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| CMS-JME-13-004 ; CERN-PH-EP-2015-305 | ||
| Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV | ||
| CMS Collaboration | ||
| 13 July 2016 | ||
| JINST 12 (2017) P02014 | ||
| Abstract: Improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 fb$^{-1}$ collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented. The corrections as a function of pseudorapidity $\eta$ and transverse momentum $p_{\mathrm{T}}$ are extracted from data and simulated events combining several channels and methods. They account successively for the effects of pileup, uniformity of the detector response, and residual data-simulation jet energy scale differences. Further corrections, depending on the jet flavor and distance parameter (jet size) $R$, are also presented. The jet energy resolution is measured in data and simulated events and is studied as a function of pileup, jet size, and jet flavor. Typical jet energy resolutions at the central rapidities are 15-20% at 30 GeV, about 10% at 100 GeV, and 5% at 1 TeV. The studies exploit events with dijet topology, as well as photon+jet, Z+jet and multijet events. Several new techniques are used to account for the various sources of jet energy scale corrections, and a full set of uncertainties, and their correlations, are provided.The final uncertainties on the jet energy scale are below 3% across the phase space considered by most analyses ($p_{\mathrm{T}}> $ 30 GeV and $| \eta| < $ 5.0). In the barrel region ($| \eta| < $ 1.3) an uncertainty below 1% for $p_{\mathrm{T}}> $ 30 GeV is reached, when excluding the jet flavor uncertainties, which are provided separately for different jet flavors. A new benchmark for jet energy scale determination at hadron colliders is achieved with 0.32% uncertainty for jets with $p_{\mathrm{T}}$ of the order of 165-330 GeV, and $| \eta| < $ 0.8. | ||
| Links: e-print arXiv:1607.03663 [hep-ex] (PDF) ; CDS record ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Ratio of measured jet $ {p_{\mathrm {T}}} $ to particle-level jet $p_{\rm T,ptcl}$ in QCD MC simulation at various stages of JEC: before any corrections (a), after pileup offset corrections (b), after all JEC (c). Here $\mu $ is the average number of pileup interactions per bunch crossing. |
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Figure 1-a:
Ratio of measured jet $ {p_{\mathrm {T}}} $ to particle-level jet $p_{\rm T,ptcl}$ in QCD MC simulation at various stages of JEC: before any corrections (a), after pileup offset corrections (b), after all JEC (c). Here $\mu $ is the average number of pileup interactions per bunch crossing. |
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Figure 1-b:
Ratio of measured jet $ {p_{\mathrm {T}}} $ to particle-level jet $p_{\rm T,ptcl}$ in QCD MC simulation at various stages of JEC: before any corrections (a), after pileup offset corrections (b), after all JEC (c). Here $\mu $ is the average number of pileup interactions per bunch crossing. |
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Figure 1-c:
Ratio of measured jet $ {p_{\mathrm {T}}} $ to particle-level jet $p_{\rm T,ptcl}$ in QCD MC simulation at various stages of JEC: before any corrections (a), after pileup offset corrections (b), after all JEC (c). Here $\mu $ is the average number of pileup interactions per bunch crossing. |
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Figure 2:
Consecutive stages of JEC, for data and MC simulation. All corrections marked with MC are derived from simulation studies, RC stands for random cone, and MJB refers to the analysis of multijet events. |
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Figure 3:
Comparison of data (circles) and Pythia6.4 simulation (histograms) for the distributions of the number of reconstructed primary vertices $N_{\rm PV}$ (a), and of the offset energy density $\rho $ (b). |
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Figure 3-a:
Comparison of data (circles) and Pythia6.4 simulation (histograms) for the distributions of the number of reconstructed primary vertices $N_{\rm PV}$ (a), and of the offset energy density $\rho $ (b). |
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Figure 3-b:
Comparison of data (circles) and Pythia6.4 simulation (histograms) for the distributions of the number of reconstructed primary vertices $N_{\rm PV}$ (a), and of the offset energy density $\rho $ (b). |
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Figure 4:
Mean of the number of good primary vertices per event, $< N_{\rm PV}> $ (a), and mean diffuse offset energy density, $< \rho > $ (ribght), versus the average number of pileup interactions per bunch crossing, $\mu $, for data (circles) and Pythia6.4 simulation (diamonds). |
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Figure 4-a:
Mean of the number of good primary vertices per event, $< N_{\rm PV}> $ (a), and mean diffuse offset energy density, $< \rho > $ (ribght), versus the average number of pileup interactions per bunch crossing, $\mu $, for data (circles) and Pythia6.4 simulation (diamonds). |
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Figure 4-b:
Mean of the number of good primary vertices per event, $< N_{\rm PV}> $ (a), and mean diffuse offset energy density, $< \rho > $ (ribght), versus the average number of pileup interactions per bunch crossing, $\mu $, for data (circles) and Pythia6.4 simulation (diamonds). |
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Figure 5:
Simulated particle-level offset $< p_{\rm T, offsetptcl}> $ defined in Eq.(3) (a), and residual offset after correcting for pileup with Eq.(2) (b) for $|\eta |< $ 1.3 , versus particle jet $ {p_{\mathrm {T}}} $, for different values of average number of pileup interactions per bunch crossing $< \mu > $. |
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Figure 5-a:
Simulated particle-level offset $< p_{\rm T, offsetptcl}> $ defined in Eq.(3) (a), and residual offset after correcting for pileup with Eq.(2) (b) for $|\eta |< $ 1.3 , versus particle jet $ {p_{\mathrm {T}}} $, for different values of average number of pileup interactions per bunch crossing $< \mu > $. |
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Figure 5-b:
Simulated particle-level offset $< p_{\rm T, offsetptcl}> $ defined in Eq.(3) (a), and residual offset after correcting for pileup with Eq.(2) (b) for $|\eta |< $ 1.3 , versus particle jet $ {p_{\mathrm {T}}} $, for different values of average number of pileup interactions per bunch crossing $< \mu > $. |
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Figure 6:
Simulated particle-level offset versus $ {p_{\mathrm {T}}} $ separately for each type of PF candidate (a). Average $ {p_{\mathrm {T}}} $ offset density versus jet distance parameter $R$ for various $p_{{\rm T},\rm ptcl}$ compared to a random-cone offset density versus cone radius (b). The jet or cone area $A_j$ corresponds to $\pi R^2$. |
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Figure 6-a:
Simulated particle-level offset versus $ {p_{\mathrm {T}}} $ separately for each type of PF candidate (a). Average $ {p_{\mathrm {T}}} $ offset density versus jet distance parameter $R$ for various $p_{{\rm T},\rm ptcl}$ compared to a random-cone offset density versus cone radius (b). The jet or cone area $A_j$ corresponds to $\pi R^2$. |
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Figure 6-b:
Simulated particle-level offset versus $ {p_{\mathrm {T}}} $ separately for each type of PF candidate (a). Average $ {p_{\mathrm {T}}} $ offset density versus jet distance parameter $R$ for various $p_{{\rm T},\rm ptcl}$ compared to a random-cone offset density versus cone radius (b). The jet or cone area $A_j$ corresponds to $\pi R^2$. |
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Figure 7:
Random-cone offset measured in data (markers) and MC simulation (histograms) normalized by the average number of pileup interactions $< \mu > $, separated by the type of PF candidate. The fraction labeled 'charged hadrons' is removed by CHS. The ratio of data over simulation, representing the scale factor applied for pileup offset in data, is also shown for PF and PF+CHS. |
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Figure 8:
Pileup offset correction uncertainties for the average 2012 (8 TeV) conditions for PF jets with CHS and $R= $ 0.5 as a function of $\eta _{\rm jet}$ for fixed $ {p_{\mathrm {T}}} = $ 30 GeV (a) and as a function of jet $ {p_{\mathrm {T}}} $ (b, and c,d panels). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh \eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. PileUpMuZero is an optional alternative uncertainty for zero-pileup ($< \mu > \approx$ 0) events, and it is therefore not included in the quadratic sum SubTotalPileUp. It accounts for the pileup uncertainty absorbed in the residual response corrections at $< \mu > \approx 20$, which is particularly prominent at 1.5 $ <|\eta |< $ 3. |
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Figure 8-a:
