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| CMS-PAS-HIN-19-013 | ||
| Study of in-medium modification of dijets in PbPb collisions at 5.02 TeV | ||
| CMS Collaboration | ||
| July 2020 | ||
| Abstract: Modifications to the distribution of charged particles with respect to high transverse momentum $(p_{\mathrm{T}})$ jets passing through a quark-gluon plasma are explored. Jets corresponding to dijet selection where the leading and subleading jets are back-to-back are studied in lead-lead (PbPb) and proton-proton (pp) collisions. Correlations of charged particles are measured in relative pseudorapidity and relative azimuth from the jet axes. Jet momentum density profiles ("jet shapes") are determined. The events are categorized in bins of collision centrality, charged particle $p_{\mathrm{T}}$ and dijet momentum balance $x_{j}$, which is the ratio between the subleading and leading jet $p_{\mathrm{T}}$. In comparing the PbPb and pp collision results, modifications to the charged particle yields is found to depend on the $x_{j}$ value. Modifications to both the charged-particle pseudorapidity dependence and the jet momentum density profile are observed to be greater for the leading jet in more momentum balanced conditions. The modifications become more pronounced with respect to the subleading jet for events with a larger dijet momentum imbalance. | ||
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CDS record (PDF) ;
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These preliminary results are superseded in this paper, JHEP 05 (2021) 116. The superseded preliminary plots can be found here. |
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| Figures & Tables | Summary | Additional Figures | References | CMS Publications |
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| Figures | |
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Figure 1:
Distributions of charged particle yields correlated to leading jets as a function of $|\Delta \eta |$ for pp (first column) and PbPb collisions in different centrality bins (second to fifth column), shown differentially for all $p_{\rm T}^{\rm trk}$ bins. The first row shows the charged particle yields without any selection on $x_{j}$, while other rows show the charged particle yields in different bins of $x_{j}$, starting with the most unbalanced 0 $ < x_{j} < $ 0.6 (second row) to most balanced 0.8 $ < x_{j} < $ 1.0 (fourth row) dijet events. |
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Figure 2:
Distributions of charged particle yields correlated to subleading jets as a function of $|\Delta \eta |$ for pp (first column) and PbPb collisions in different centrality bins (second to fifth column), shown differentially for all $p_{\rm T}^{\rm trk}$ bins. The first row shows the charged particle yields without any selection on $x_{j}$, while other rows show the charged particle yields in different bins of $x_{j}$, starting with the most unbalanced 0 $ < x_{j} < $ 0.6 (second row) to most balanced 0.8 $ < x_{j} < $ 1.0 (fourth row) dijet events. |
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Figure 3:
Jet radial momentum profile $\mathrm {P}(\Delta r)$ for pp (first column) and PbPb collisions in different centrality bins (second to fifth column), shown differentially in $p_{\rm T}^{\rm trk}$ for leading (top row) and subleading (bottom row) jets. |
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Figure 4:
PbPb to pp ratio of the jet radial momentum distributions, $\mathrm {P} (\Delta r)_{\rm PbPb}/\mathrm {P} (\Delta r)_{\rm pp}$, for different centrality bins for the leading jets (top row) and subleading jets (bottom row). |
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Figure 5:
Leading jet shapes $\rho (\Delta r)$ (normalized to unity over $\Delta r < $ 1) for pp (first column) and PbPb collisions in different centrality bins (second to fifth columns), shown differentially in $p_{\rm T}^{\rm trk}$ for inclusive $x_{j}$ bin (first row) and in differential bins 0 $ < x_{j} < $ 0.6 (second row), 0.6 $ < x_{j} < $ 0.8 (third row), and 0.8 $ < x_{j} < $ 1.0 (fourth row). |
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Figure 6:
PbPb to pp ratio for leading jet shapes $\rho (\Delta r)_{\rm PbPb} / \rho (\Delta r)_{\rm pp}$, in different centrality bins for 0 $ < x_{j} < $ 0.6 (top row), 0.6 $ < x_{j} < $ 0.8 (middle row) and 0.8 $ < x_{j} < $ 1.0 (bottom row) dijet selections. The leading jet shape ratio for all dijets, i.e. without any selection on the dijet momentum balance are also shown in each row for comparison. |
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Figure 7:
Subleading jet shapes $\rho (\Delta r)$ (normalized to unity over $\Delta r < $ 1) for pp (first column) and PbPb collisions in different centrality bins (second to fifth columns), shown differentially in $p_{\rm T}^{\rm trk}$ for inclusive $x_{j}$ bin (first row) and in differential bins 0 $ < x_{j} < $ 0.6 (second row), 0.6 $ < x_{j} < $ 0.8 (third row), and 0.8 $ < x_{j} < $ 1.0 (fourth row). |
