Purpose
This Twiki page is to document results and ideas of Dmytro Oliinychenko during his summer studentship at CERN. The supervisor is Mateusz Ploskon. The topic of research is studies of jets in heavy ion collisions.
Introduction and main goal
Jets are a nice probe of Quark-Gluon Plasma (QGP). Jet quenching, i.e. attenuation or disappearance of the hadron spray born in hard interaction, was one of the first proposed signals of QGP [1]. Jet quenching was observed experimentally in heavy ion collision experiments at RHIC and LHC and is considered as one of the arguments for QGP existence. The phenomenon of jet quenching is interesting not only qualitatively as a QGP signal, but also quantitatively as a probe that allows to measure properties of the hot and dense quark-gluon medium. There is a number of models for parton energy loss in QGP, which allowed to extract transport coefficient \hat{q}, gluon density and initial energy density loss in QGP \epsilon_{0} from nuclear modification factor and di-hadron observables.
However, there is a hope to extract more information about QGP using jets. Fully recostructed jets seem to be one more promising probe, because they can give an additional information about medium. Taking jet energy profile and its content as observables we can directly (and hopefully model-independently) get the gluon medium-induced bremsstrahlung spectrum (suggested in [3]) and in-medium quark fragmentation functions.
Maybe also some other quantities?
Fully reconstructed jets were considered as promising already in 2004[2]. To 2009 it was already carefully studied (e.g. [2,3,4]) at which jet observables one should look and which theoretical quantities one can extract from them. However, there is a reason that prevented people from accomplishing this study already at RHIC, even before LHC start. It is hard to distinguish jets that were born inside fireball from those born outside. The goal of my studies is to do this job, i.e. distinguish "true jets" from background. This can be reformulated as follows: such discriminator should be found that it will cut off almost all "false" jets born outside the fireball.
Results
06.07.2013
First step is to study p+p collisions without noise. Technically, procedure is the following: pp event at \sqrt_{S} = 2.76
TeV is modelled using Pythia8 with standard options and
HardQCD:all = on
. To make the simulation faster and to require less statistics, allowed hard process Q^2 in event is restricted to some bin. Afterwards data for all bins are put together and properly normalized. Final particles from simulation are delivered to
FastJet. Jets are formed using
anti-kt algorithm with
R_jet = 0.4 and default recombination scheme (direct adding). There is a pseudorapidity cut applied to jets: |η|<3.5 Jet constituents are considered as an input for
FastJet. Subjets are formed with
kt algorithm with
R_subjet = 0.2 and default recombination scheme. Results are as follows:
1. Jet pT and η
More... Close From them we can conclude that i) number of jets with high transverse momentum is very small, ii) faster jets tend more to midrapidity.
2. Jet multiplicity distribution and number of constituents distribution
More... Close We see that number of constituents per jet is growing with pT, at low pT bins distribution has clear maximum, while at high pT distribution becomes almost uniform. At the same time average number of jets per event is almost the same for all pT and never exceeds 6. ( I think this comes from lack of statistics.)
3. Let us now consider the behaviuor of subjets - their pT, η distributions, number of subjets per jet and fraction of pT carried by subjet - Z.
More... Close In subjet pT distribution for jet pT > 20 GeV one can see maximums at the right wing. This means that at jet pT > 20 GeV there is often a situation when only one subjet carries most of the jet momentum. This conclusion is confirmed by Z (subjet pT fraction) distribution. Distribution of subjet pseudorapidity is similar to that of jets. No special effects of recombination scheme are visible. Number of subjets per jet tends to behave similarly for all jet pTs. Strangely, number of subjets distribution rapidly dies at number of subjets = 8 for all pT ( again not enough statistics). Average number of subjets per jet is 4-5. With increasing pT number of subjets per jet remains the same in average, but number of constituents per jet grows. Thus, at higher jet pT subjets have a bigger number of constituents.
