Published March 17, 2025 | Version v1
Model Open

Statistical models for CMS-SUS-23-015

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Description

Introduction

This resource contains the full statistical model related to the paper Search for new physics in jet scaling patterns of multilepton events at √s = 13 TeV, by the CMS collaboration.

The analysis searches for the production of a wino-like chargino-neutralino pair, decaying to bino-like neutralino pairs with the emissions of a W and Z pair. The two bino-like neutralinos then decay to three quarks through RPV interactions.

The results of the analysis are interpreted in two models, one in which the bino-like neutralino decays to uds, referred to as RPVq, and one in which the bino-like neutralino decays to udb, referred to as RPVb. The wino-like chargino neutralino pair is assumed to be mass degenerate, and each model is parametrized into the mass pair of the wino-like chargino and the bino-like neutralino.

The instructions below include the commands needed to reproduce the exclusion limits for the RPVq and RPVb models corresponding to Fig. 5 in the paper. For additional technical documentation please consult the Combine documentation.

Datacards

While a full description of the analysis can be found in the paper, a short description of the datacards contained in this repository follows.

Datacards are held in the input directory. A datacard is provided for each signal mass hypothesis. The naming conventions is:

dataCard_(RPVb|RPVq)[chargino_mass]n[neutralino_mass]_v39_Data_Naming.txt

Data, and templates for each of the signal and background processes, are arranged in histograms with 119 total bins, stored in a root file named:

dataCard_(RPVb|RPVq)[chargino_mass]n[neutralino_mass]_v39_Data_Naming.root

Each of the 119 bins represent a counting experiment in one of the several control and signal regions. The bin numbering scheme, with reference to symbols defined in the paper is described in the following table, with the first 13 bins corresponfing to control regions, and the remaining bins corresponding to signal regions.

Bin \(N_l\) OSSFn \(m_{OSSF}\) \(N_j\) \(N_b\) \(M_T\) (GeV) \(S_T\) (GeV)
1 4 OSSF2 2OnZ
2 4 OSSF2 OnZ 0
3 4 OSSF2 OnZ > 0 > 350
4 3 OSSF1 BelowZ
5 3 OSSF0
6 3 OSSF1 AboveZ 0
7 3 OSSF1 AboveZ >0
8 3 OSSF1 OnZ 0 <30
9 3 OSSF1 OnZ 0 30-90
10 3 OSSF1 OnZ 0 >90
11 3 OSSF1 OnZ 1 <30
12 3 OSSF1 OnZ 1 30-90
13 3 OSSF1 OnZ 1 >90
14 3 OSSF1 OnZ 2 0 <250
15-28 3 OSSF1 OnZ 2 0 250-1650 (100 GeV/bin)
29 3 OSSF1 OnZ 2 0 1650-1850
30 3 OSSF1 OnZ 2 0 >1850
31 3 OSSF1 OnZ 3 0 <350
32-45 3 OSSF1 OnZ 3 0 350-1750 (100 GeV/bin)
46 3 OSSF1 OnZ 3 0 1750-1950
47 3 OSSF1 OnZ 3 0 >1950
48 3 OSSF1 OnZ 4 0 <400
49-59 3 OSSF1 OnZ 4 0 400-1500 (100 GeV/bin)
60 3 OSSF1 OnZ 4 0 1500-1800
61 3 OSSF1 OnZ 4 0 >1800
62 3 OSSF1 OnZ >4 0 <600
63-67 3 OSSF1 OnZ >4 0 600-1600 (200 GeV/bin)
68 3 OSSF1 OnZ >4 0 >1600
69 3 OSSF1 OnZ 2 >0 <250
70-80 3 OSSF1 OnZ 2 >0 250-1350 (100 GeV/bin)
81 3 OSSF1 OnZ 2 >0 1350-1550
82 3 OSSF1 OnZ 2 >0 >1750
83 3 OSSF1 OnZ 3 >0 <300
84-95 3 OSSF1 OnZ 3 >0 300-1500
96 3 OSSF1 OnZ 3 >0 1500-1700 (100 GeV/bin)
97 3 OSSF1 OnZ 3 >0 >1700
98 3 OSSF1 OnZ 4 >0 <450
99-107 3 OSSF1 OnZ 4 >0 450-1350 (100 GeV/bin)
108-109 3 OSSF1 OnZ 4 >0 1350-1750 (200 GeV/bin)
110 3 OSSF1 OnZ 4 >0 >1750
111 3 OSSF1 OnZ >4 >0 <600
112-118 3 OSSF1 OnZ >4 >0 600-2000 (200 GeV/bin)
119 3 OSSF1 OnZ >4 >0 >2000

Nuisance parameters corresponding to systematic uncertainties are described and in input/systematics_description.html.

The parameter of interest (POI) is a signal strength modifier r of the expected cross section for the relevant model.

Software instructions

General installation instructions for Combine can be found in the Combine documentation.

A container image is provided to ensure reproducible results. The results in this README are obtained using v9.2.1:

docker run --name combine -it gitlab-registry.cern.ch/cms-cloud/combine-standalone:v9.2.1

A slim version of the container image is also available at gitlab-registry.cern.ch/cms-cloud/combine-standalone:v9.2.1-slim. Versions of packages in the slim container image do not match exactly with the ones in the default container, so small differences in the output of commands with respect to the ones shown below are to be expected.

You can copy files (such as the datacards and other inputs for combine) using docker cp as documented here.

For the commands below, you may require running ulimit -s unlimited; ulimit -u unlimited to avoid memory issues.

Instructions to reproduce Fig. 5

To reproduce the exclusion limits in Fig 5, you can, taking the example of RPVq model for the chargino mass of 600 GeV and neutralino mass 200 GeV you can do:

combine -M AsymptoticLimits input/dataCard_RPVq600n200_v39_Data_Naming.txt

This will result in the following output:

 -- AsymptoticLimits ( CLs ) --
Observed Limit: r < 3.9995
Expected  2.5%: r < 1.2866
Expected 16.0%: r < 1.7301
Expected 50.0%: r < 2.4219
Expected 84.0%: r < 3.4355
Expected 97.5%: r < 4.6940

Showing the observed, as well as expected limits.

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