Pileup offset correction uncertainties for the average 2012 (8 TeV) conditions for PF jets with CHS and $R= $ 0.5 as a function of $\eta _{\rm jet}$ for fixed $ {p_{\mathrm {T}}} = $ 30 GeV (a) and as a function of jet $ {p_{\mathrm {T}}} $ (b, and c,d panels). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh \eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. PileUpMuZero is an optional alternative uncertainty for zero-pileup ($< \mu > \approx$ 0) events, and it is therefore not included in the quadratic sum SubTotalPileUp. It accounts for the pileup uncertainty absorbed in the residual response corrections at $< \mu > \approx 20$, which is particularly prominent at 1.5 $ <|\eta |< $ 3. |
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Figure 8-b:
Pileup offset correction uncertainties for the average 2012 (8 TeV) conditions for PF jets with CHS and $R= $ 0.5 as a function of $\eta _{\rm jet}$ for fixed $ {p_{\mathrm {T}}} = $ 30 GeV (a) and as a function of jet $ {p_{\mathrm {T}}} $ (b, and c,d panels). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh \eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. PileUpMuZero is an optional alternative uncertainty for zero-pileup ($< \mu > \approx$ 0) events, and it is therefore not included in the quadratic sum SubTotalPileUp. It accounts for the pileup uncertainty absorbed in the residual response corrections at $< \mu > \approx 20$, which is particularly prominent at 1.5 $ <|\eta |< $ 3. |
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Figure 8-c:
Pileup offset correction uncertainties for the average 2012 (8 TeV) conditions for PF jets with CHS and $R= $ 0.5 as a function of $\eta _{\rm jet}$ for fixed $ {p_{\mathrm {T}}} = $ 30 GeV (a) and as a function of jet $ {p_{\mathrm {T}}} $ (b, and c,d panels). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh \eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. PileUpMuZero is an optional alternative uncertainty for zero-pileup ($< \mu > \approx$ 0) events, and it is therefore not included in the quadratic sum SubTotalPileUp. It accounts for the pileup uncertainty absorbed in the residual response corrections at $< \mu > \approx 20$, which is particularly prominent at 1.5 $ <|\eta |< $ 3. |
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Figure 8-d:
Pileup offset correction uncertainties for the average 2012 (8 TeV) conditions for PF jets with CHS and $R= $ 0.5 as a function of $\eta _{\rm jet}$ for fixed $ {p_{\mathrm {T}}} = $ 30 GeV (a) and as a function of jet $ {p_{\mathrm {T}}} $ (b, and c,d panels). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh \eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. PileUpMuZero is an optional alternative uncertainty for zero-pileup ($< \mu > \approx$ 0) events, and it is therefore not included in the quadratic sum SubTotalPileUp. It accounts for the pileup uncertainty absorbed in the residual response corrections at $< \mu > \approx 20$, which is particularly prominent at 1.5 $ <|\eta |< $ 3. |
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Figure 9:
Pileup offset correction $C_{\rm hybrid}$ including data/MC scale factors, with systematic uncertainty band, for the average 2012 (8 TeV) conditions of $< \mu > = $ 20 for PF jets without CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (b), compared to corrections for 2010 [13] and 2011 [45] data at 7 TeV after extrapolation to similar pileup conditions. The same results are also shown for PF jets with CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $ {p_{\mathrm {T}}} $ (c), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (d), compared to corrections for 2011 data at 7 TeV [45]. |
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Figure 9-a:
Pileup offset correction $C_{\rm hybrid}$ including data/MC scale factors, with systematic uncertainty band, for the average 2012 (8 TeV) conditions of $< \mu > = $ 20 for PF jets without CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (b), compared to corrections for 2010 [13] and 2011 [45] data at 7 TeV after extrapolation to similar pileup conditions. The same results are also shown for PF jets with CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $ {p_{\mathrm {T}}} $ (c), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (d), compared to corrections for 2011 data at 7 TeV [45]. |
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Figure 9-b:
Pileup offset correction $C_{\rm hybrid}$ including data/MC scale factors, with systematic uncertainty band, for the average 2012 (8 TeV) conditions of $< \mu > = $ 20 for PF jets without CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (b), compared to corrections for 2010 [13] and 2011 [45] data at 7 TeV after extrapolation to similar pileup conditions. The same results are also shown for PF jets with CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $ {p_{\mathrm {T}}} $ (c), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (d), compared to corrections for 2011 data at 7 TeV [45]. |
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Figure 9-c:
Pileup offset correction $C_{\rm hybrid}$ including data/MC scale factors, with systematic uncertainty band, for the average 2012 (8 TeV) conditions of $< \mu > = $ 20 for PF jets without CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (b), compared to corrections for 2010 [13] and 2011 [45] data at 7 TeV after extrapolation to similar pileup conditions. The same results are also shown for PF jets with CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $ {p_{\mathrm {T}}} $ (c), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (d), compared to corrections for 2011 data at 7 TeV [45]. |
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Figure 9-d:
Pileup offset correction $C_{\rm hybrid}$ including data/MC scale factors, with systematic uncertainty band, for the average 2012 (8 TeV) conditions of $< \mu > = $ 20 for PF jets without CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (b), compared to corrections for 2010 [13] and 2011 [45] data at 7 TeV after extrapolation to similar pileup conditions. The same results are also shown for PF jets with CHS and $R= $ 0.5 at $|\eta |= $ 0 versus $ {p_{\mathrm {T}}} $ (c), and at $p_{{\rm T},\rm corr}= $ 30 GeV versus $|\eta |$ (d), compared to corrections for 2011 data at 7 TeV [45]. |
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Figure 10:
Simulated jet response $R_{\rm ptcl}$ versus $|\eta |$ for $R= $ 0.5 (a). Simulated jet response $R_{\rm ptcl}$, after JEC have been applied, versus $p_{\rm T, ptcl}$ for $R= $ 0.5 in various $\eta $ regions (b). |
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Figure 10-a:
Simulated jet response $R_{\rm ptcl}$ versus $|\eta |$ for $R= $ 0.5 (a). Simulated jet response $R_{\rm ptcl}$, after JEC have been applied, versus $p_{\rm T, ptcl}$ for $R= $ 0.5 in various $\eta $ regions (b). |
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Figure 10-b:
Simulated jet response $R_{\rm ptcl}$ versus $|\eta |$ for $R= $ 0.5 (a). Simulated jet response $R_{\rm ptcl}$, after JEC have been applied, versus $p_{\rm T, ptcl}$ for $R= $ 0.5 in various $\eta $ regions (b). |
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Figure 11:
Jet energy correction factors for a jet with $ {p_{\mathrm {T}}} = $ 30 GeV, as a function of $\eta $ and for various jet sizes $R$ (a). Simulated jet energy response $R_{\rm ptcl}$ after JEC for $|\eta |< $ 1.3 as a function of the jet $ {p_{\mathrm {T}}} $ for various jet sizes $R$ (b). |
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Figure 11-a:
Jet energy correction factors for a jet with $ {p_{\mathrm {T}}} = $ 30 GeV, as a function of $\eta $ and for various jet sizes $R$ (a). Simulated jet energy response $R_{\rm ptcl}$ after JEC for $|\eta |< $ 1.3 as a function of the jet $ {p_{\mathrm {T}}} $ for various jet sizes $R$ (b). |
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Figure 11-b:
Jet energy correction factors for a jet with $ {p_{\mathrm {T}}} = $ 30 GeV, as a function of $\eta $ and for various jet sizes $R$ (a). Simulated jet energy response $R_{\rm ptcl}$ after JEC for $|\eta |< $ 1.3 as a function of the jet $ {p_{\mathrm {T}}} $ for various jet sizes $R$ (b). |
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Figure 12:
Changes in PF jet and calorimeter jet response resulting from $\pm$3% variations of single-pion response in parameterized fast simulation in HCAL+ECAL. |
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Figure 13:
Changes in PF jet and calorimeter jet response resulting from $\pm$3% variations of single-pion response in parameterized fast simulation in ECAL (a), and HCAL (b). |
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Figure 13-a:
Changes in PF jet and calorimeter jet response resulting from $\pm$3% variations of single-pion response in parameterized fast simulation in ECAL (a), and HCAL (b). |
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Figure 13-b:
Changes in PF jet and calorimeter jet response resulting from $\pm$3% variations of single-pion response in parameterized fast simulation in ECAL (a), and HCAL (b). |
