Inclusive search for squarks and gluinos in pp collisions at sqrt(s) = 7 TeV

TL;DR

This work presents an inclusive razor-based search for heavy particle pair production in $pp$ collisions at $\sqrt{s}=7$ TeV using CMS data corresponding to ${\cal L}=35\,\mathrm{pb}^{-1}$. By exploiting the variables $M_R$ and $R= M_T^{R}/M_R$, the analysis achieves a kinematic separation between signal and SM backgrounds and employs data-driven background estimates across electron, muon, and hadronic boxes. No significant excess is observed, leading to 95\% CL limits on signal yields and CMSSM parameter-space exclusions, as well as cross-section bounds for two simplified SUSY models. The razor approach demonstrates complementary sensitivity to MET-based searches and highlights the utility of data-driven background modeling in early LHC data for new-physics probes.

Abstract

A search is performed for heavy particle pairs produced in sqrt(s) = 7 TeV proton-proton collisions with 35 inverse picobarns of data collected by the CMS experiment at the LHC. The search is sensitive to squarks and gluinos of generic supersymmetry models, provided they are kinematically accessible, with minimal assumptions on properties of the lightest superpartner particle. The kinematic consistency of the selected events is tested against the hypothesis of heavy particle pair production using the dimensionless razor variable R, related to the missing transverse energy. The new physics signal is characterized by a broad peak in the distribution of MR, an event-by-event indicator of the heavy particle mass scale. This new approach is complementary to missing transverse energy-based searches. After background modeling based on data, and background rejection based on R and MR, no significant excess of events is found beyond the standard model expectations. The results are interpreted in the context of the constrained minimal supersymmetric standard model as well as two simplified supersymmetry models.

Figures (14)

• Figure 1: Scatter plot in the ($M_R$, $R$) plane for simulated events: (top left) QCD multijet, (top right) $\mathrm{W}$+jets, (bottom left) ${t}\overline{{t}}\xspace$+jets, and (bottom right) the SUSY benchmark model LM1 PTDR2 with $M_\Delta = 597\,\text{Ge\spaceV}\xspace$. The yields are normalized to an integrated luminosity of 35$\,\text{pb}^\text{$-$1}$. The bin size is (20$\,\text{Ge\spaceV}$$\times$ 0.015).
• Figure 2: (Left) $M_{R}$ distributions for different values of the $R$ threshold for data events in the QCD control box. Fits of the $M_{R}$ distribution to an exponential function and an asymmetric Gaussian at low $M_R$, are shown as dotted black curves. (Right) The exponential slope $S$ from fits to the $M_{R}$ distribution, as a function of the square of the $R$ threshold for data events in the QCD control box.
• Figure 3: (Left) $M_{R}$ distributions for different values of the $R$ threshold from data events selected in the MU (upper) and ELE (lower) boxes. Dotted curves show the results of fits using two independent exponential functions and an asymmetric Gaussian at low $M_R$. (Right) The slope $S$ of the first exponential component as a function of the square of the $R$ threshold in the MU (upper) and ELE (lower) boxes. The dotted lines show the results of the fits to the form $S = a + bR^{2}$.
• Figure 4: The $M_R$ distributions with $R > 0.45$ in the ELE (left) and MU (right) boxes for data (points) and backgrounds (curves). The bands show the uncertainties of the background predictions.
• Figure 5: The $M_R$ distributions with $R > 0.5$ in the HAD box for data (points) and backgrounds (curves) on (top) linear and (bottom) logarithmic scales. The bands show the uncertainties of the background predictions. The corresponding distributions for SUSY benchmark models LM1 PTDR2 with $M_\Delta = 597\,\text{Ge\spaceV}\xspace$ and LM0 alphaT with $M_\Delta = 400\,\text{Ge\spaceV}\xspace$ are overlaid.