategyThe analysis uses a kinematic observable, the total jet mass, M Σ J [64-66], as the primary discriminating variable to separate signal and background. The observable M Σ J is defined as the sum of the masses of the four leading large-R jets.The use of M Σ J in this analysis provides an opportunity to employ the fully data-driven jet mass template method to estimate the background contribution in signal regions. The jet mass template method is discussed in Ref. [66], and its first experimental implementation is described in Ref. [21]. In this method, single-jet mass templates are extracted from signal-depleted control regions. These jet mass templates are created in bins that are defined by a number of observables, which include jet p T and |η|, and the b-matching status. They provide a probability density function that describes the relative probability for a jet with a given p T and η to have a certain mass. This method assumes that jet mass templates only depend on these observables and are the same in the control regions and signal regions. A sample where the background M Σ J distribution needs to be estimated, such as a validation region or a signal region, is referred to as the kinematic sample. The only information used is the jet p T and η, as well as its b-matching status, which are inputs to the templates. For each jet in the kinematic sample, its corresponding jet mass template is used to generate a random jet mass. An M Σ J distribution can be constructed from ...

Exotic decays of top partners: Mind the search gap

“…this, we show the M Σ J distribution of an RPV gluino pair with mg = 1800 GeV and mχ0 1 = 1050 GeV (a target benchmark of Ref. [48]) in comparison to a TT pair signal with m T = 1000 GeV (a typical mass considered in this article) in Fig. 5 A detailed cut flow table is not provided in Ref.…”

“…. ATLAS 13 TeV RPV gluino pair search Ref [48]. provides a detailed cut flow.Table IIshows the event numbers after each cut as reported in Ref [48].…”

“…ATLAS 13 TeV RPV gluino pair search Ref [48]. provides a detailed cut flow.Table IIshows the event numbers after each cut as reported in Ref [48]. (in brackets) as well as event numbers we obtain in our recast, showing good agreement.…”

Machine learning templates for QCD factorization in the search for physics beyond the standard model

“…A comparison between the predicted m j and observed m j is then sensitive to the presence of new particles. The ATLAS collaboration has successfully applied this method in both Run 1 and Run 2 to set strong limits on potential gluino and squark production [8,9]. The background estimation procedure described above has two major limitations 1 .…”

“…The application of GANs to the phase space relevant to the Supersymmetry (SUSY) search from Ref. [7][8][9] is presented in Sec. 3.…”