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Figure 14:
Response correction factors with their systematic uncertainty band from simulation for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and as a function of $|\eta |$ at $p_{\rm T, corr}= $ 30 GeV (b), $p_{\rm T, corr}= $ 100 GeV (c) and $p_{\rm T, corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking periods. |
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Figure 14-a:
Response correction factors with their systematic uncertainty band from simulation for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and as a function of $|\eta |$ at $p_{\rm T, corr}= $ 30 GeV (b), $p_{\rm T, corr}= $ 100 GeV (c) and $p_{\rm T, corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking periods. |
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Figure 14-b:
Response correction factors with their systematic uncertainty band from simulation for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and as a function of $|\eta |$ at $p_{\rm T, corr}= $ 30 GeV (b), $p_{\rm T, corr}= $ 100 GeV (c) and $p_{\rm T, corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking periods. |
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Figure 14-c:
Response correction factors with their systematic uncertainty band from simulation for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and as a function of $|\eta |$ at $p_{\rm T, corr}= $ 30 GeV (b), $p_{\rm T, corr}= $ 100 GeV (c) and $p_{\rm T, corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking periods. |
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Figure 14-d:
Response correction factors with their systematic uncertainty band from simulation for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{\rm T, corr}$ (a), and as a function of $|\eta |$ at $p_{\rm T, corr}= $ 30 GeV (b), $p_{\rm T, corr}= $ 100 GeV (c) and $p_{\rm T, corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking periods. |
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Figure 15:
Relative energy scale correction for $ {p_{\mathrm {T}}} = $ 60 , 120, 240 and 480 GeV as a function of $|\eta |$. The residual corrections increase toward high rapidity and low $ {p_{\mathrm {T}}} $, where effects from nonlinear calorimeter response become more important. The curves are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh \eta = $ 4000 GeV (corresponding to $\eta \approx 2.8$ for a jet with $ {p_{\mathrm {T}}} = $ 480 GeV) so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. The statistical uncertainty associated with a constant fit versus $ {p_{\mathrm {T}}} $ is shown for $ {p_{\mathrm {T}}} = $ 120 GeV (markers). |
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Figure 16:
The $k_{\rm FSR}(\alpha =0.2)$ correction factor (defined in Eq.(14)) plotted vs. $|\eta |$ (a). This ratio is used for ISR+FSR corrections that are applied to dijet events with $\alpha < $ 0.2 , for the MPF and $ {p_{\mathrm {T}}} $-balance methods, and for Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C. The points are fitted with $f(\eta) = p_0 + {p_1 \cosh \eta}/{( 1 + p_2 \cosh \eta )}$ as in Ref. [13]. Relative $\eta $ corrections obtained with the MPF and balance methods and the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C MC generators (b). The results are shown after corrections for ISR+FSR, and compared to the central values, obtained with the MPF method and Pythia6.4 tune Z2* simulated events. |
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Figure 16-a:
The $k_{\rm FSR}(\alpha =0.2)$ correction factor (defined in Eq.(14)) plotted vs. $|\eta |$ (a). This ratio is used for ISR+FSR corrections that are applied to dijet events with $\alpha < $ 0.2 , for the MPF and $ {p_{\mathrm {T}}} $-balance methods, and for Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C. The points are fitted with $f(\eta) = p_0 + {p_1 \cosh \eta}/{( 1 + p_2 \cosh \eta )}$ as in Ref. [13]. Relative $\eta $ corrections obtained with the MPF and balance methods and the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C MC generators (b). The results are shown after corrections for ISR+FSR, and compared to the central values, obtained with the MPF method and Pythia6.4 tune Z2* simulated events. |
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Figure 16-b:
The $k_{\rm FSR}(\alpha =0.2)$ correction factor (defined in Eq.(14)) plotted vs. $|\eta |$ (a). This ratio is used for ISR+FSR corrections that are applied to dijet events with $\alpha < $ 0.2 , for the MPF and $ {p_{\mathrm {T}}} $-balance methods, and for Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C. The points are fitted with $f(\eta) = p_0 + {p_1 \cosh \eta}/{( 1 + p_2 \cosh \eta )}$ as in Ref. [13]. Relative $\eta $ corrections obtained with the MPF and balance methods and the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C MC generators (b). The results are shown after corrections for ISR+FSR, and compared to the central values, obtained with the MPF method and Pythia6.4 tune Z2* simulated events. |
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Figure 17:
Relative $\eta $ correction factor at the crossover $\bar{p}_{\rm T}$ (defined as the value of $ {p_{\mathrm {T}}} $ where the log-linear and constant fits versus $p_{\rm T, ave}$ agree) value, and at half and twice the $\bar{p}_{\rm T}$ values (a). The statistical uncertainty in the constant fit at each value of $\bar{p}_{\rm T}$ is also shown. Distribution of the $ {p_{\mathrm {T}}} $ and $\eta $ bins used in the dijet balance measurement, with a point at the average $ {p_{\mathrm {T}}} $ and $\eta $ for each bin (b). The horizontal red lines indicate the crossover $\bar{p}_{\rm T}$ value for each bin. |
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Figure 17-a:
Relative $\eta $ correction factor at the crossover $\bar{p}_{\rm T}$ (defined as the value of $ {p_{\mathrm {T}}} $ where the log-linear and constant fits versus $p_{\rm T, ave}$ agree) value, and at half and twice the $\bar{p}_{\rm T}$ values (a). The statistical uncertainty in the constant fit at each value of $\bar{p}_{\rm T}$ is also shown. Distribution of the $ {p_{\mathrm {T}}} $ and $\eta $ bins used in the dijet balance measurement, with a point at the average $ {p_{\mathrm {T}}} $ and $\eta $ for each bin (b). The horizontal red lines indicate the crossover $\bar{p}_{\rm T}$ value for each bin. |
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Figure 17-b:
Relative $\eta $ correction factor at the crossover $\bar{p}_{\rm T}$ (defined as the value of $ {p_{\mathrm {T}}} $ where the log-linear and constant fits versus $p_{\rm T, ave}$ agree) value, and at half and twice the $\bar{p}_{\rm T}$ values (a). The statistical uncertainty in the constant fit at each value of $\bar{p}_{\rm T}$ is also shown. Distribution of the $ {p_{\mathrm {T}}} $ and $\eta $ bins used in the dijet balance measurement, with a point at the average $ {p_{\mathrm {T}}} $ and $\eta $ for each bin (b). The horizontal red lines indicate the crossover $\bar{p}_{\rm T}$ value for each bin. |
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Figure 18:
Systematic uncertainties for the relative $\eta $-dependent corrections as a function of jet $ {p_{\mathrm {T}}} $ (a) and as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (b) and for jets with $ {p_{\mathrm {T}}} = $ 100 GeV (c). Time-dependent uncertainties as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. SubTotalRelative is the quadratic sum of RelativePt, RelativeJER, RelativeFSR and RelativeStat. |
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Figure 18-a:
Systematic uncertainties for the relative $\eta $-dependent corrections as a function of jet $ {p_{\mathrm {T}}} $ (a) and as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (b) and for jets with $ {p_{\mathrm {T}}} = $ 100 GeV (c). Time-dependent uncertainties as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. SubTotalRelative is the quadratic sum of RelativePt, RelativeJER, RelativeFSR and RelativeStat. |
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Figure 18-b:
Systematic uncertainties for the relative $\eta $-dependent corrections as a function of jet $ {p_{\mathrm {T}}} $ (a) and as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (b) and for jets with $ {p_{\mathrm {T}}} = $ 100 GeV (c). Time-dependent uncertainties as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. SubTotalRelative is the quadratic sum of RelativePt, RelativeJER, RelativeFSR and RelativeStat. |
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Figure 18-c:
Systematic uncertainties for the relative $\eta $-dependent corrections as a function of jet $ {p_{\mathrm {T}}} $ (a) and as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (b) and for jets with $ {p_{\mathrm {T}}} = $ 100 GeV (c). Time-dependent uncertainties as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. SubTotalRelative is the quadratic sum of RelativePt, RelativeJER, RelativeFSR and RelativeStat. |
