CMS-SMP-19-003 ; CERN-EP-2020-040 | ||
Dependence of inclusive jet production on the anti-${k_{\mathrm{T}}}$ distance parameter in pp collisions at $\sqrt{s} = $ 13 TeV | ||
CMS Collaboration | ||
11 May 2020 | ||
JHEP 12 (2020) 082 | ||
Abstract: The dependence of inclusive jet production in proton-proton collisions with a center-of-mass energy of 13 TeV on the distance parameter $R$ of the anti-${k_{\mathrm{T}}}$ algorithm is studied using data corresponding to integrated luminosities up to 35.9 fb$^{-1}$ collected by the CMS experiment in 2016. The ratios of the inclusive cross sections as functions of transverse momentum ${p_{\mathrm{T}}}$ and rapidity $y$, for $R$ in the range 0.1 to 1.2 to those using $R= $ 0.4 are presented in the region 84 $ < {p_{\mathrm{T}}} < $ 1588 GeV and $|y| < $ 2.0. The results are compared to calculations at leading and next-to-leading order in the strong coupling constant using different parton shower models. The variation of the ratio of cross sections with $R$ is well described by calculations including a parton shower model, but not by a leading-order quantum chromodynamics calculation including nonperturbative effects. The agreement between the data and the theoretical predictions for the ratios of cross sections is significantly improved when next-to-leading order calculations with nonperturbative effects are used. | ||
Links: e-print arXiv:2005.05159 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; HepData record ; CADI line (restricted) ; |
Figures | |
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Figure 1:
Response matrix constructed from a simulation of a sample generated using PYTHIA, for AK4 jets in the $ {| y |} < $ 0.5 bin (left). A correlation matrix generated after data is unfolded by the D'Agostini unfolding using PYTHIA simulation for AK4 jets (right). |
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Figure 1-a:
Response matrix constructed from a simulation of a sample generated using PYTHIA, for AK4 jets in the $ {| y |} < $ 0.5 bin. |
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Figure 1-b:
A correlation matrix generated after data is unfolded by the D'Agostini unfolding using PYTHIA simulation for AK4 jets. |
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Figure 2:
Nonperturbative correction factor for the cross section ratio of inclusive AK2 (left) and AK8 jets (right) with respect to the AK4 jets in the rapidity bin $ {| y |} < $ 0.5. Vertical error bars represent the statistical uncertainty of the NP correction for different predictions. |
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Figure 2-a:
Nonperturbative correction factor for the cross section ratio of inclusive AK2 jets with respect to the AK4 jets in the rapidity bin $ {| y |} < $ 0.5. Vertical error bars represent the statistical uncertainty of the NP correction for different predictions. |
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Figure 2-b:
Nonperturbative correction factor for the cross section ratio of inclusive AK8 jets with respect to the AK4 jets in the rapidity bin $ {| y |} < $ 0.5. Vertical error bars represent the statistical uncertainty of the NP correction for different predictions. |
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Figure 3:
Total uncertainty (relative) from experimental sources for the ratio of cross section of inclusive jets of size 0.2 (top) and 0.8 (bottom) with respect to that of AK4 jets in the rapidity bin $ {| y |} < $ 0.5. Statistical uncertainties are also overlaid as vertical black (red) bars for data (response matrices, RM, in simulation). |
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Figure 3-a:
Total uncertainty (relative) from experimental sources for the ratio of cross section of inclusive jets of size 0.2 with respect to that of AK4 jets in the rapidity bin $ {| y |} < $ 0.5. Statistical uncertainties are also overlaid as vertical black (red) bars for data (response matrices, RM, in simulation). |
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Figure 3-b:
Total uncertainty (relative) from experimental sources for the ratio of cross section of inclusive jets of size 0.8 with respect to that of AK4 jets in the rapidity bin $ {| y |} < $ 0.5. Statistical uncertainties are also overlaid as vertical black (red) bars for data (response matrices, RM, in simulation). |
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Figure 4:
Comparison of the ratio of the differential cross sections of jets of different sizes with respect to that of AK4 jets from data and from NLO predictions using POWHEG $+$ PYTHIA (CUETP8M1 tune) in the region $ {| y |} < $ 0.5. Colored symbols indicate data and colored lines represent prediction from simulation. Offsets by the amount written in the parentheses have been added to the corresponding data points to separate the results for different jet sizes. |
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Figure 5:
Comparison of the ratios of differential cross sections for the AK2 (upper) and AK8 (lower) jets with respect to that of AK4 jets from data and ${p\text {QCD}}$ predictions using NLOJET++ in the region $ {| y |} < $ 0.5. Black symbols indicate data and colored lines represent ${p\text {QCD}}$ predictions. Statistical uncertainties are shown as vertical bars for the data and the NLO$\otimes $NP prediction. The yellowish olive region around data represents the experimental systematic uncertainty whereas the region shaded in light blue color around NLO$\otimes $NP prediction shows the theoretical uncertainty in the prediction. |
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Figure 5-a:
Comparison of the ratios of differential cross sections for the AK2 jets with respect to that of AK4 jets from data and ${p\text {QCD}}$ predictions using NLOJET++ in the region $ {| y |} < $ 0.5. Black symbols indicate data and colored lines represent ${p\text {QCD}}$ predictions. Statistical uncertainties are shown as vertical bars for the data and the NLO$\otimes $NP prediction. The yellowish olive region around data represents the experimental systematic uncertainty whereas the region shaded in light blue color around NLO$\otimes $NP prediction shows the theoretical uncertainty in the prediction. |
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Figure 5-b:
Comparison of the ratios of differential cross sections for the AK8 jets with respect to that of AK4 jets from data and ${p\text {QCD}}$ predictions using NLOJET++ in the region $ {| y |} < $ 0.5. Black symbols indicate data and colored lines represent ${p\text {QCD}}$ predictions. Statistical uncertainties are shown as vertical bars for the data and the NLO$\otimes $NP prediction. The yellowish olive region around data represents the experimental systematic uncertainty whereas the region shaded in light blue color around NLO$\otimes $NP prediction shows the theoretical uncertainty in the prediction. |
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Figure 6:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of jet ${p_{\mathrm {T}}}$ in data, and for multiple theoretical predictions in rapidity bins $ {| y |} < $ 0.5 (left column) and 1.5 $ < {| y |} < $ 2.0 (right column) at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
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Figure 6-a:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of 196 $<$ jet ${p_{\mathrm {T}}} < $ 272 GeV in data, and for multiple theoretical predictions in rapidity bin $ {| y |} < $ 0.5 at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
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Figure 6-b:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of 196 $<$ jet ${p_{\mathrm {T}}} < $ 272 GeV in data, and for multiple theoretical predictions in rapidity bin 1.5 $ < {| y |} < $ 2.0 at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
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Figure 6-c:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of 395 $<$ jet ${p_{\mathrm {T}}} < $ 468 GeV in data, and for multiple theoretical predictions in rapidity bin $ {| y |} < $ 0.5 at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
png pdf |
Figure 6-d:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of 395 $<$ jet ${p_{\mathrm {T}}} < $ 468 GeV in data, and for multiple theoretical predictions in rapidity bin 1.5 $ < {| y |} < $ 2.0 at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
png pdf |
Figure 6-e:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of 548 $<$ jet ${p_{\mathrm {T}}} < $ 638 GeV in data, and for multiple theoretical predictions in rapidity bin $ {| y |} < $ 0.5 at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
png pdf |
Figure 6-f:
Comparison of the ratio of cross sections of inclusive jets of various sizes with respect to AK4 jets, as a function of jet size in different regions of 548 $<$ jet ${p_{\mathrm {T}}} < $ 638 GeV in data, and for multiple theoretical predictions in rapidity bin 1.5 $ < {| y |} < $ 2.0 at particle level. When the dijet production cross section ratio is presented using pure NLO predictions for two jet sizes, the ratio becomes LO at ${\alpha _S} $; this is quoted as LO$\otimes $NP in the figure. Points corresponding to a particular prediction are connected via lines to guide the eye. Experimental uncertainties in the ratio of cross sections are shown with bands around the data points, whereas theoretical uncertainties are shown with the bands around the fixed-order predictions. |
Tables | |
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Table 1:
Trigger ${p_{\mathrm {T}}}$ thresholds and effective integrated luminosity of the HLT triggers based on AK8 jets. These triggers were not active during the initial part of data taking in 2016, thus the maximum integrated luminosity is less than 35.9 fb$^{-1}$. |
Summary |
A measurement has been made of the ratio of cross sections of inclusive anti-${k_{\mathrm{T}}}$ jets of multiple sizes with respect to jets with the distance parameter $R = $ 0.4; this is the first such result from the CMS Collaboration. Because of cancellation of many experimental and theoretical systematic uncertainties for the ratio, it is more sensitive to perturbative and nonperturbative effects than the absolute cross section measurement; the experimental systematic uncertainty in the cross section ratio is of similar size as the statistical uncertainty, whereas the theoretical uncertainty is dominated by the choice of the renormalization and factorization scales. From the ratio measurement, we observe that the nonperturbative correction is important in describing the data at low transverse momentum. Thus, the modeling of nonperturbative effects, such as hadronization and the underlying event has a significant impact on the description of the data in different regions of phase space. Finally, the variation of the ratio of cross sections with jet size $R$ emphasizes the importance of the inclusion of parton showering algorithms to capture the effects of higher-order terms in the perturbation series by the resummation approach, which are absent in the case of fixed-order computation. This is also demonstrated by the analytic calculations using joint resummation in threshold for single jet production, and jet size. Therefore, this study shows the importance of final-state radiation modeled in Monte Carlo simulation to describe the data, and also implies that the differences between various parton showering and hadronization models are significant. |
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Compact Muon Solenoid LHC, CERN |