HeavyIonJets

Introduction

Results from updated jet studies

Direct comparison between pp (left) and PbPb (right) jet energy resolution. J3 sample embedded to the most central PbPb collisions simulated by unquenched HIJING (b=2 fm, dN/dη= 2700).

Jet energy scale (most left) for the most central HIJING (b=2 fm, dN/dη= 2700) collisions and efficiency (middle plot). One can see that the shift for small jet energies is correlated with steeply falling efficiency. Corresponding fake-rate (most right).

Jet position resolution in the most central HIJING (b=2 fm, dN/dη= 2700). Right plot: coordinates (η φ) of a jet reconstructed with R=0.4 are substituted by coordinates of a closest jet reconstructed with R=0.2. One can see the enhancement in the jet position resolution. This strategy is further used in the study of jet substructure.

Fragmentation function (distribution of longitudinal fraction of particle’s momentum with respect to the jet) and j_T distribution (distribution of the transverse momentum of particles inside jet with respect to the jet axis). Open markers = truth distributions computed using truth jets (Cone4Truth) and pythia stable charged particles. Closed markers = reconstructed distributions in the most central HIJING collisions (b=2 fm, dN/dη= 2700) computed using background subtracted jets (AvgBkgrSutbrCone4Tower jets) and tracks. Reconstructed distributions are corrected for: 1) the background contribution (blue markers), 2) jet position resolution (by matching to jets reconstructed with cone algorithm with R=0.2), 3) for the efficiency (uniform correction by 70%).

Basic performance of tracks enetering the jet internal structure study. Momentum resolution (left) and position resolution (right).

Comparison of differential jet shape in the most central HIJING samples (b=2 fm, dN/dη= 2700) and the most peripheral (b=10 fm, dN/dη= 460). PYTHIA di-jet events were embedded into pp HIJING events. Only jets with E_T in the range of 70-140 GeV have been selected. Correction on jet position resolution was applied.

Comparison between radiative and collisional energy loss by PYQUEN. J3 sample without heavy ion underlying event has been used. Differential jets shape (left) compared to jet energy spectra (right).

Dijet correlations. Comparison between radiative, and collisional energy loss, and no-quenching (right). This can be compared to pp reconstructed and simulated events (ToDo: higher statistics, log scale).

Recent results

Study of influence of detector effects and effect of underlying event on measurements of jet internal structure

Fragmentation function (distribution of longitudinal fraction of particle momenta with respect to jet) and j_T distribution (distribution of transverse momenta of particles inside jet with respect to the jet axis) can be affected by intrinsic fluctuations of the underlying event which cannot be subtracted. The size of these fluctuations can be characterized by rms of the energy distribution measured at the calorimeter level. We have compared underlying event modeled by the central HIJING collision (b=0-3fm) and central HYDJET collisions (b=0-3fm). The comparison is in the following figure

The rms of the energy of underlying event in the case of HIJING is σ = 0.8 GeV whereas in the case of HYDJET it is σ = 0.6 GeV. (Plot uses following data samples: mc09_7TeV.208807.Hijing_PbPb_2p75TeV_Central.recon.ESD.e511_s780_s767_r1334_tid144743_00 and mc09_7TeV.208812.Hydjet_PbPb_2p75TeV_Central.recon.ESD.e540_s780_s767_r1334_tid144741_00. Both reconstructed in Athena 15.6.9 using HIJetAnalysis package. Statistics of 10 events, |η|<5.).

To systematically study the effect of the underlying event on fragmentation function and j_T distribution we have used simulated pp jets and its constituents (technical details bellow). Reference distributions are shown in closed black markers. To study the effect of jet position resolution deterioration we have smeared the jet axis by adding a randomly generated shift in η and φ so that we received the jet position resolution of σ(Δη) = σ(Δφ) = 0.06. This corresponds to the worst case scenario of jet position resolution received from simulations of HIJING central events. This effect is shown in open markers. One can see that the jet position resolution deterioration leads to a change of the slope of the j_T distribution whereas the fragmentation function remains almost unaffected. To study the effect of a possible jet energy scale shift we have added again a randomly generated shift with gaussian distribution with the mean of 5.6 GeV (average Et of jets is 56 GeV). The effect is shown in blue markers. One can see that the jet energy scale shift mainly affects the large z component whereas the low z remains unaffected. Naturally, the jet energy scale shift does not affect the j_T distribution.

Technical details: J3 sample mc09_7TeV.105012.J3_pythia_jetjet.recon.ESD.e468_s766_s767_r1206, statistics of 400000 events, 5357 jets with Et=<40,140> GeV, |eta|<1.9, AntiKt6TrackJets collection.

