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| CMS-PAS-TOP-24-001 | ||
| Measurement of the dineutrino system kinematics in dileptonic top quark pair events in pp collisions at $ \sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 31 July 2024 | ||
| Abstract: Differential top quark pair cross sections are measured in the dilepton final states $ e^{+}e^{-} $, $ \mu^{+}\mu^{-} $, and $ e^{\pm}\mu^{\mp} $, as a function of kinematics of the system of two neutrinos: the transverse momentum $ p_{T}^{\nu\nu} $ of the dineutrino system, the minimum distance in azimuthal angle between $ p_{T}^{\nu\nu} $ and leptons, and in two dimensions in bins of both observables. The measurements are performed using CERN LHC proton-proton collisions at $ \sqrt{s} = $ 13 TeV, recorded by the CMS detector between 2016 and 2018, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. The measured cross sections are unfolded to the particle level using an unregularized least square method. The obtained results are found to be in agreement with the latest theory predictions and Monte Carlo simulations of the standard model. | ||
| Links: CDS record (PDF) ; Physics Briefing ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
In the left diagram the standard model $ \mathrm{t} \overline{\mathrm{t}} $ process is sketched, while the right diagram shows the production of a hypothetical stop pair, where both stops decay to a top and a neutralino. This analysis focuses on signatures, where both of the W bosons decay leptonically. |
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Figure 1-a:
In the left diagram the standard model $ \mathrm{t} \overline{\mathrm{t}} $ process is sketched, while the right diagram shows the production of a hypothetical stop pair, where both stops decay to a top and a neutralino. This analysis focuses on signatures, where both of the W bosons decay leptonically. |
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Figure 1-b:
In the left diagram the standard model $ \mathrm{t} \overline{\mathrm{t}} $ process is sketched, while the right diagram shows the production of a hypothetical stop pair, where both stops decay to a top and a neutralino. This analysis focuses on signatures, where both of the W bosons decay leptonically. |
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Figure 2:
Observed (black markers) and expected distributions of leading lepton $ p_{\mathrm{T}} $ (top left), leading jet $ p_{\mathrm{T}} $ (top right), the number of jets (bottom left), and the number of b-tagged jets (bottom right), after event selection. The hatched (grey) areas denote the systematic (total) uncertainties on the expected yields. Events from all data-taking periods and all channels are combined. The lower panel of each plot shows the ratio between observed and expected distributions. The last bin includes all events above the plotted range. |
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Figure 2-a:
Observed (black markers) and expected distributions of leading lepton $ p_{\mathrm{T}} $ (top left), leading jet $ p_{\mathrm{T}} $ (top right), the number of jets (bottom left), and the number of b-tagged jets (bottom right), after event selection. The hatched (grey) areas denote the systematic (total) uncertainties on the expected yields. Events from all data-taking periods and all channels are combined. The lower panel of each plot shows the ratio between observed and expected distributions. The last bin includes all events above the plotted range. |
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Figure 2-b:
Observed (black markers) and expected distributions of leading lepton $ p_{\mathrm{T}} $ (top left), leading jet $ p_{\mathrm{T}} $ (top right), the number of jets (bottom left), and the number of b-tagged jets (bottom right), after event selection. The hatched (grey) areas denote the systematic (total) uncertainties on the expected yields. Events from all data-taking periods and all channels are combined. The lower panel of each plot shows the ratio between observed and expected distributions. The last bin includes all events above the plotted range. |
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Figure 2-c:
Observed (black markers) and expected distributions of leading lepton $ p_{\mathrm{T}} $ (top left), leading jet $ p_{\mathrm{T}} $ (top right), the number of jets (bottom left), and the number of b-tagged jets (bottom right), after event selection. The hatched (grey) areas denote the systematic (total) uncertainties on the expected yields. Events from all data-taking periods and all channels are combined. The lower panel of each plot shows the ratio between observed and expected distributions. The last bin includes all events above the plotted range. |
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Figure 2-d:
Observed (black markers) and expected distributions of leading lepton $ p_{\mathrm{T}} $ (top left), leading jet $ p_{\mathrm{T}} $ (top right), the number of jets (bottom left), and the number of b-tagged jets (bottom right), after event selection. The hatched (grey) areas denote the systematic (total) uncertainties on the expected yields. Events from all data-taking periods and all channels are combined. The lower panel of each plot shows the ratio between observed and expected distributions. The last bin includes all events above the plotted range. |
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Figure 3:
Difference between $ p_{\mathrm{T,gen.}}^\text{miss} $ and $ p_{\mathrm{T,rec.}}^\text{miss} $ as a function of the $ p_{\mathrm{T,gen.}}^\text{miss} $ (left) and the number of primary vertices (right) for signal events. The mean difference between the generated and the $ p_{\mathrm{T,rec.}}^\text{miss} $ per bin is shown as solid line, while the dashed line shows the corresponding $ \sigma $, which corresponds to the resolution. The results for $ p_{\mathrm{T}}^\text{miss} $ corrected by the DNN regression (light blue), derived with the PUPPI algorithm (red), and the PF algorithm (orange) are shown. A simulated sample for the 2018 data-taking period is used. |