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Figure 18-d:
Systematic uncertainties for the relative $\eta $-dependent corrections as a function of jet $ {p_{\mathrm {T}}} $ (a) and as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (b) and for jets with $ {p_{\mathrm {T}}} = $ 100 GeV (c). Time-dependent uncertainties as a function of jet $\eta $ for jets with $ {p_{\mathrm {T}}} = $ 30 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only uncertainties for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. SubTotalRelative is the quadratic sum of RelativePt, RelativeJER, RelativeFSR and RelativeStat. |
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Figure 19:
Jet response obtained with the $ {p_{\mathrm {T}}} $-balance and MPF methods in Z+jet events (points), for both data and simulation ({\sc Madgraph}4+Pythia6.4 tune Z2*), plotted as a function of $\alpha =p_{\rm T,2ndjet}/p_{\rm T,Z}$ (top). The response in data is scaled by a factor of 1.02, constant as a function of $ {p_{\mathrm {T}}} $. A fit to a first-order polynomial (dashed lines) is shown, together with the statistical uncertainty from the fit (shaded bands). Only events with $p_{\rm T, Z}> $ 30 GeV and $|\eta _{\rm jet}|< $ 1.3 are considered. The ratio of the jet response from the $ {p_{\mathrm {T}}} $-balance and MPF methods in data and simulation shown in the bottom panel. The simulated jet response $p_{\rm T,jet}/p_{\rm T,ptcl}$ is higher than unity because the jets are corrected with JEC from QCD dijet events with lower jet response than Z+jet events due to higher gluon fraction and larger underlying event. |
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Figure 20:
Relative resolution (blue scale) in the plane of mean number of pileup events ($\mu $) and Z boson transverse momentum ($p_{\rm T, Z}$) for the MPF balance (a) and $ {p_{\mathrm {T}}} $-balance methods (b). |
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Figure 20-a:
Relative resolution (blue scale) in the plane of mean number of pileup events ($\mu $) and Z boson transverse momentum ($p_{\rm T, Z}$) for the MPF balance (a) and $ {p_{\mathrm {T}}} $-balance methods (b). |
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Figure 20-b:
Relative resolution (blue scale) in the plane of mean number of pileup events ($\mu $) and Z boson transverse momentum ($p_{\rm T, Z}$) for the MPF balance (a) and $ {p_{\mathrm {T}}} $-balance methods (b). |
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Figure 21:
Comparison of jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples as a function of Z boson or photon $ {p_{\mathrm {T}}} $. The jet response from the MPF method (a,b) and the $ {p_{\mathrm {T}}} $-balance method (c,d) is shown as a function of Z and $\gamma $ $ {p_{\mathrm {T}}} $ for data (a,c) and simulation (b,d). The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, explaining the low MPF response in both data and simulation. The footprint effect is absent for muons and corrected for photons. |
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Figure 21-a:
Comparison of jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples as a function of Z boson or photon $ {p_{\mathrm {T}}} $. The jet response from the MPF method (a,b) and the $ {p_{\mathrm {T}}} $-balance method (c,d) is shown as a function of Z and $\gamma $ $ {p_{\mathrm {T}}} $ for data (a,c) and simulation (b,d). The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, explaining the low MPF response in both data and simulation. The footprint effect is absent for muons and corrected for photons. |
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Figure 21-b:
Comparison of jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples as a function of Z boson or photon $ {p_{\mathrm {T}}} $. The jet response from the MPF method (a,b) and the $ {p_{\mathrm {T}}} $-balance method (c,d) is shown as a function of Z and $\gamma $ $ {p_{\mathrm {T}}} $ for data (a,c) and simulation (b,d). The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, explaining the low MPF response in both data and simulation. The footprint effect is absent for muons and corrected for photons. |
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Figure 21-c:
Comparison of jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples as a function of Z boson or photon $ {p_{\mathrm {T}}} $. The jet response from the MPF method (a,b) and the $ {p_{\mathrm {T}}} $-balance method (c,d) is shown as a function of Z and $\gamma $ $ {p_{\mathrm {T}}} $ for data (a,c) and simulation (b,d). The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, explaining the low MPF response in both data and simulation. The footprint effect is absent for muons and corrected for photons. |
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Figure 21-d:
Comparison of jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples as a function of Z boson or photon $ {p_{\mathrm {T}}} $. The jet response from the MPF method (a,b) and the $ {p_{\mathrm {T}}} $-balance method (c,d) is shown as a function of Z and $\gamma $ $ {p_{\mathrm {T}}} $ for data (a,c) and simulation (b,d). The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, explaining the low MPF response in both data and simulation. The footprint effect is absent for muons and corrected for photons. |
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Figure 22:
Ratio of the jet response measurement obtained from data and simulation with the MPF method (a) and $ {p_{\mathrm {T}}} $-balance method (b). Results are shown for the $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples. The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet\ sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, but the effect cancels out in the ratio of data over simulation. |
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Figure 22-a:
Ratio of the jet response measurement obtained from data and simulation with the MPF method (a) and $ {p_{\mathrm {T}}} $-balance method (b). Results are shown for the $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples. The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet\ sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, but the effect cancels out in the ratio of data over simulation. |
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Figure 22-b:
Ratio of the jet response measurement obtained from data and simulation with the MPF method (a) and $ {p_{\mathrm {T}}} $-balance method (b). Results are shown for the $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, and $\gamma $+jet samples. The $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet\ sample has not been corrected for the electron EM footprint in ${\vec{p}_{\mathrm {T}}^{\, \text {miss}}} $, but the effect cancels out in the ratio of data over simulation. |
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Figure 23:
$C_{\rm recoil}$ ratio of the effective jet $ {p_{\mathrm {T}}} $ of jets in the recoil over the total recoil $ {p_{\mathrm {T}}} $, (Eq.(23)), calculated with recoil jets of $ {p_{\mathrm {T}}} > $ 30 GeV (for MJB) and $ {p_{\mathrm {T}}} > $ 10 GeV (for MPF) in data and MC simulation (a). Multijet balance response calculated with the MJB and MPF methods for data and MC simulation (b). The filled bands show the total (statistical and systematic) uncertainty on MC and the error bars the statistical uncertainty on data. |
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Figure 23-a:
$C_{\rm recoil}$ ratio of the effective jet $ {p_{\mathrm {T}}} $ of jets in the recoil over the total recoil $ {p_{\mathrm {T}}} $, (Eq.(23)), calculated with recoil jets of $ {p_{\mathrm {T}}} > $ 30 GeV (for MJB) and $ {p_{\mathrm {T}}} > $ 10 GeV (for MPF) in data and MC simulation (a). Multijet balance response calculated with the MJB and MPF methods for data and MC simulation (b). The filled bands show the total (statistical and systematic) uncertainty on MC and the error bars the statistical uncertainty on data. |
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Figure 23-b:
$C_{\rm recoil}$ ratio of the effective jet $ {p_{\mathrm {T}}} $ of jets in the recoil over the total recoil $ {p_{\mathrm {T}}} $, (Eq.(23)), calculated with recoil jets of $ {p_{\mathrm {T}}} > $ 30 GeV (for MJB) and $ {p_{\mathrm {T}}} > $ 10 GeV (for MPF) in data and MC simulation (a). Multijet balance response calculated with the MJB and MPF methods for data and MC simulation (b). The filled bands show the total (statistical and systematic) uncertainty on MC and the error bars the statistical uncertainty on data. |
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Figure 24:
Comparison of the data-to-simulation ratio of the jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, $\gamma $+jet, and multijet samples after applying the corrections for JES and ISR+FSR (a) and after applying, in addition, the nuisance parameter values found by the global fit (b). The uncertainty in the ratio, excluding jet-flavor and time-dependent effects, is shown by the shaded region. The solid line shows the global fit central value and the dotted curves the statistical uncertainty of the fit. As the multijet analysis connects the jet energy scale of jets in two different $ {p_{\mathrm {T}}} $ ranges (Eq.(24)), it can be used to constrain one given the other or vice versa: the two sets of points are relative to the two approaches. |