08.07.2013
Plots for varying subjet radius:
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15.07.2013
With the help of Mateusz I have realised that previous plots were by pTHat, not by pT. In addition they weren't properly normalized. Again, pp collision was simulated via Pythia8, particles with |η| < 3.5 - Q R_jet (Q = 1, R_jet = 0.4) were taken for jet reconstruction. Particles from jets were taken as a new input for
FastJet reconstruction with R_subjet = 0.1, 0.2, 0.3. Here are 5 histograms for subjets: subjet Z (pT_subjet/pT_jet), leading subjet Z, subleading subjet Z, subjet normalized projection to jet momentum (p_subjet, p_jet)/p_jet^2, subjet pT:
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There is also one interesting quantity refered to as jet girth[5] - linear radial moment ∑ pT(particle)/pT(jet) * r(particle), where r(particle) is the Euclidean distance between particle and jet axis in η - φ plane. I have divided girth by jet radius to obtain value which always lies between 0 and 1. Here is what I got:
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18.07.2013
pp collision was simulated via Pythia8, particles with |η| < 2.8 - Q R_jet (Q = 1, R_jet = 0.4) were taken for jet reconstruction. Particles from jets were taken as a new input for
FastJet reconstruction with R_subjet = 0.2. Leading subjet pT fraction distribution is given, bumps in the central region should correspond to gluon jets, right jumps - to quark jets.
23.07.2013
Using Pythia6 I have generated gluon- and d-jets with narrow Pt spectrum around 45
GeV. To produce such jets I used Py1ent and generated two gluons or d and anti-d quarks with given Pt, that fly into opposite directions.
pythia6->Py1ent(-1, 21, 50., TMath::Pi()/2., 0.);
pythia6->Py1ent( 2, 21, 50., TMath::Pi()/2., TMath::Pi());
R_subjet = 0.2, algorithm for subjet extraction is kt.
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Analoguos plots for R_subjet = 0.1:
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Kt subjet exctraction algorithm is on the left panel, anti-kt subjet extraction algorithm is on the right panel.
This is similar qualitatively to
http://jets.physics.harvard.edu/qvg/
results, but it differs quantitatively. My assumption is that my quark jets are purely d jets, while their quark jets are a mixture. This leads me to an attempt to generate different flavour jets. Kt subjet exctraction algorithm is on the left panel, anti-kt subjet extraction algorithm is on the right panel.
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29.07.2013
I have gone in for Toy Model to consider background effects. I generate gluon jets and d-jets with Pt around 45
GeV (40 - 50
GeV, rather sharp peak) using Pythia6. To particles generated in this way I add "background" with Boltzmann spectrum, T = 700
MeV, average background multiplicity 1917 particles per event. Eta and phi are uniformly distributed. After that I consider three types of jets: I) hard jets (true jets), II) pure background jets (fake jets) - jets that consist purely from background particles and III) full jets merged with hard (half constituents of the jet match with some hard jet). For these jets Z (subjet Pt fraction) distribution was built. Additionally, constituents lower Pt cut was considered.
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05.08.2013
Same Toy Model and conditions as earlier but statistics 10 times increased (thank to pdsf.nersc.gov grid) and more quantities are plotted: Pt (hard jets, full jets, full merged with hard), leading subjet Pt fraction Z (hard jets, fake jets, full merged with hard), Z with background exctraction (fake jets and full merged with hard), background density rho.








06.08.2013
I tried to generate jets with Pythia8 and check for bumps at Z=1. No bumps. Huge crosses must me due to sides of distribution when summing by
PtHat.
Pt versus leading subjet Pt in Pythia 6:
07.08.2013
ToyModel. Pt (hard jets, full jets, full merged with hard), leading subjet Pt fraction Z (hard jets, fake jets, full merged with hard), Z with background exctraction (fake jets and full merged with hard), background density rho. Pt of jets is 1) 15-20GeV and 2) 70-80
GeV.
20
GeV:
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80
GeV:
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15.08.2013
I have looked into jet contents. How many mesons and baryons are there in gluon/light quark jets? Here is the plot to answer it.
23.08.2013
With the help of Mateusz and Xiaoming I tried to analyze data, keeping in mind my previous MC studies. It took me a week to get some minimal understanding how data analysis is done at ALICE.
References
[1] J. D. Bjorken, FERMILAB-PUB-82-059-THY (1982)
[2]C. A. Salgado and U. A. Wiedemann, Phys. Rev. Lett. 93 , 042301 (2004)
[3]I. Vitev, S. Wicks and B. W. Zhang, arXiv:0810.2807 [hep-ph]
[4]F. Arleo, arXiv:0810.1193v1 [hep-ph], 2008
[5]J. Gallicchio and M. D. Schwartz; Quark and Gluon Tagging at the LHC; 2011