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| CMS-SMP-15-007 ; CERN-EP-2016-104 | ||
| Measurement of the double-differential inclusive jet cross section in proton-proton collisions at $ \sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| 14 May 2016 | ||
| Eur. Phys. J. C 76 (2016) 451 | ||
| Abstract: A measurement of the double-differential inclusive jet cross section as a function of jet transverse momentum $p_{\mathrm{T}}$ and absolute jet rapidity $|y|$ is presented. The analysis is based on proton-proton collisions collected by the CMS experiment at the LHC at a centre-of-mass energy of 13 TeV. The data samples correspond to integrated luminosities of 71 and 44 pb$^{-1}$ for $|y|< $ 3 and 3.2 $ <|y|< $ 4.7 , respectively. Jets are reconstructed with the anti-$k_{\mathrm{t}}$ clustering algorithm for two jet sizes, $R$, of 0.7 and 0.4, in a phase space region covering jet $p_{\mathrm{T}}$ up to 2 TeV and jet rapidity up to $|y|$ = 4.7. Predictions of perturbative quantum chromodynamics at next-to-leading order precision, complemented with electroweak and nonperturbative corrections, are used to compute the absolute scale and the shape of the inclusive jet cross section. The cross section difference in $R$, when going to a smaller jet size of 0.4, is best described by Monte Carlo event generators with next-to-leading order predictions matched to parton showering, hadronisation, and multiparton interactions. In the phase space accessible with the new data, this measurement provides a first indication that jet physics is as well understood at $ \sqrt{s} = $ 13 TeV as at smaller centre-of-mass energies. | ||
| Links: e-print arXiv:1605.04436 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; Rivet record ; HepData record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1-a:
Fits to the nonperturbative corrections obtained for inclusive AK7 jet cross sections as a function of jet $ {p_{\mathrm {T}}} $ for two rapidity bins: 0.5 $ < |y| < $ 1.0 (left) and 2.5 $ < |y| < $ 3.0 (right). The dotted lines represent the uncertainty bands, which are evaluated by fitting the envelopes of the predictions of the different generators used. |
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Figure 1-b:
Fits to the nonperturbative corrections obtained for inclusive AK7 jet cross sections as a function of jet $ {p_{\mathrm {T}}} $ for two rapidity bins: 0.5 $ < |y| < $ 1.0 (left) and 2.5 $ < |y| < $ 3.0 (right). The dotted lines represent the uncertainty bands, which are evaluated by fitting the envelopes of the predictions of the different generators used. |
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Figure 2-a:
Fits to the nonperturbative corrections obtained for inclusive AK4 jet cross sections as a function of jet $ {p_{\mathrm {T}}} $ for two rapidity bins: 0.5 $ < |y| < $ 1.0 (left) and 2.5 $ < |y| < $ 3.0 (right). The dotted lines represent the uncertainty bands, which are evaluated by fitting the envelopes of the predictions of the different generators used. |
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Figure 2-b:
Fits to the nonperturbative corrections obtained for inclusive AK4 jet cross sections as a function of jet $ {p_{\mathrm {T}}} $ for two rapidity bins: 0.5 $ < |y| < $ 1.0 (left) and 2.5 $ < |y| < $ 3.0 (right). The dotted lines represent the uncertainty bands, which are evaluated by fitting the envelopes of the predictions of the different generators used. |
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Figure 3-a:
Electroweak correction factors for the seven rapidity bins for the AK7 (left) and AK4 (right) jets as a function of jet $ {p_{\mathrm {T}}} $. |
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Figure 3-b:
Electroweak correction factors for the seven rapidity bins for the AK7 (left) and AK4 (right) jets as a function of jet $ {p_{\mathrm {T}}} $. |
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Figure 4-a:
Double-differential inclusive jet cross section as function of jet ${p_{\mathrm {T}}} $. On the left, data (points) and predictions from NLOJet++ based on the CT14 PDF set corrected for the NP and electroweak effects (line) are shown. On the right, data (points) and predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1 (line) are shown. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm ($R = $ 0.7). |
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Figure 4-b:
Double-differential inclusive jet cross section as function of jet ${p_{\mathrm {T}}} $. On the left, data (points) and predictions from NLOJet++ based on the CT14 PDF set corrected for the NP and electroweak effects (line) are shown. On the right, data (points) and predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1 (line) are shown. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm ($R = $ 0.7). |
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Figure 5-a:
Double-differential inclusive jet cross section as function of jet ${p_{\mathrm {T}}} $. On the left, data (points) and predictions from NLOJet++ based on the CT14 PDF set corrected for the NP and electroweak effects (line) are shown. On the right, data (points) and predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1 (line) are shown. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm ($R = $ 0.4 ). |
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Figure 5-b:
Double-differential inclusive jet cross section as function of jet ${p_{\mathrm {T}}} $. On the left, data (points) and predictions from NLOJet++ based on the CT14 PDF set corrected for the NP and electroweak effects (line) are shown. On the right, data (points) and predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1 (line) are shown. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm ($R = $ 0.4 ). |
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Figure 6-a:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 6-b:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 6-c:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 6-d:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 6-e:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 6-f:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 6-g:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-a:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-b:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-c:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-d:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-e:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-f:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 7-g:
Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 8-a:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 8-b:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 8-c:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 8-d:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 8-e:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 8-f:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 8-g:
Ratio of measured values to predictions from POWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for POWHEG, PYTHIA-8, and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 9-a:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 9-b:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
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Figure 9-c:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 9-d:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 9-e:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 9-f:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
png pdf |
Figure 9-g:
Ratio of measured values to predictions fromPOWHEG (PH) + PYTHIA-8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands forPOWHEG , PYTHIA-8 , and HERWIG++ (HPP), respectively. Jets are clustered with the anti-$ {k_{\mathrm {t}}}$ algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties. |
| Tables | |
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Table 1:
Trigger regions defined as ranges of the leading jet ${p_{\mathrm {T}}} $ in each event for all single-jet triggers used in the inclusive jet cross section measurement. |
| Summary |
|
A measurement of the double-differential cross section as a function of jet $ p_{\mathrm{T}} $italic and absolute rapidity $|y|$ is presented for two jet sizes $R= $ 0.4 and 0.7 using data from proton-proton collisions at $ \sqrt{s} = $ 13 TeV collected with the CMS detector. Data samples corresponding to integrated luminosities of 71 pb$^{-1}$ and 44 pb$^{-1}$ are used for absolute rapidities $|y|< $ 3 and for the forward region 3.2 $ <|y|< $ 4.7 , respectively. As expected for LO predictions, the MC event generators PYTHIA-8 and HERWIG++ exhibit significant discrepancies in absolute scale with respect to data, which are somewhat more pronounced for the case of HERWIG++. In contrast, the shape of the inclusive jet $ p_{\mathrm{T}} $ distribution is well described by HERWIG++ in all rapidity bins. Predictions from PYTHIA-8 start deviating from the observed shape as $|y|$ increases. In the comparison between data and predictions at NLO in perturbative QCD including corrections for nonperturbative and electroweak effects, it is observed that jet cross sections for the larger jet size of $R= $ 0.7 are accurately described, while for $R= $ 0.4 theory overestimates the cross section by 5-10% almost globally. In contrast, NLO predictions matched to parton showers as performed with POWHEG + PYTHIA-8 for two different tunes, perform equally well for both jet sizes. This result is consistent with the previous measurement performed at $ \sqrt{s} = $ 7 TeV [15], where it was observed that POWHEG + PYTHIA-8 correctly describes the $R$ dependence of the inclusive jet cross section, while fixed-order predictions at NLO were insufficient in that respect. This measurement is a first indication that jet physics is as well understood at $ \sqrt{s} = $ 13 TeV as at smaller centre-of-mass energies in the phase space accessible with the new data. |
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