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Figure 3-a:
Difference between $ p_{\mathrm{T,gen.}}^\text{miss} $ and $ p_{\mathrm{T,rec.}}^\text{miss} $ as a function of the $ p_{\mathrm{T,gen.}}^\text{miss} $ (left) and the number of primary vertices (right) for signal events. The mean difference between the generated and the $ p_{\mathrm{T,rec.}}^\text{miss} $ per bin is shown as solid line, while the dashed line shows the corresponding $ \sigma $, which corresponds to the resolution. The results for $ p_{\mathrm{T}}^\text{miss} $ corrected by the DNN regression (light blue), derived with the PUPPI algorithm (red), and the PF algorithm (orange) are shown. A simulated sample for the 2018 data-taking period is used. |
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Figure 3-b:
Difference between $ p_{\mathrm{T,gen.}}^\text{miss} $ and $ p_{\mathrm{T,rec.}}^\text{miss} $ as a function of the $ p_{\mathrm{T,gen.}}^\text{miss} $ (left) and the number of primary vertices (right) for signal events. The mean difference between the generated and the $ p_{\mathrm{T,rec.}}^\text{miss} $ per bin is shown as solid line, while the dashed line shows the corresponding $ \sigma $, which corresponds to the resolution. The results for $ p_{\mathrm{T}}^\text{miss} $ corrected by the DNN regression (light blue), derived with the PUPPI algorithm (red), and the PF algorithm (orange) are shown. A simulated sample for the 2018 data-taking period is used. |
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Figure 4:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 4-a:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 4-b:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 4-c:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 4-d:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 4-e:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 4-f:
Breakdown of the relative uncertainties from experimental (left) and theory (right) uncertainties on the differential cross section measurement as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center) and both variables (bottom). In the latter case, each group of 4 bins corresponds to $ p_{\text{T}}^{\nu\nu} $ bins, and $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ bin edges are indicated by vertical dashed lines. The statistical uncertainty (dark grey) takes the available statistics of both the simulated samples and the recorded data into account. |
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Figure 5:
The observed (black markers) and simulated distributions of $ p_{\mathrm{T,DNN}}^\text{miss} $ (top left), $ \text{min}[\Delta\phi(p_{\mathrm{T}}^\text{miss},\ell)] $ (top right), and the two-dimensional distribution with both observables (bottom) are shown. Events from all data-taking periods and all channels are combined. The hatched (grey) areas indicate the systematic (total) uncertainty on the simulation. The bottom panel of each plot shows the ratio of observed data to the expectation from MC simulation in each bin. The last bin includes all events above the plotted range. |
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Figure 5-a:
The observed (black markers) and simulated distributions of $ p_{\mathrm{T,DNN}}^\text{miss} $ (top left), $ \text{min}[\Delta\phi(p_{\mathrm{T}}^\text{miss},\ell)] $ (top right), and the two-dimensional distribution with both observables (bottom) are shown. Events from all data-taking periods and all channels are combined. The hatched (grey) areas indicate the systematic (total) uncertainty on the simulation. The bottom panel of each plot shows the ratio of observed data to the expectation from MC simulation in each bin. The last bin includes all events above the plotted range. |
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Figure 5-b:
The observed (black markers) and simulated distributions of $ p_{\mathrm{T,DNN}}^\text{miss} $ (top left), $ \text{min}[\Delta\phi(p_{\mathrm{T}}^\text{miss},\ell)] $ (top right), and the two-dimensional distribution with both observables (bottom) are shown. Events from all data-taking periods and all channels are combined. The hatched (grey) areas indicate the systematic (total) uncertainty on the simulation. The bottom panel of each plot shows the ratio of observed data to the expectation from MC simulation in each bin. The last bin includes all events above the plotted range. |
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Figure 5-c:
The observed (black markers) and simulated distributions of $ p_{\mathrm{T,DNN}}^\text{miss} $ (top left), $ \text{min}[\Delta\phi(p_{\mathrm{T}}^\text{miss},\ell)] $ (top right), and the two-dimensional distribution with both observables (bottom) are shown. Events from all data-taking periods and all channels are combined. The hatched (grey) areas indicate the systematic (total) uncertainty on the simulation. The bottom panel of each plot shows the ratio of observed data to the expectation from MC simulation in each bin. The last bin includes all events above the plotted range. |
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Figure 6:
Result of the closure test based on simulation. The potential BSM contribution is scaled by a factor of ten. The test is performed for the $ p_{\text{T}}^{\nu\nu} $ (top) and 2D measurement (bottom) using the nominal (black), the regularized (orange), and the bin-by-bin unfolding (purple), based on all data-taking periods combined. The unfolded distributions are compared to the expected distribution (red) based on the sum of the nominal dileptonic $ \mathrm{t} \overline{\mathrm{t}} $ signal sample and BSM signal with the corresponding $ \chi^2/\text{ndf} $ values given in the legend. The nominal distribution, used for the response matrix, is shown in blue. The error bars correspond to the statistical uncertainty. The lower part shows the ratios between the unfolded and the expected distributions. |
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Figure 6-a:
Result of the closure test based on simulation. The potential BSM contribution is scaled by a factor of ten. The test is performed for the $ p_{\text{T}}^{\nu\nu} $ (top) and 2D measurement (bottom) using the nominal (black), the regularized (orange), and the bin-by-bin unfolding (purple), based on all data-taking periods combined. The unfolded distributions are compared to the expected distribution (red) based on the sum of the nominal dileptonic $ \mathrm{t} \overline{\mathrm{t}} $ signal sample and BSM signal with the corresponding $ \chi^2/\text{ndf} $ values given in the legend. The nominal distribution, used for the response matrix, is shown in blue. The error bars correspond to the statistical uncertainty. The lower part shows the ratios between the unfolded and the expected distributions. |
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Figure 6-b:
Result of the closure test based on simulation. The potential BSM contribution is scaled by a factor of ten. The test is performed for the $ p_{\text{T}}^{\nu\nu} $ (top) and 2D measurement (bottom) using the nominal (black), the regularized (orange), and the bin-by-bin unfolding (purple), based on all data-taking periods combined. The unfolded distributions are compared to the expected distribution (red) based on the sum of the nominal dileptonic $ \mathrm{t} \overline{\mathrm{t}} $ signal sample and BSM signal with the corresponding $ \chi^2/\text{ndf} $ values given in the legend. The nominal distribution, used for the response matrix, is shown in blue. The error bars correspond to the statistical uncertainty. The lower part shows the ratios between the unfolded and the expected distributions. |
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Figure 7:
The measured signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 7-a:
The measured signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 7-b:
The measured signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 7-c:
The measured signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 8:
The measured normalized signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 8-a:
The measured normalized signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 8-b:
The measured normalized signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
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Figure 8-c:
The measured normalized signal cross sections (black markers) as a function of $ p_{\text{T}}^{\nu\nu} $ (top), $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $ (center), and both observables in two dimensions (bottom) are shown. The theoretical predictions from POWHEG +PYTHIA (dark red), POWHEG + HERWIG (orange), MC@NLO+PYTHIA (purple), and the fixed-order NLO (light blue) and NNLO (brown) calculations are compared to the measurement. The total (statistical) uncertainty on the measurement is shown as an orange (dark grey) band. The bottom panel of each plot shows the ratio between theoretical predictions and the measurement. |
| Tables | |
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Table 1:
Data and MC simulation yields after selection, combined for all data-taking periods and split by channels. The uncertainties on the simulation yield include systematic and statistical uncertainties (see also Section 6). The relative contribution in percent of each process to the total expected yield of a channel is given in parentheses. |
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Table 2:
Definition of the fiducial phase space for the same-flavor channels and the different-flavor channel. The two leptons have to be oppositely charged. |
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Table 3:
Results of the $ \chi^2 $ tests for the absolute and normalized differential cross section measurements for each of the predictions. The $ \chi^2 $ values including uncertainties on the predictions are given in parentheses. |
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Table 4:
p-values of the $ \chi^2 $ tests for the absolute and normalized cross section measurements for each of the predictions. The resulting p-values including uncertainties on the predictions are given in parentheses. |
| Summary |
| Measurements of differential top pair production cross section in the dileptonic channel in pp collisions at $ \sqrt{s}= $ 13 TeV using observables based on the dineutrino kinematics have been presented. The measurements are performed based on collision data recorded by the CMS detector between 2016 and 2018 during the Run 2 operation of the LHC corresponding to an integrated luminosity of 138 fb$^{-1}$. The differential cross sections are derived as a function of the transverse momentum of the dineutrino system $ p_{\text{T}}^{\nu\nu} $ and the minimal azimuthal angle between the dineutrino system and a lepton $ \text{min}[\Delta\phi(p_{\text{T}}^{\nu\nu},\ell)] $, as well as both observables in two dimensions. To improve the resolution of the missing transverse momentum, which serves as a measure for $ p_{\text{T}}^{\nu\nu} $ in signal events, a dedicated DNN regression has been developed. The method significantly improves the resolution of both the magnitude and the azimuthal angle of the missing transverse momentum. The absolute and normalized differential cross section results are obtained based on an unregularized least square unfolding method. The differential cross sections are compared to predictions based on MC simulation as well as two fixed-order theory calculations, corresponding to NLO and NNLO accuracy in QCD. Given the so far unexplored observables and phase space regions considered in this analysis, remarkable agreement between the different theory predictions and the measured differential cross sections has been observed. For both one-dimensional measurements, the best overall description is provided by the two POWHEG predictions, while for the two-dimensional measurement the best agreement is observed for the NNLO fixed-order calculation. However, the differences between the five predictions are mostly small, such that none of the predictions is significantly disfavored by the measured differential cross sections. |
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