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Figure 24-a:
Comparison of the data-to-simulation ratio of the jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, $\gamma $+jet, and multijet samples after applying the corrections for JES and ISR+FSR (a) and after applying, in addition, the nuisance parameter values found by the global fit (b). The uncertainty in the ratio, excluding jet-flavor and time-dependent effects, is shown by the shaded region. The solid line shows the global fit central value and the dotted curves the statistical uncertainty of the fit. As the multijet analysis connects the jet energy scale of jets in two different $ {p_{\mathrm {T}}} $ ranges (Eq.(24)), it can be used to constrain one given the other or vice versa: the two sets of points are relative to the two approaches. |
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Figure 24-b:
Comparison of the data-to-simulation ratio of the jet response measurements from $ \mathrm{ Z } (\to \mu \mu)$+jet, $ \mathrm{ Z } (\to \mathrm{ e } \mathrm{ e })$+jet, $\gamma $+jet, and multijet samples after applying the corrections for JES and ISR+FSR (a) and after applying, in addition, the nuisance parameter values found by the global fit (b). The uncertainty in the ratio, excluding jet-flavor and time-dependent effects, is shown by the shaded region. The solid line shows the global fit central value and the dotted curves the statistical uncertainty of the fit. As the multijet analysis connects the jet energy scale of jets in two different $ {p_{\mathrm {T}}} $ ranges (Eq.(24)), it can be used to constrain one given the other or vice versa: the two sets of points are relative to the two approaches. |
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Figure 25:
Central value of the data-to-simulation ratio of ${\rm d}R/{\rm d}\alpha _{\rm max}$, and its 68% probability region, as a function of jet $ {p_{\mathrm {T}}} $, for the $ {p_{\mathrm {T}}} $-balance (a) and MPF (b) methods. The ${\rm d}R/{\rm d}\alpha _{\rm max}$ is the derivative of the jet response evaluated in events with $\alpha <\alpha _{\rm max}$. The y-axis scale for the MPF method is zoomed by ${\times } 4$ compared to the $ {p_{\mathrm {T}}} $-balance method, demonstrating the much smaller initial ISR+FSR uncertainty for this method. The shadowed regions show the input distributions to the global fit, while the full color regions show the post-fit distributions. The uncertainties on ${\rm d}R/{\rm d}\alpha _{\rm max}$ before the global fit are labeled 'In', and the uncertainties constrained by the global fit are labeled 'Out'. |
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Figure 25-a:
Central value of the data-to-simulation ratio of ${\rm d}R/{\rm d}\alpha _{\rm max}$, and its 68% probability region, as a function of jet $ {p_{\mathrm {T}}} $, for the $ {p_{\mathrm {T}}} $-balance (a) and MPF (b) methods. The ${\rm d}R/{\rm d}\alpha _{\rm max}$ is the derivative of the jet response evaluated in events with $\alpha <\alpha _{\rm max}$. The y-axis scale for the MPF method is zoomed by ${\times } 4$ compared to the $ {p_{\mathrm {T}}} $-balance method, demonstrating the much smaller initial ISR+FSR uncertainty for this method. The shadowed regions show the input distributions to the global fit, while the full color regions show the post-fit distributions. The uncertainties on ${\rm d}R/{\rm d}\alpha _{\rm max}$ before the global fit are labeled 'In', and the uncertainties constrained by the global fit are labeled 'Out'. |
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Figure 25-b:
Central value of the data-to-simulation ratio of ${\rm d}R/{\rm d}\alpha _{\rm max}$, and its 68% probability region, as a function of jet $ {p_{\mathrm {T}}} $, for the $ {p_{\mathrm {T}}} $-balance (a) and MPF (b) methods. The ${\rm d}R/{\rm d}\alpha _{\rm max}$ is the derivative of the jet response evaluated in events with $\alpha <\alpha _{\rm max}$. The y-axis scale for the MPF method is zoomed by ${\times } 4$ compared to the $ {p_{\mathrm {T}}} $-balance method, demonstrating the much smaller initial ISR+FSR uncertainty for this method. The shadowed regions show the input distributions to the global fit, while the full color regions show the post-fit distributions. The uncertainties on ${\rm d}R/{\rm d}\alpha _{\rm max}$ before the global fit are labeled 'In', and the uncertainties constrained by the global fit are labeled 'Out'. |
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Figure 26:
Absolute scale time-dependent uncertainty as a function of jet $ {p_{\mathrm {T}}} $ for various data-taking periods (a). Systematic uncertainties for the absolute jet scale as a function of $ {p_{\mathrm {T}}} $ (b). SubTotalAbsolute is the quadratic sum of AbsoluteScale, AbsoluteStat, Fragmentation, SinglePionECAL, SinglePionHCAL and MPFBias. |
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Figure 26-a:
Absolute scale time-dependent uncertainty as a function of jet $ {p_{\mathrm {T}}} $ for various data-taking periods (a). Systematic uncertainties for the absolute jet scale as a function of $ {p_{\mathrm {T}}} $ (b). SubTotalAbsolute is the quadratic sum of AbsoluteScale, AbsoluteStat, Fragmentation, SinglePionECAL, SinglePionHCAL and MPFBias. |
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Figure 26-b:
Absolute scale time-dependent uncertainty as a function of jet $ {p_{\mathrm {T}}} $ for various data-taking periods (a). Systematic uncertainties for the absolute jet scale as a function of $ {p_{\mathrm {T}}} $ (b). SubTotalAbsolute is the quadratic sum of AbsoluteScale, AbsoluteStat, Fragmentation, SinglePionECAL, SinglePionHCAL and MPFBias. |
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Figure 27:
Residual data/simulation response correction factors for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{{\rm T},\rm corr}$ (a), and as a function of $|\eta |$ for $p_{{\rm T},\rm corr}= $ 30 GeV (b), $p_{{\rm T},\rm corr}= $ 100 GeV (c), and $p_{{\rm T}, \rm corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
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Figure 27-a:
Residual data/simulation response correction factors for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{{\rm T},\rm corr}$ (a), and as a function of $|\eta |$ for $p_{{\rm T},\rm corr}= $ 30 GeV (b), $p_{{\rm T},\rm corr}= $ 100 GeV (c), and $p_{{\rm T}, \rm corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
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Figure 27-b:
Residual data/simulation response correction factors for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{{\rm T},\rm corr}$ (a), and as a function of $|\eta |$ for $p_{{\rm T},\rm corr}= $ 30 GeV (b), $p_{{\rm T},\rm corr}= $ 100 GeV (c), and $p_{{\rm T}, \rm corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
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Figure 27-c:
Residual data/simulation response correction factors for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{{\rm T},\rm corr}$ (a), and as a function of $|\eta |$ for $p_{{\rm T},\rm corr}= $ 30 GeV (b), $p_{{\rm T},\rm corr}= $ 100 GeV (c), and $p_{{\rm T}, \rm corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
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Figure 27-d:
Residual data/simulation response correction factors for the 2012 data collected at 8 TeV for PF jets with CHS and $R= $ 0.5 , compared to corrections at 7 TeV corresponding to 36 pb$^{-1}$ of data taken in 2010 [13] and 5 fb$^{-1}$ taken in 2011 [45]. The comparison is shown at $|\eta |= $ 0 versus $p_{{\rm T},\rm corr}$ (a), and as a function of $|\eta |$ for $p_{{\rm T},\rm corr}= $ 30 GeV (b), $p_{{\rm T},\rm corr}= $ 100 GeV (c), and $p_{{\rm T}, \rm corr}= $ 1000 GeV (d). The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 3500 GeV so as to show only correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
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Figure 28:
Jet-flavor fractions in the physics (Ph) and algorithmic (Al) flavor definitions for QCD dijet (a), Z+jet (b), and $\gamma $+jet (c) samples. As explained in Section 6, the variable $\alpha =p_{\rm T, 3rdjet}/p_{\rm T, ave}$ for dijet events and $\alpha =p_{\rm T, 2ndjet}/p_{{\rm T}, \gamma /{\rm Z}}$ for Z+jet and $\gamma +$jet events. |
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Figure 28-a:
Jet-flavor fractions in the physics (Ph) and algorithmic (Al) flavor definitions for QCD dijet (a), Z+jet (b), and $\gamma $+jet (c) samples. As explained in Section 6, the variable $\alpha =p_{\rm T, 3rdjet}/p_{\rm T, ave}$ for dijet events and $\alpha =p_{\rm T, 2ndjet}/p_{{\rm T}, \gamma /{\rm Z}}$ for Z+jet and $\gamma +$jet events. |