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Figure 8:
PbPb to pp ratio for subleading jet shapes $\rho (\Delta r)_{\rm PbPb} / \rho (\Delta r)_{\rm pp}$, in different centrality bins for 0 $ < x_{j} < $ 0.6 (top row), 0.6 $ < x_{j} < $ 0.8 (middle row) and 0.8 $ < x_{j} < $ 1.0 (bottom row) dijet selections. The subleading jet shape ratio for all dijets, i.e. without any selection on the dijet momentum balance are also shown in each row for comparison. |
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Figure 9:
Ratio of momentum unbalanced jet shapes 0.0 $ < x_{j} < $ 0.6 (top row) and balanced jet shapes 0.8 $ < x_{j} < $ 1.0 (bottom row) to $x_{j}$ integrated jet shapes for leading jets in pp collisions and different PbPb centrality bins. |
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Figure 10:
Ratio of momentum unbalanced jet shapes 0.0 $ < x_{j} < $ 0.6 (top row) and balanced jet shapes 0.8 $ < x_{j} < $ 1.0 (bottom row) to $x_{j}$ integrated jet shape for subleading jets in pp collisions and different PbPb centrality bins. |
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Figure 11:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 11-a:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 11-b:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 11-c:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 11-d:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 11-e:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 12:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 12-a:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 12-b:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 12-c:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 12-d:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
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Figure 12-e:
Generator level $x_{j}$ versus reconstructed $x_{j}$ in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$. Pythia8 simulation is on the leftmost column in the top row while the most central Pythia+Hydjet in on the right of the bottow row. |
| Tables | |
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Table 1:
Number of events for pp and for different PbPb centrality bins within stated $x_{j}$ ranges. The numbers in parentheses show the fraction of events in each $x_{j}$ bin for a given centrality. |
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Table 2:
Systematic uncertainties for the leading jet shape components, integrated in $\eta $, and $\Delta r$, and shown for pp and centrality binned PbPb collisions. The ranges correspond to the $p_{\mathrm {T}}$ dependence of the uncertainty. |
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Table 3:
Systematic uncertainties for the subleading jet shape components, integrated in $\eta $, and $\Delta r$, and shown for pp and centrality binned PbPb collisions. The ranges correspond to the $p_{\mathrm {T}}$ dependence of the uncertainty. |
| Summary |
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CMS has measured charged particle yields in events containing back-to-back leading and subleading jet pairs around the respective jet axes using data from pp and PbPb collisions at ${\sqrt {\smash [b]{s_{_{\mathrm {NN}}}}}} = $ 5.02 TeV collected in 2017 and 2018. Using a momentum weighting, jet shapes are also determined. When comparing the charged particle yields around the jet axes, there is an excess of low ${p_{\mathrm{T}}}{}$ particles in PbPb collisions with respect to pp collisions. This excess is larger in the subleading side compared to leading side. The excess is also found to have a different $x_{j}$ dependence for the leading and subleading sides. The leading jets show the strongest modifications effects in balanced events, where the transverse momenta of the two jets are close to each other. However, subleading jets experience the greatest modifications in events with a large jet momentum imbalance between the leading and subleading jets. This indicates that in balanced events both jets lose a comparable amount of energy, while in events with a momentum imbalance the leading jet loses significantly less energy. A possible explanation for the imbalance is that the leading jet is produced near the surface of the plasma while the subleading jet needs to traverse a long distance through the plasma. For the jet shapes, a redistribution of energy is observed from small angles with respect to the jet axis to larger angles when comparing PbPb collisions to pp events. The difference between the PbPb and pp results is larger for the leading jet compared to the subleading jets, which can be explained by the fact that the subleading jet distribution in pp collisions is significantly wider than that for leading jets. When