Girth and groomed radius of jets recoiling against isolated photons in lead-lead and proton-proton collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV

The CMS collaboration Hayrapetyan, Aram ; Tumasyan, Armen ; Adam, Wolfgang ; et al.
Phys.Lett.B 861 (2025) 139088, 2025.
Inspire Record 2783507 DOI 10.17182/hepdata.151507

This Letter presents the first measurements of the groomed jet radius $R_\mathrm{g}$ and the jet girth $g$ in events with an isolated photon recoiling against a jet in lead-lead (PbPb) and proton-proton (pp) collisions at the LHC at a nucleon-nucleon center-of-mass energy of 5.02 TeV. The observables $R_\mathrm{g}$ and $g$ provide a quantitative measure of how narrow or broad a jet is. The analysis uses PbPb and pp data samples with integrated luminosities of 1.7 nb$^{-1}$ and 301 pb$^{-1}$, respectively, collected with the CMS experiment in 2018 and 2017. Events are required to have a photon with transverse momentum $p_\mathrm{T}^\gamma$$>$ 100 GeV and at least one jet back-to-back in azimuth with respect to the photon and with transverse momentum $p_\mathrm{T}^\text{jet}$ such that $p_\mathrm{T}^\text{jet} / p_\mathrm{T}^\gamma$$>$ 0.4. The measured $R_\mathrm{g}$ and $g$ distributions are unfolded to the particle level, which facilitates the comparison between the PbPb and pp results and with theoretical predictions. It is found that jets with $p_\mathrm{T}^\text{jet} / p_\mathrm{T}^\gamma$$>$ 0.8, i.e., those that closely balance the photon $p_\mathrm{T}^\gamma$, are narrower in PbPb than in pp collisions. Relaxing the selection to include jets with $p_\mathrm{T}^\text{jet} / p_\mathrm{T}^\gamma$$>$ 0.4 reduces the narrowing of the angular structure of jets in PbPb relative to the pp reference. This shows that selection bias effects associated with jet energy loss play an important role in the interpretation of jet substructure measurements.

28 data tables

Unfolded jet girth distribution in PbPb normalized to the number of jets that pass the $x_J$>0.4 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.

Covariance matrix of the statistical uncertainty in data for the unfolded jet girth distribution in PbPb for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the jet girth distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded jet girth distribution in PbPb for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the jet girth distribution.

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Version 2
A measurement of soft-drop jet observables in $pp$ collisions with the ATLAS detector at $\sqrt{s} = 13$ TeV

The ATLAS collaboration Aad, Georges ; Abbott, Brad ; Abbott, Dale Charles ; et al.
Phys.Rev.D 101 (2020) 052007, 2020.
Inspire Record 1772062 DOI 10.17182/hepdata.92073

Jet substructure quantities are measured using jets groomed with the soft-drop grooming procedure in dijet events from 32.9 fb$^{-1}$ of $pp$ collisions collected with the ATLAS detector at $\sqrt{s} = 13$ TeV. These observables are sensitive to a wide range of QCD phenomena. Some observables, such as the jet mass and opening angle between the two subjets which pass the soft-drop condition, can be described by a high-order (resummed) series in the strong coupling constant $\alpha_S$. Other observables, such as the momentum sharing between the two subjets, are nearly independent of $\alpha_S$. These observables can be constructed using all interacting particles or using only charged particles reconstructed in the inner tracking detectors. Track-based versions of these observables are not collinear safe, but are measured more precisely, and universal non-perturbative functions can absorb the collinear singularities. The unfolded data are directly compared with QCD calculations and hadron-level Monte Carlo simulations. The measurements are performed in different pseudorapidity regions, which are then used to extract quark and gluon jet shapes using the predicted quark and gluon fractions in each region. All of the parton shower and analytical calculations provide an excellent description of the data in most regions of phase space.

252 data tables

Data from Fig 6a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 6b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 6c. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

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Measurement of jet-substructure observables in top quark, $W$ boson and light jet production in proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

The ATLAS collaboration Aaboud, Morad ; Aad, Georges ; Abbott, Brad ; et al.
JHEP 08 (2019) 033, 2019.
Inspire Record 1724098 DOI 10.17182/hepdata.89324

A measurement of jet substructure variables is presented using data collected in 2016 by the ATLAS experiment at the LHC with proton-proton collisions at $\sqrt{s}=13$ TeV. Large-radius jets groomed with the trimming and soft-drop algorithms are studied. Dedicated event selections are used to study jets produced by light quarks or gluons, and hadronically decaying top quarks and $W$ bosons. The variables measured are sensitive to pronged substructure, and therefore are typically used for tagging jets from boosted massive particles. These include the energy correlation functions and the $N$-subjettiness variables. The number of subjets and the Les Houches angularity are also considered. The distributions of the substructure variables, corrected for detector effects, are compared to the predictions of various Monte Carlo event generators. They are also compared between the large-radius jets originating from light quarks or gluons, and hadronically decaying top quarks and $W$ bosons.

88 data tables

Figure 3a, Normalised differential Nsubjets distribution for soft-drop groomed jets, Dijet selection.

Figure 4a, Normalised differential LHA distribution for soft-drop groomed jets, Dijet selection

Figure 5a, Normalised differential C2 distribution for soft-drop groomed jets, Dijet selection

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Version 2
A measurement of the soft-drop jet mass in pp collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector

The ATLAS collaboration Aaboud, Morad ; Aad, Georges ; Abbott, Brad ; et al.
Phys.Rev.Lett. 121 (2018) 092001, 2018.
Inspire Record 1637587 DOI 10.17182/hepdata.79953

Jet substructure observables have significantly extended the search program for physics beyond the Standard Model at the Large Hadron Collider. The state-of-the-art tools have been motivated by theoretical calculations, but there has never been a direct comparison between data and calculations of jet substructure observables that are accurate beyond leading-logarithm approximation. Such observables are significant not only for probing the collinear regime of QCD that is largely unexplored at a hadron collider, but also for improving the understanding of jet substructure properties that are used in many studies at the Large Hadron Collider. This Letter documents a measurement of the first jet substructure quantity at a hadron collider to be calculated at next-to-next-to-leading-logarithm accuracy. The normalized, differential cross-section is measured as a function of log$_{10}\rho^2$, where $\rho$ is the ratio of the soft-drop mass to the ungroomed jet transverse momentum. This quantity is measured in dijet events from 32.9 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collisions recorded by the ATLAS detector. The data are unfolded to correct for detector effects and compared to precise QCD calculations and leading-logarithm particle-level Monte Carlo simulations.

12 data tables

Data from Fig 3a. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 3b. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 3c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. The uncertainties are applied symmetrically, though the cross section cannot go below zero in the first bin.

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