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Figure 28-b:
Jet-flavor fractions in the physics (Ph) and algorithmic (Al) flavor definitions for QCD dijet (a), Z+jet (b), and $\gamma $+jet (c) samples. As explained in Section 6, the variable $\alpha =p_{\rm T, 3rdjet}/p_{\rm T, ave}$ for dijet events and $\alpha =p_{\rm T, 2ndjet}/p_{{\rm T}, \gamma /{\rm Z}}$ for Z+jet and $\gamma +$jet events. |
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Figure 28-c:
Jet-flavor fractions in the physics (Ph) and algorithmic (Al) flavor definitions for QCD dijet (a), Z+jet (b), and $\gamma $+jet (c) samples. As explained in Section 6, the variable $\alpha =p_{\rm T, 3rdjet}/p_{\rm T, ave}$ for dijet events and $\alpha =p_{\rm T, 2ndjet}/p_{{\rm T}, \gamma /{\rm Z}}$ for Z+jet and $\gamma +$jet events. |
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Figure 29:
Comparison of jet response (a) and simulated composition (b) for different flavors of leading jets in Z+jet events with 50 $ < {p_{\mathrm {T}}} ^Z< $ 70 GeV, $|\eta _{\rm jet}|< $ 1.3 , and $\alpha = $ 0.3 (defined in Eq.(16)). The response values are compared for Pythia6.4 and Herwig++2.3, the composition is from Pythia6.4. |
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Figure 29-a:
Comparison of jet response (a) and simulated composition (b) for different flavors of leading jets in Z+jet events with 50 $ < {p_{\mathrm {T}}} ^Z< $ 70 GeV, $|\eta _{\rm jet}|< $ 1.3 , and $\alpha = $ 0.3 (defined in Eq.(16)). The response values are compared for Pythia6.4 and Herwig++2.3, the composition is from Pythia6.4. |
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Figure 29-b:
Comparison of jet response (a) and simulated composition (b) for different flavors of leading jets in Z+jet events with 50 $ < {p_{\mathrm {T}}} ^Z< $ 70 GeV, $|\eta _{\rm jet}|< $ 1.3 , and $\alpha = $ 0.3 (defined in Eq.(16)). The response values are compared for Pythia6.4 and Herwig++2.3, the composition is from Pythia6.4. |
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Figure 30:
Residual jet-flavor correction factor as a function of jet $p_{\rm T,corr}$ from Pythia6.4 tune Z2*, derived on top of inclusive JEC and defined relative to the QCD flavor mixture (a). The neutrinos are excluded from particle jets, which brings c- and b-jet response in between that of light quarks and gluons. The lines show the parameterizations used for residual jet-flavor corrections. Difference in light-quark and gluon jet response as a function of jet $p_{\rm T,corr}$, as predicted by Pythia6.4 and Herwig++2.3 (b). |
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Figure 30-a:
Residual jet-flavor correction factor as a function of jet $p_{\rm T,corr}$ from Pythia6.4 tune Z2*, derived on top of inclusive JEC and defined relative to the QCD flavor mixture (a). The neutrinos are excluded from particle jets, which brings c- and b-jet response in between that of light quarks and gluons. The lines show the parameterizations used for residual jet-flavor corrections. Difference in light-quark and gluon jet response as a function of jet $p_{\rm T,corr}$, as predicted by Pythia6.4 and Herwig++2.3 (b). |
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Figure 30-b:
Residual jet-flavor correction factor as a function of jet $p_{\rm T,corr}$ from Pythia6.4 tune Z2*, derived on top of inclusive JEC and defined relative to the QCD flavor mixture (a). The neutrinos are excluded from particle jets, which brings c- and b-jet response in between that of light quarks and gluons. The lines show the parameterizations used for residual jet-flavor corrections. Difference in light-quark and gluon jet response as a function of jet $p_{\rm T,corr}$, as predicted by Pythia6.4 and Herwig++2.3 (b). |
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Figure 31:
a: Ratio of jet responses in Pythia6.4 (tune Z2*) and Herwig++2.3 (tune EE3C) versus jet $ {p_{\mathrm {T}}} $, for pure jet flavors selected using the physics definition, where the shaded envelope highlights the largest differences observed for the gluon jets. b: Pythia6.4/Herwig++2.3 response differences as a function of jet $ {p_{\mathrm {T}}} $ for QCD dijet and Z/$\gamma $+jet flavor mixtures calculated from the parameterized flavor response differences and compared to the full simulation for dijet and Z+jet samples. The ``20% glue'' corresponds to the effective Z/$\gamma $+jet flavor mixture at $ {p_{\mathrm {T}}} = $ 200 GeV, which has 20% of gluons. |
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Figure 31-a:
a: Ratio of jet responses in Pythia6.4 (tune Z2*) and Herwig++2.3 (tune EE3C) versus jet $ {p_{\mathrm {T}}} $, for pure jet flavors selected using the physics definition, where the shaded envelope highlights the largest differences observed for the gluon jets. b: Pythia6.4/Herwig++2.3 response differences as a function of jet $ {p_{\mathrm {T}}} $ for QCD dijet and Z/$\gamma $+jet flavor mixtures calculated from the parameterized flavor response differences and compared to the full simulation for dijet and Z+jet samples. The ``20% glue'' corresponds to the effective Z/$\gamma $+jet flavor mixture at $ {p_{\mathrm {T}}} = $ 200 GeV, which has 20% of gluons. |
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Figure 31-b:
a: Ratio of jet responses in Pythia6.4 (tune Z2*) and Herwig++2.3 (tune EE3C) versus jet $ {p_{\mathrm {T}}} $, for pure jet flavors selected using the physics definition, where the shaded envelope highlights the largest differences observed for the gluon jets. b: Pythia6.4/Herwig++2.3 response differences as a function of jet $ {p_{\mathrm {T}}} $ for QCD dijet and Z/$\gamma $+jet flavor mixtures calculated from the parameterized flavor response differences and compared to the full simulation for dijet and Z+jet samples. The ``20% glue'' corresponds to the effective Z/$\gamma $+jet flavor mixture at $ {p_{\mathrm {T}}} = $ 200 GeV, which has 20% of gluons. |
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Figure 32:
Systematic uncertainties in jet energy corrections for various flavor mixtures (QCD dijets, Z+jet and $\gamma $+jet) and pure flavors (gluons, light quarks and bottom quarks) as a function of jet $ {p_{\mathrm {T}}} $ (a,c, for fixed $|\eta _{\rm jet}|= $ 0 , a,b, and $|\eta _{\rm jet}|= $ 2.7 , c,d) and $\eta _{\rm jet}$ (b,d, for fixed $ {p_{\mathrm {T}}} = $ 30 GeV, a,b, and 100 GeV , c,d). The sign of the systematic source indicates the sign of the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C difference. The shaded band shows gluon flavor response uncertainty symmetrically around zero. |
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Figure 32-a:
Systematic uncertainties in jet energy corrections for various flavor mixtures (QCD dijets, Z+jet and $\gamma $+jet) and pure flavors (gluons, light quarks and bottom quarks) as a function of jet $ {p_{\mathrm {T}}} $ (a,c, for fixed $|\eta _{\rm jet}|= $ 0 , a,b, and $|\eta _{\rm jet}|= $ 2.7 , c,d) and $\eta _{\rm jet}$ (b,d, for fixed $ {p_{\mathrm {T}}} = $ 30 GeV, a,b, and 100 GeV , c,d). The sign of the systematic source indicates the sign of the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C difference. The shaded band shows gluon flavor response uncertainty symmetrically around zero. |
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Figure 32-b:
Systematic uncertainties in jet energy corrections for various flavor mixtures (QCD dijets, Z+jet and $\gamma $+jet) and pure flavors (gluons, light quarks and bottom quarks) as a function of jet $ {p_{\mathrm {T}}} $ (a,c, for fixed $|\eta _{\rm jet}|= $ 0 , a,b, and $|\eta _{\rm jet}|= $ 2.7 , c,d) and $\eta _{\rm jet}$ (b,d, for fixed $ {p_{\mathrm {T}}} = $ 30 GeV, a,b, and 100 GeV , c,d). The sign of the systematic source indicates the sign of the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C difference. The shaded band shows gluon flavor response uncertainty symmetrically around zero. |
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Figure 32-c:
Systematic uncertainties in jet energy corrections for various flavor mixtures (QCD dijets, Z+jet and $\gamma $+jet) and pure flavors (gluons, light quarks and bottom quarks) as a function of jet $ {p_{\mathrm {T}}} $ (a,c, for fixed $|\eta _{\rm jet}|= $ 0 , a,b, and $|\eta _{\rm jet}|= $ 2.7 , c,d) and $\eta _{\rm jet}$ (b,d, for fixed $ {p_{\mathrm {T}}} = $ 30 GeV, a,b, and 100 GeV , c,d). The sign of the systematic source indicates the sign of the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C difference. The shaded band shows gluon flavor response uncertainty symmetrically around zero. |
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Figure 32-d:
Systematic uncertainties in jet energy corrections for various flavor mixtures (QCD dijets, Z+jet and $\gamma $+jet) and pure flavors (gluons, light quarks and bottom quarks) as a function of jet $ {p_{\mathrm {T}}} $ (a,c, for fixed $|\eta _{\rm jet}|= $ 0 , a,b, and $|\eta _{\rm jet}|= $ 2.7 , c,d) and $\eta _{\rm jet}$ (b,d, for fixed $ {p_{\mathrm {T}}} = $ 30 GeV, a,b, and 100 GeV , c,d). The sign of the systematic source indicates the sign of the Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C difference. The shaded band shows gluon flavor response uncertainty symmetrically around zero. |