studying the $x_{j}$ bins for the subleading jet, there is a peak in the PbPb to pp ratio for unbalanced dijet momentum events that disappears for balanced events. This peak can be attributed to a third jet contribution that is needed in pp events to conserve momentum for events where there is a large dijet momentum imbalance. When comparing jet shape plots corresponding to different dijet momentum balance conditions, the distributions for leading jets are found to be broader for events with balanced jet momenta compared to those where there is a momentum imbalance. For subleading jets, the situation changes with the events with a significant momentum imbalance found to be broader. These observations are consistent with the previous hypothesis given to interpret the particle yield measurements, namely that the average path length inside the medium for leading jets is larger for momentum balanced events, while for subleading jets it is larger in unbalanced events. These data can be used to constrain models of the production point of the dijet within the quark-gluon plasma. |
| Additional Figures | |
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Additional Figure 1:
Distributions of charged particle yields correlated to leading jets as a function of $|\Delta \eta |$ for pp (first column) and 0-10 % central PbPb collisions (second column), shown differentially for all charged particle transverse momentum $(p_{\rm T}^{\rm ch})$ bins. The first row shows the charged particle yields without any selection on $x_{j} = {{p_{\mathrm {T}}} {}^{\mathrm {subleading}}}/{{p_{\mathrm {T}}} {}^{\mathrm {leading}}}$, while other rows show the charged particle yields in different bins of $x_{j}$, starting with the most unbalanced 0 $ < x_{j} < $ 0.6 (second row) to the most balanced 0.8 $ < x_{j} < $ 1.0 (third row) dijet events. |
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Additional Figure 2:
Distributions of charged particle yields correlated to subleading jets as a function of $|\Delta \eta |$ for pp (first column) and 0-10 % central PbPb collisions (second column), shown differentially for all charged particle transverse momentum $(p_{\rm T}^{\rm ch})$ bins. The first row shows the charged particle yields without any selection on $x_{j} = {{p_{\mathrm {T}}} {}^{\mathrm {subleading}}}/{{p_{\mathrm {T}}} {}^{\mathrm {leading}}}$, while other rows show the charged particle yields in different bins of $x_{j}$, starting with the most unbalanced 0 $ < x_{j} < $ 0.6 (second row) to the most balanced 0.8 $ < x_{j} < $ 1.0 (third row) dijet events. |
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Additional Figure 3:
Leading jet shapes $\rho (\Delta r)$ (normalized to unity over $\Delta r < $ 1) for pp (first column) and 0-10 % central PbPb collisions (second column), shown differentially in charged particle transverse momentum $(p_{\rm T}^{\rm ch})$ for inclusive $x_{j} = {{p_{\mathrm {T}}} {}^{\mathrm {subleading}}}/{{p_{\mathrm {T}}} {}^{\mathrm {leading}}}$ bin (first row) and in $x_{j}$ bins 0 $ < x_{j} < $ 0.6 (second row) and 0.8 $ < x_{j} < $ 1.0 (third row). |
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Additional Figure 4:
Subleading jet shapes $\rho (\Delta r)$ (normalized to unity over $\Delta r < $ 1) for pp (first column) and 0-10 % central PbPb collisions (second column), shown differentially in charged particle transverse momentum $(p_{\rm T}^{\rm ch})$ for inclusive $x_{j} = {{p_{\mathrm {T}}} {}^{\mathrm {subleading}}}/{{p_{\mathrm {T}}} {}^{\mathrm {leading}}}$ bin (first row) and in $x_{j}$ bins 0 $ < x_{j} < $ 0.6 (second row) and 0.8 $ < x_{j} < $ 1.0 (third row). |
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Additional Figure 5:
PbPb to pp ratio for leading jet shapes $\rho (\Delta r)_{\rm PbPb} / \rho (\Delta r)_{\rm pp}$ for events in the 0-10 % centrality class. The gray points show $x_{j} = {{p_{\mathrm {T}}} {}^{\mathrm {subleading}}}/{{p_{\mathrm {T}}} {}^{\mathrm {leading}}}$ integrated ratio, while the red points are the ratio in 0 $ < x_{j} < $ 0.6 bin and blue points in 0.8 $ < x_{j} < $ 1.0 bin. Error bars are statistical uncertainties while the shaded areas show systematic uncertainties. |
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Additional Figure 6:
PbPb to pp ratio for subleading jet shapes $\rho (\Delta r)_{\rm PbPb} / \rho (\Delta r)_{\rm pp}$ for events in the 0-10 % centrality class. The gray points show $x_{j} = {{p_{\mathrm {T}}} {}^{\mathrm {subleading}}}/{{p_{\mathrm {T}}} {}^{\mathrm {leading}}}$ integrated ratio, while the red points are the ratio in 0 $ < x_{j} < $ 0.6 bin and blue points in 0.8 $ < x_{j} < $ 1.0 bin. Error bars are statistical uncertainties while the shaded areas show systematic uncertainties. |
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Compact Muon Solenoid LHC, CERN |
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