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| CMS-TOP-17-015 ; CERN-EP-2018-177 | ||
| Study of the underlying event in top quark pair production in pp collisions at 13 TeV | ||
| CMS Collaboration | ||
| 8 July 2018 | ||
| Eur. Phys. J. C 79 (2019) 123 | ||
| Abstract: Measurements of normalized differential cross sections as functions of the multiplicity and kinematic variables of charged-particle tracks from the underlying event in top quark and antiquark pair production are presented. The measurements are performed in proton-proton collisions at a center-of-mass energy of 13 TeV, and are based on data collected by the CMS experiment at the LHC in 2016 corresponding to an integrated luminosity of 35.9 fb$^{-1}$. Events containing one electron, one muon, and two jets from the hadronization and fragmentation of b quarks are used. These measurements characterize, for the first time, properties of the underlying event in top quark pair production and show no deviation from the universality hypothesis at energy scales typically above twice the top quark mass. | ||
| Links: e-print arXiv:1807.02810 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Distribution of all PF candidates reconstructed in a POWHEG+PYTHIA8 simulated ${{\mathrm {t}\overline {\mathrm {t}}}}$ event in the $\eta $-$\phi $ plane. Only particles with $ {p_{\mathrm {T}}} > $ 900 MeV are shown, with a marker whose are is proportional to the particle $ {p_{\mathrm {T}}} $. The fiducial region in $\eta $ is represented by the dashed lines. |
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Figure 2:
Distributions of the variables used to categorize the study of the UE. Upper left: multiplicity of additional jets ($ {p_{\mathrm {T}}} > $ 30 GeV). Upper right: $ {{p_{\mathrm {T}}} (\ell \ell)} $. Lower: $ {m(\ell \ell)} $. The distributions in data are compared to the sum of the expectations for the signal and backgrounds. The shaded band represents the uncertainty associated to the integrated luminosity and the theoretical value of the ${{\mathrm {t}\overline {\mathrm {t}}}}$ cross section. |
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Figure 2-a:
Distribution of the multiplicity of additional jets ($ {p_{\mathrm {T}}} > $ 30 GeV). The distribution in data is compared to the sum of the expectations for the signal and backgrounds. The shaded band represents the uncertainty associated to the integrated luminosity and the theoretical value of the ${{\mathrm {t}\overline {\mathrm {t}}}}$ cross section. |
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Figure 2-b:
Distribution of $ {{p_{\mathrm {T}}} (\ell \ell)} $. The distribution in data is compared to the sum of the expectations for the signal and backgrounds. The shaded band represents the uncertainty associated to the integrated luminosity and the theoretical value of the ${{\mathrm {t}\overline {\mathrm {t}}}}$ cross section. |
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Figure 2-c:
Distribution of $ {m(\ell \ell)} $. The distribution in data is compared to the sum of the expectations for the signal and backgrounds. The shaded band represents the uncertainty associated to the integrated luminosity and the theoretical value of the ${{\mathrm {t}\overline {\mathrm {t}}}}$ cross section. |
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Figure 3:
Display of the transverse momentum of the selected charged particles, the two leptons, and the dilepton pair in the transverse plane corresponding to the same event as in Fig. 1. The $ {p_{\mathrm {T}}} $ of the particles is proportional to the length of the arrows and the dashed lines represent the regions that are defined relative to the $ {{\vec{p}_{\mathrm {T}}} (\ell \ell)} $ direction. For clarity, the $ {p_{\mathrm {T}}} $ of the leptons has been rescaled by a factor of 0.5. |
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Figure 4:
The normalized differential cross section as a function of $ {N_\text {ch}} $ is shown on the upper panel. The data (colored boxes) are compared to the nominal POWHEG+PYTHIA8 predictions and to the expectations obtained from varied $ {\alpha _S} ^\text {ISR}(M_ {\mathrm {Z}})$ or $ {\alpha _S} ^\text {FSR}(M_ {\mathrm {Z}})$ POWHEG+PYTHIA8 setups (markers). The different panels on the lower display show the ratio between each model tested (see text) and the data. In both cases the shaded (hatched) band represents the total (statistical) uncertainty of the data, while the error bars represent either the total uncertainty of the POWHEG+PYTHIA8 setup, computed as described in the text, or the statistical uncertainty of the other MC simulation setups. |
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Figure 4-a:
The normalized differential cross section as a function of $ {N_\text {ch}} $ is shown. The data (colored boxes) are compared to the nominal POWHEG+PYTHIA8 predictions and to the expectations obtained from varied $ {\alpha _S} ^\text {ISR}(M_ {\mathrm {Z}})$ or $ {\alpha _S} ^\text {FSR}(M_ {\mathrm {Z}})$ POWHEG+PYTHIA8 setups (markers). |
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Figure 4-b:
The different panels show the ratio between each model tested (see text) and the data. In both cases the shaded (hatched) band represents the total (statistical) uncertainty of the data, while the error bars represent either the total uncertainty of the POWHEG+PYTHIA8 setup, computed as described in the text, or the statistical uncertainty of the other MC simulation setups. |
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Figure 5:
Normalized differential cross section as function of $\Sigma {p_{\mathrm {T}}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 5-a:
Normalized differential cross section as function of $\Sigma {p_{\mathrm {T}}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 5-b:
Normalized differential cross section as function of $\Sigma {p_{\mathrm {T}}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 6:
Normalized differential cross section as function of $ {\overline {{p_{\mathrm {T}}}}} $, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 6-a:
Normalized differential cross section as function of $ {\overline {{p_{\mathrm {T}}}}} $, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 6-b:
Normalized differential cross section as function of $ {\overline {{p_{\mathrm {T}}}}} $, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 7:
Normalized differential cross section as function of $ {{| {\vec{p}_{\mathrm {T}}} |}} $, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 7-a:
Normalized differential cross section as function of $ {{| {\vec{p}_{\mathrm {T}}} |}} $, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 7-b:
Normalized differential cross section as function of $ {{| {\vec{p}_{\mathrm {T}}} |}} $, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 8:
Normalized differential cross section as function of ${\Sigma p_{z}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 8-a:
Normalized differential cross section as function of ${\Sigma p_{z}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 8-b:
Normalized differential cross section as function of ${\Sigma p_{z}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 9:
Normalized differential cross section as function of ${\overline {p_z}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 9-a:
Normalized differential cross section as function of ${\overline {p_z}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 9-b:
Normalized differential cross section as function of ${\overline {p_z}}$ , compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 10:
Normalized differential cross section as function of the sphericity variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 10-a:
Normalized differential cross section as function of the sphericity variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 10-b:
Normalized differential cross section as function of the sphericity variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 11:
Normalized differential cross section as function of the aplanarity variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 11-a:
Normalized differential cross section as function of the aplanarity variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 11-b:
Normalized differential cross section as function of the aplanarity variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 12:
Normalized differential cross section as function of the $C$ variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 12-a:
Normalized differential cross section as function of the $C$ variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 12-b:
Normalized differential cross section as function of the $C$ variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 13:
Normalized differential cross section as function of the $D$ variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 13-a:
Normalized differential cross section as function of the $D$ variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 13-b:
Normalized differential cross section as function of the $D$ variable, compared to the predictions of different models. The conventions of Fig. 4 are used. |
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Figure 14:
Average $ {N_\text {ch}} $ in different event categories. The mean observed in data (boxes) is compared to the predictions from different models (markers), which are superimposed in the upper figure. The total (statistical) uncertainty of the data is represented by a shaded (hatched) area and the statistical uncertainty of the models is represented with error bars. In the specific case of the POWHEG+PYTHIA8 model the error bars represent the total uncertainty (see text). The lower figure displays the pull between different models and the data, with the different panels corresponding to different sets of models. The bands represent the interval where $ {| \text {pull} |} < $ 1. The error bar for the POWHEG+PYTHIA8 model represents the range of variation of the pull for the different configurations described in the text. |
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Figure 14-a:
Average $ {N_\text {ch}} $ in different event categories. The mean observed in data (boxes) is compared to the predictions from different models (markers), which are superimposed in the upper figure. The total (statistical) uncertainty of the data is represented by a shaded (hatched) area and the statistical uncertainty of the models is represented with error bars. In the specific case of the POWHEG+PYTHIA8 model the error bars represent the total uncertainty (see text). The lower figure displays the pull between different models and the data, with the different panels corresponding to different sets of models. The bands represent the interval where $ {| \text {pull} |} < $ 1. The error bar for the POWHEG+PYTHIA8 model represents the range of variation of the pull for the different configurations described in the text. |
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Figure 14-b:
Average $ {N_\text {ch}} $ in different event categories. The mean observed in data (boxes) is compared to the predictions from different models (markers), which are superimposed in the upper figure. The total (statistical) uncertainty of the data is represented by a shaded (hatched) area and the statistical uncertainty of the models is represented with error bars. In the specific case of the POWHEG+PYTHIA8 model the error bars represent the total uncertainty (see text). The lower figure displays the pull between different models and the data, with the different panels corresponding to different sets of models. The bands represent the interval where $ {| \text {pull} |} < $ 1. The error bar for the POWHEG+PYTHIA8 model represents the range of variation of the pull for the different configurations described in the text. |
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Figure 15:
Average $\Sigma {p_{\mathrm {T}}}$ in different event categories. The conventions of Fig. 14 are used. |
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Figure 15-a:
Average $\Sigma {p_{\mathrm {T}}}$ in different event categories. The conventions of Fig. 14 are used. |
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Figure 15-b:
Average $\Sigma {p_{\mathrm {T}}}$ in different event categories. The conventions of Fig. 14 are used. |
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Figure 16:
Average ${\Sigma p_{z}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 16-a:
Average ${\Sigma p_{z}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 16-b:
Average ${\Sigma p_{z}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 17:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 17-a:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 17-b:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 18:
Average ${{\overline {p_z}}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 18-a:
Average ${{\overline {p_z}}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 18-b:
Average ${{\overline {p_z}}}$ in different categories. The conventions of Fig. 14 are used. |
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Figure 19:
Average $ {{| {\vec{p}_{\mathrm {T}}} |}} $ in different categories. The conventions of Fig. 14 are used. |
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Figure 19-a:
Average $ {{| {\vec{p}_{\mathrm {T}}} |}} $ in different categories. The conventions of Fig. 14 are used. |
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Figure 19-b:
Average $ {{| {\vec{p}_{\mathrm {T}}} |}} $ in different categories. The conventions of Fig. 14 are used. |
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Figure 20:
Average sphericity in different categories. The conventions of Fig. 14 are used. |
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Figure 20-a:
Average sphericity in different categories. The conventions of Fig. 14 are used. |
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Figure 20-b:
Average sphericity in different categories. The conventions of Fig. 14 are used. |
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Figure 21:
Average aplanarity in different categories. The conventions of Fig. 14 are used. |
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Figure 21-a:
Average aplanarity in different categories. The conventions of Fig. 14 are used. |
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Figure 21-b:
Average aplanarity in different categories. The conventions of Fig. 14 are used. |
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Figure 22:
Average $C$ in different categories. The conventions of Fig. 14 are used. |
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Figure 22-a:
Average $C$ in different categories. The conventions of Fig. 14 are used. |
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Figure 22-b:
Average $C$ in different categories. The conventions of Fig. 14 are used. |
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Figure 23:
Average $D$ in different categories. The conventions of Fig. 14 are used. |
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Figure 23-a:
Average $D$ in different categories. The conventions of Fig. 14 are used. |
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Figure 23-b:
Average $D$ in different categories. The conventions of Fig. 14 are used. |
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Figure 24:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different $ {{p_{\mathrm {T}}} (\ell \ell)} $ categories. The conventions of Fig. 14 are used. |
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Figure 24-a:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different $ {{p_{\mathrm {T}}} (\ell \ell)} $ categories. The conventions of Fig. 14 are used. |
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Figure 24-b:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different $ {{p_{\mathrm {T}}} (\ell \ell)} $ categories. The conventions of Fig. 14 are used. |
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Figure 25:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different jet multiplicity categories. The conventions of Fig. 14 are used. |
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Figure 25-a:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different jet multiplicity categories. The conventions of Fig. 14 are used. |
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Figure 25-b:
Average ${{\overline {{p_{\mathrm {T}}}}}}$ in different jet multiplicity categories. The conventions of Fig. 14 are used. |
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Figure 26:
Scan of the $\chi ^2$ as a function of the value of $ {\alpha _S} ^\text {FSR}(M_ {\mathrm {Z}})$ employed in the POWHEG+PYTHIA8 simulation, when the inclusive ${{\overline {{p_{\mathrm {T}}}}}}$ or the ${{\overline {{p_{\mathrm {T}}}}}}$ distribution measured in different regions is used. The curves result from a fourth-order polynomial interpolation between the simulated $ {\alpha _S} ^\text {FSR}(M_ {\mathrm {Z}})$ points. |
| Tables | |
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Table 1:
MC simulation settings used for the comparisons with the differential cross section measurements of the UE. The table lists the main characteristics and values used for the most relevant parameters of the generators. The row labeled "Setup designation'' shows the definitions of the abbreviations used throughout this paper. |
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Table 2:
Uncertainties affecting the measurement of the average of the UE observables. The values are expressed in% and the last row reports the quadratic sum of the individual contributions. |
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Table 3:
Comparison between the measured distributions at particle level and the predictions of different generator setups. We list the results of the $\chi ^2$ tests together with dof. For the comparison no uncertainties in the predictions are taken into account, except for the POWHEG+PYTHIA8 setup for which the comparison including the theoretical uncertainties is quoted separately in parenthesis. |
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Table 4:
The first rows give the best fit values for $ {\alpha _S} ^\text {FSR}$ for the POWHEG+PYTHIA8 setup, obtained from the inclusive distribution of different observables and the corresponding 68 and 95% confidence intervals. The last two rows give the preferred value of the renormalization scale in units of $M_ {\mathrm {Z}}$, and the associated $ \pm $1$ \sigma $ interval that can be used as an estimate of its variation to encompass the differences between data and the POWHEG+PYTHIA8 setup. |
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Table 5:
Variations of the POWHEG+PYTHIA8 setup used for the comparison with the measurements. The values changed with respect to the CUETP8M2T4 tune are given in the columns corresponding to each model. Further details on parameters or specificities of the models can be found in Ref. [16, 71, 3, 31, 31, 4, 32, 33]. For the Rope hadronization model two variations are considered: one with no CR and the other with the default CR model. The settings for the former are denoted in parenthesis in the last column. |
| Summary |
|
The first measurement of the underlying event (UE) activity in $\mathrm{t\bar{t}}$ dilepton events produced in hadron colliders has been reported. The measurement makes use of $\sqrt{s} = $ 13 TeV proton-proton collision data collected by the CMS experiment in 2016, and corresponding to 35.9 fb$^{-1}$. Using particle-flow reconstruction, the contribution from the UE has been isolated by removing charged particles associated with the decay products of the $\mathrm{t\bar{t}}$ event candidates as well as with pileup interactions from the set of reconstructed charged particles per event. The measurements performed are expected to be valid for other $\mathrm{t\bar{t}}$ final states, and can be used as a reference for complementary studies, eg, of how different color reconnection (CR) models compare to data in the description of the jets from $\mathrm{W}\to \mathrm{q}\mathrm{\bar{q}}'$ decays. The chosen observables and categories enhance the sensitivity to the modeling of multiparton interactions (MPI), CR and the choice of strong coupling parameter at the mass of Z boson (${\alpha_S}^\text{FSR}(M_\mathrm{Z})$) in the PYTHIA8 parton shower Monte Carlo simulation. These parameters have significant impact on the modeling of $\mathrm{t\bar{t}}$ production at the LHC. In particular, the compatibility of the data with different choices of the ${\alpha_S}^\text{FSR}(M_\mathrm{Z})$ parameter in PYTHIA8 has been quantified, resulting in a lower value than the one considered in Ref. [71]. The majority of the distributions analyzed indicate a fair agreement between the data and the POWHEG+PYTHIA8 setup with the CUETP8M2T4 tune [17], but disfavor the setups in which MPI and CR are switched off, or in which ${\alpha_S}^\text{FSR}(M_\mathrm{Z})$ is increased. The data also disfavor the default configurations in HERWIG++, HERWIG7, and SHERPA. It has been furthermore verified that, as expected, the choice of the next-to-leading-order matrix-element generator does not impact significantly the expected characteristics of the UE by comparing predictions from POWHEG and MadGraph5+MCatNLO, both interfaced with PYTHIA8. The present results test the hypothesis of universality in UE at an energy scale typically higher than the ones at which models have been studied. The UE model is tested up to a scale of two times the top quark mass, and the measurements in categories of dilepton invariant mass indicate that it should be valid at even higher scales. In addition, they can be used to improve the assessment of systematic uncertainties in future top quark analyses. The results obtained in this study show that a value of ${\alpha_S}^\text{FSR}(M_\mathrm{Z})=$ 0.120 $\pm$ 0.006 is consistent with the data. The corresponding uncertainties translate to a variation of the renormalization scale by a factor of $\sqrt{2}$. |
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