To study similar effects in the case of jet shapes we have used the same pp sample as above but now we have added guassian noise to constituents of jets. The guassian noise has mean Et = 0 and σ(Et)=1.4 GeV. This generates the jet energy resolution smearing of 20% and jet position resolution smearing of σ(Δη) = 0.06 (it approaches again the worst case scenario by HIJING). The reference jet shape is presented in closed black markers, red markers show jet shape computed in the situation of adding the noise. One can see a characteristic shift in the jet shape – the depletion in the center of a jet and enhancement in the jet periphery. To recover the jet shape, we tried to use a similar method as we did for results presented in PPR, i.e. to estimate the jet position using just a hard core of a jet (i.e. to recombine constituents inside a cone of size R<R_orig (for each jet R randomly chosen in the interval of <0.1,0.5>)). This is shown in green markers.

To study the unfolding of the detector effect we have used the new version of RooUnfold 0.2.2 and remade the old study that was done using RooUnfold 0.1.5. We tested bin-by-bin unfolding and bayesian unfolding. We have trained the response matrix event by event using 2D distributions of jet shapes shown in the following figure (training reconstructed - right, training truth - left). The resulting jet shapes after the unfolding are shown bellow. We used the same data sample as above, jets were reconstructed using AntiKt6TowerJets.

PPR studies - performance, fragmentation function and jT distribution

• (top) Tower energies for a PYTHIA di-jet event embedded into a HIJING event without quenching. (bottom) Tower energies in the same event after layer- and eta-dependent subtraction of ET cells to remove the underlying event. The background-subtracted tower energies are then used as input to the seeded cone algorithm. The inset figures show the eta-dependence of the energy in the towers integrated over −0.5 < phi < −1.5 rad, which picks out the jet at phi=~1 rad. The large background from the underlying event is suppressed by the background subtraction.
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• Comparison of the ET-dependent sigma(jTSum) cut for two different jet energies 40-60 GeV (left) and 60-80 GeV (right). Jets with sigma(jTSum)> -2.5 are removed
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• Comparison of efficiency (left) and ET resolution (right) for the cone (closed) and kT (open) algorithms for reconstructing jets in dNch/deta = 2650 pdf pdf

• Jet reconstruction efficiency for jets reconstructed with the seeded cone as a function of input jet ET and as a function of HIJING Pb+Pb multiplicity
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• (left) Jet energy resolution as function of truth jet ET for three multiplicity bins for seeded cone jet algorithm. (right) The azimuthal angular resolution of the seeded cone jets as function of truth jet energy
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• Jet energy resolution for ET > 50 GeV seeded cone jets as a function of eta for HIJING Pb+Pb events of different centrality, dNch/deta||eta|<0.5.
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• Input (filled circles), raw reconstructed (diamonds), and fake (squares) spectra for cone jets in central (dNch/dh = 2650) Pb+Pb collisions. The reconstructed spectrum is not corrected for efficiency or energy resolution. The dashed line represents the absolute fake jet rate from pure HIJING events prior to background jet rejection (see text for details). (bottom) Ratio of reconstructed to input jet spectrum for three different Pb+Pb collision centralities without efficiency and resolution corrections to the reconstructed spectra
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• Fragmentation function and jT distribution (Fig.6.16 from PPR)
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• Reconstructed PYQUEN and PYTHIA jT (left) and z (right) distributions. (lower) PYQUEN to PYTHIA ratio for reconstructed events.
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• Fragmentation function and jT distribution after the subtraction of background distribution and after the correction on the tracking efficiency. Truth distributions (open markers), reconstructed distributions (closed markers).
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• Fragmentation function and jT distribution after the subtraction of background distribution, after the correction on the tracking efficiency and after the additional jet position resolution correction. Truth distributions (open markers), reconstructed distributions (closed markers).
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• Fragmentation function and jT distribution from PYQUEN and PYTHIA simulated events.
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• Fragmentation function and jT distribution from PYQUEN and PYTHIA reconstructed events.
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Jet shapes

• Integral jet shape for reconstructed (closed) and truth (open) p+p events. eps, pdf, jpg
  
  

• Integral jet shape reconstructed in the most central collisions (closed) and jet shape reconstructed in the most peripheral collisions (open). HIJING without quenching. eps, pdf, jpg
  
  

• Integral and differential jet shape for PYQUEN and PYTHIA simulated events.
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• Integral and differential jet shape for PYQUEN and PYTHIA reconstructed events.
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Di-jet correlations

• Conditional yield for finding an associated jet above 70 GeV (B) given a leading jetabove 100 GeV (A), plotted as a function of (left) di-jet |Dphi| and (right) pout.

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Responsible: MartinSpousta
Last reviewed by: Never reviewed