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Figure 33:
Distribution of the Z+b-jet response using the MPF method with a fixed requirement $\alpha < $ 0.3 (a). Data-to-simulation ratio of the Z+b-jet response relative to the inclusive Z+jet sample with the MPF and the $ {p_{\mathrm {T}}} $-balance methods (b). |
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Figure 33-a:
Distribution of the Z+b-jet response using the MPF method with a fixed requirement $\alpha < $ 0.3 (a). Data-to-simulation ratio of the Z+b-jet response relative to the inclusive Z+jet sample with the MPF and the $ {p_{\mathrm {T}}} $-balance methods (b). |
png pdf |
Figure 33-b:
Distribution of the Z+b-jet response using the MPF method with a fixed requirement $\alpha < $ 0.3 (a). Data-to-simulation ratio of the Z+b-jet response relative to the inclusive Z+jet sample with the MPF and the $ {p_{\mathrm {T}}} $-balance methods (b). |
png pdf |
Figure 34:
Residual correction factors (calculated as the ratio of the MC and data MPF response) as a function of Z boson $ {p_{\mathrm {T}}} $, for Z+b-jet and Z+jet events with $\alpha < $ 0.3 (a), and their ratio (b). |
png pdf |
Figure 34-a:
Residual correction factors (calculated as the ratio of the MC and data MPF response) as a function of Z boson $ {p_{\mathrm {T}}} $, for Z+b-jet and Z+jet events with $\alpha < $ 0.3 (a), and their ratio (b). |
png pdf |
Figure 34-b:
Residual correction factors (calculated as the ratio of the MC and data MPF response) as a function of Z boson $ {p_{\mathrm {T}}} $, for Z+b-jet and Z+jet events with $\alpha < $ 0.3 (a), and their ratio (b). |
png pdf |
Figure 35:
Jet $ {p_{\mathrm {T}}} $ resolution distributions in the barrel for two bins of jet $ {p_{\mathrm {T}}} $. $\Delta R$ indicates the distance parameter value used for matching reconstructed jets to the corresponding particle-level jets. The nongaussian tails due to inactive areas of the ECAL and HCAL punchthrough become more visible for narrow high-$ {p_{\mathrm {T}}} $ jets with small core resolution. The Gaussian core resolution is fit to within $\pm$2$ \sigma $ (solid line) and its extrapolation is indicated with a dotted line. The tails are well modeled by a double-sided Crystal Ball function. |
png pdf |
Figure 35-a:
Jet $ {p_{\mathrm {T}}} $ resolution distributions in the barrel for two bins of jet $ {p_{\mathrm {T}}} $. $\Delta R$ indicates the distance parameter value used for matching reconstructed jets to the corresponding particle-level jets. The nongaussian tails due to inactive areas of the ECAL and HCAL punchthrough become more visible for narrow high-$ {p_{\mathrm {T}}} $ jets with small core resolution. The Gaussian core resolution is fit to within $\pm$2$ \sigma $ (solid line) and its extrapolation is indicated with a dotted line. The tails are well modeled by a double-sided Crystal Ball function. |
png pdf |
Figure 35-b:
Jet $ {p_{\mathrm {T}}} $ resolution distributions in the barrel for two bins of jet $ {p_{\mathrm {T}}} $. $\Delta R$ indicates the distance parameter value used for matching reconstructed jets to the corresponding particle-level jets. The nongaussian tails due to inactive areas of the ECAL and HCAL punchthrough become more visible for narrow high-$ {p_{\mathrm {T}}} $ jets with small core resolution. The Gaussian core resolution is fit to within $\pm$2$ \sigma $ (solid line) and its extrapolation is indicated with a dotted line. The tails are well modeled by a double-sided Crystal Ball function. |
png pdf |
Figure 36:
JER versus $ {p_{\mathrm {T}}} $ in the barrel for varying levels of pileup $\mu $. The results are shown separately for PF+CHS jets with size $R= $ 0.7 (a), and for PF+CHS jets with size $R= $ 0.5 (b). |
png pdf |
Figure 36-a:
JER versus $ {p_{\mathrm {T}}} $ in the barrel for varying levels of pileup $\mu $. The results are shown separately for PF+CHS jets with size $R= $ 0.7 (a), and for PF+CHS jets with size $R= $ 0.5 (b). |
png pdf |
Figure 36-b:
JER versus $ {p_{\mathrm {T}}} $ in the barrel for varying levels of pileup $\mu $. The results are shown separately for PF+CHS jets with size $R= $ 0.7 (a), and for PF+CHS jets with size $R= $ 0.5 (b). |
png pdf |
Figure 37:
JER parameters ($N$, $S$, $C$; see text) fitted in bins of $\mu $ for various values of the distance parameter $R$, as a function of their average value of pileup times jet area ($\mu A$). The results are compared between PF (solid symbols) and PF+CHS (open symbols). The dotted and dash-dotted curves represent the fit for PF and PF+CHS jets, respectively. |
png pdf |
Figure 38:
True JER in simulation for different jet flavors in the $\gamma $+jet sample, for jets with $|\eta |< $ 0.5. The distributions are shown for particle-level jets with no neutrinos (a), and with neutrinos exceptionally included (b) to demonstrate the large fluctuations this induces for c and b jets. |
png pdf |
Figure 38-a:
True JER in simulation for different jet flavors in the $\gamma $+jet sample, for jets with $|\eta |< $ 0.5. The distributions are shown for particle-level jets with no neutrinos (a), and with neutrinos exceptionally included (b) to demonstrate the large fluctuations this induces for c and b jets. |
png pdf |
Figure 38-b:
True JER in simulation for different jet flavors in the $\gamma $+jet sample, for jets with $|\eta |< $ 0.5. The distributions are shown for particle-level jets with no neutrinos (a), and with neutrinos exceptionally included (b) to demonstrate the large fluctuations this induces for c and b jets. |
png pdf |
Figure 39:
a: Asymmetry distribution, Eq.(39), for data and simulation for jets with $ {p_{\mathrm {T}}} \approx$ 250 GeV and $|\eta |< $ 0.5. b: Asymmetry measured for various thresholds $\alpha _{\rm max}$, extrapolated to zero additional jet activity, for jets with $ {p_{\mathrm {T}}} \approx$ 250 GeV and $|\eta |< $ 0.5 in data and MC simulation at the detector- and particle-level. The light horizontal line indicates the average particle-level resolution obtained as the difference in quadrature of MC simulation reconstructed asymmetry and particle-level imbalance, extrapolated to zero additional jet activity. |
png pdf |
Figure 39-a:
a: Asymmetry distribution, Eq.(39), for data and simulation for jets with $ {p_{\mathrm {T}}} \approx$ 250 GeV and $|\eta |< $ 0.5. b: Asymmetry measured for various thresholds $\alpha _{\rm max}$, extrapolated to zero additional jet activity, for jets with $ {p_{\mathrm {T}}} \approx$ 250 GeV and $|\eta |< $ 0.5 in data and MC simulation at the detector- and particle-level. The light horizontal line indicates the average particle-level resolution obtained as the difference in quadrature of MC simulation reconstructed asymmetry and particle-level imbalance, extrapolated to zero additional jet activity. |
png pdf |
Figure 39-b:
a: Asymmetry distribution, Eq.(39), for data and simulation for jets with $ {p_{\mathrm {T}}} \approx$ 250 GeV and $|\eta |< $ 0.5. b: Asymmetry measured for various thresholds $\alpha _{\rm max}$, extrapolated to zero additional jet activity, for jets with $ {p_{\mathrm {T}}} \approx$ 250 GeV and $|\eta |< $ 0.5 in data and MC simulation at the detector- and particle-level. The light horizontal line indicates the average particle-level resolution obtained as the difference in quadrature of MC simulation reconstructed asymmetry and particle-level imbalance, extrapolated to zero additional jet activity. |
png pdf |
Figure 40:
Extrapolated JER as a function of jet $ {p_{\mathrm {T}}} $ obtained with the asymmetry method on dijet events for data (solid circles), reconstructed MC simulation (open squares), and particle-level simulation with PLI (dashed line). The bottom plot shows the ratio of data over MC. |
png pdf |
Figure 41:
Jet energy resolution data/MC scale factor versus $|\eta |$ for dijet data collected at 8 TeV (closed circles, solid area) compared to results at 7 TeV (open circles, dashed area). |
png pdf |
Figure 42:
a: The $\alpha $ distribution in data (circles) and simulation (histogram), with the function used for simulation reweighting overlaid on the ratio of data over simulation in the bottom plot. b: Comparison of particle-level imbalances $\sigma _{A,\rm gen}(\alpha \rightarrow 0)$ in Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C as a function of jet $p_{\rm T,ave}$. The bottom plot shows the ratio of Pythia over Herwig. |
png pdf |
Figure 42-a:
a: The $\alpha $ distribution in data (circles) and simulation (histogram), with the function used for simulation reweighting overlaid on the ratio of data over simulation in the bottom plot. b: Comparison of particle-level imbalances $\sigma _{A,\rm gen}(\alpha \rightarrow 0)$ in Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C as a function of jet $p_{\rm T,ave}$. The bottom plot shows the ratio of Pythia over Herwig. |
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Figure 42-b:
a: The $\alpha $ distribution in data (circles) and simulation (histogram), with the function used for simulation reweighting overlaid on the ratio of data over simulation in the bottom plot. b: Comparison of particle-level imbalances $\sigma _{A,\rm gen}(\alpha \rightarrow 0)$ in Pythia6.4 tune Z2* and Herwig++2.3 tune EE3C as a function of jet $p_{\rm T,ave}$. The bottom plot shows the ratio of Pythia over Herwig. |
png pdf |
Figure 43:
Data/MC scale factors for the jet $ {p_{\mathrm {T}}} $ resolution as a function of $|\eta |$, determined from 8-TeV $\gamma $+jet data (hatched boxes) compared to those obtained from dijet data (solid boxes) at 7 TeV (a) and at 8 TeV (b). |
png pdf |
Figure 43-a:
Data/MC scale factors for the jet $ {p_{\mathrm {T}}} $ resolution as a function of $|\eta |$, determined from 8-TeV $\gamma $+jet data (hatched boxes) compared to those obtained from dijet data (solid boxes) at 7 TeV (a) and at 8 TeV (b). |
png pdf |
Figure 43-b:
Data/MC scale factors for the jet $ {p_{\mathrm {T}}} $ resolution as a function of $|\eta |$, determined from 8-TeV $\gamma $+jet data (hatched boxes) compared to those obtained from dijet data (solid boxes) at 7 TeV (a) and at 8 TeV (b). |
png pdf |
Figure 44:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 44-a:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 44-b:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 44-c:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 44-d:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 44-e:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 44-f:
Summary of JES systematic uncertainties as a function of jet $ {p_{\mathrm {T}}} $ (for 3 different $|\eta _{\rm jet}|$ values, a,c,e) and of $\eta _{\rm jet}$ (for 3 different $ {p_{\mathrm {T}}} $ values, b,d,f). The markers show the single effect of different sources, the gray dark band the cumulative total uncertainty. The total uncertainty, when excluding the effects of time dependence and flavor, is also shown in yellow light. The plots are limited to a jet energy $E= {p_{\mathrm {T}}} \cosh\eta = $ 4000 GeV so as to show only the correction factors for reasonable $ {p_{\mathrm {T}}} $ in the considered data-taking period. |
png pdf |
Figure 45:
Correlation of total JES systematic uncertainties excluding time-dependent and flavor uncertainties (TotalNoTimeNoFlavor) for PF+CHS versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3 (a). The color represents the degree of correlation (between $-1$ and $1$). Correlation of JES systematic uncertainties (TotalNoTimeNoFlavor) for PF+CHS versus $ {p_{\mathrm {T}}} $ (multiplied by $100^{{\rm j}\eta }$) and j$\eta $ bin (b). The integer j$\eta $ is introduced for illustration purposes, with j$\eta = $ 0 for the barrel region (BB), j$\eta = $ 1 for the endcap inside tracker coverage (EC1), j$\eta = $ 2 for the endcap outside tracker coverage (EC2), and j$\eta = $ 3 for the forward region (HF). |
png pdf |
Figure 45-a:
Correlation of total JES systematic uncertainties excluding time-dependent and flavor uncertainties (TotalNoTimeNoFlavor) for PF+CHS versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3 (a). The color represents the degree of correlation (between $-1$ and $1$). Correlation of JES systematic uncertainties (TotalNoTimeNoFlavor) for PF+CHS versus $ {p_{\mathrm {T}}} $ (multiplied by $100^{{\rm j}\eta }$) and j$\eta $ bin (b). The integer j$\eta $ is introduced for illustration purposes, with j$\eta = $ 0 for the barrel region (BB), j$\eta = $ 1 for the endcap inside tracker coverage (EC1), j$\eta = $ 2 for the endcap outside tracker coverage (EC2), and j$\eta = $ 3 for the forward region (HF). |
png pdf |
Figure 45-b:
Correlation of total JES systematic uncertainties excluding time-dependent and flavor uncertainties (TotalNoTimeNoFlavor) for PF+CHS versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3 (a). The color represents the degree of correlation (between $-1$ and $1$). Correlation of JES systematic uncertainties (TotalNoTimeNoFlavor) for PF+CHS versus $ {p_{\mathrm {T}}} $ (multiplied by $100^{{\rm j}\eta }$) and j$\eta $ bin (b). The integer j$\eta $ is introduced for illustration purposes, with j$\eta = $ 0 for the barrel region (BB), j$\eta = $ 1 for the endcap inside tracker coverage (EC1), j$\eta = $ 2 for the endcap outside tracker coverage (EC2), and j$\eta = $ 3 for the forward region (HF). |
png pdf |
Figure 46:
PF jet composition in data and simulation versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3 (a), and versus $\eta $ at 56 $ < {p_{\mathrm {T}}} < $ 74 GeV (b). |
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Figure 46-a:
PF jet composition in data and simulation versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3 (a), and versus $\eta $ at 56 $ < {p_{\mathrm {T}}} < $ 74 GeV (b). |
png pdf |
Figure 46-b:
PF jet composition in data and simulation versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3 (a), and versus $\eta $ at 56 $ < {p_{\mathrm {T}}} < $ 74 GeV (b). |
png pdf |
Figure 47:
Jet composition at particle level in the Pythia6.4 tune Z2* for QCD dijet sample, shown versus $ {p_{\mathrm {T}}} $ at $|\eta |< $ 1.3. The component labeled '$\gamma (\mathrm {rest})$' denotes all photons not coming from $\pi ^0$s, and the component labeled 'rest' refers to all particles not listed specifically. |
| Tables | |
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Table 1:
List of JES uncertainty sources, grouped by categories, with numbering, a short description, and range of validity in $|\eta |$. |
png pdf |
Table 2:
List of JES uncertainty source combinations with a short description and list of uncertainty components. The numbering of the sources ($3^{\rm rd}$ column) corresponds to that used in Table 1 (2$^{\rm nd}$ column). |
| Summary |
|
The understanding of jet energy scale and resolution achieved by the CMS experiment exploiting the pp data taken at 8 TeV, corresponding to an integrated luminosity of 19.7 fb$^{-1}$, has been documented. The CMS strategy involves the sequential correction of the jets for the pileup offset, simulated response, and residual $\eta$ and $p_{\mathrm{T}}$ dependencies in data with respect to simulation, with optional corrections depending on the jet flavor. The pileup offset corrections are determined from QCD dijet simulations processed with and without pileup overlay, with additional corrections for residual differences between data and detector simulation, extracted using the random-cone method in zero-bias events. The simulated jet response corrections are determined from a Monte Carlo event sample, as a function of jet $p_{\mathrm{T}}$ and $\eta$, for various jet algorithms and distance parameter sizes. The $\eta$-dependent corrections for residual differences between data and MC simulation are determined with dijet events, relative to a jet in the central region $|\eta|< $ 1.3. The $p_{\mathrm{T}}$-dependent corrections for residual differences within $|\eta|< $ 1.3 at 30 $ < p_{\mathrm{T}} < $ 800 GeV are measured combining photon+jet, $ \mathrm{Z} ( \to \mu \mu) $+jets, and $ \mathrm{Z} ( \to \mathrm{ee}) $+jets events. The $p_{\mathrm{T}}$ dependence at $p_{\mathrm{T}}> $ 800 GeV is directly constrained with multijet events. The optional jet-flavor corrections are derived from MC simulation and checked for b jets. The simulated jet $p_{\mathrm{T}}$ resolution is determined, as a function of jet $p_{\mathrm{T}}$ and $\eta$, for different levels of pileup. The dependence of the resolution on the jet flavor is also studied. The $\eta$-dependent corrections for residual differences between data and MC simulation in the jet resolution are determined with both dijet and $\gamma$+jet events. In all methods using MC simulation, the uncertainties arising from the modeling of jet radiation and hadronization are constrained from the study of the differences between Pythia6.4 and Herwig++ 2.3 generators. Detailed studies are performed to correct for biases in the data-based methods due to differences with respect to the MC simulation, in initial- and final-state radiation as well as in jet $p_{\mathrm{T}}$ resolution. The systematic uncertainties in the jet energy corrections, and their correlations, are provided as a function of $\eta$ and $p_{\mathrm{T}}$. The final uncertainties on the jet energy scale are below 3% across the phase space considered by most analyses ($p_{\mathrm{T}}> $ 30 GeV and $|\eta|< $ 5.0). In the barrel region we reach an uncertainty below 1% for $p_{\mathrm{T}}> $ 30 GeV, when excluding the jet-flavor uncertainties, provided separately for different jet-flavor mixtures. At its lowest, the core uncertainty (excluding optional time-dependent and flavor systematics) is 0.32% for jets with $p_{\mathrm{T}}$ between 165 and 330 GeV, and $|\eta|< $ 0.8. These results set a new benchmark for jet energy scale determination at hadron colliders. |
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