Back-to-Back Jet analysis with PYTHIA and HYDJET++

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Back-to-Back Jet analysis with PYTHIA and HYDJET++ Hiroki Yokoyama Univ. of TSUKUBA

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Back-to-Back Jet analysis with PYTHIA and HYDJET++. Hiroki Yokoyama Univ. of TSUKUBA . Motivation. J-Cal performance at Back-to-Back Jet physics Which method is most excellent to find Back-to-Back Jets in Heavy Ion Experiment? Resolution of primary - parton energy . - PowerPoint PPT Presentation

Transcript of Back-to-Back Jet analysis with PYTHIA and HYDJET++

Page 1: Back-to-Back Jet analysis  with PYTHIA and HYDJET++

Back-to-Back Jet analysis with PYTHIA and

HYDJET++Hiroki Yokoyama

Univ. of TSUKUBA

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Motivation J-Cal performance at Back-to-Back Jet

physics Which method is most excellent to find

Back-to-Back Jets in Heavy Ion Experiment? Resolution of primary-parton energy

Simulation with PYTHIA and HYDJET++

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Jet Finding in pp CellJet algorithm track by track energy smearing

charged particles : ALICE TPC+ITS momentum resolution(assume pion mass)

neutral particles : ALICE EMCal energy resolution find jet using Visible(neutral+charged) or Charged

particles parameter

value

ConeRadius

0.2

eT-seed 20GeV(Visible), 13GeV(Charged)

Min-eT 1.5GeV(Visible), 1GeV(Charged)

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Back-to-Back Jet Physics in pp

PYTHIA8 CellJet Jet-Finding algorithm R=0.2 (η-φ space) Dijet

coplanarity = |φJet1-φJet2| - π energy balance = parton energy resolution = ΔeT/eT

Coplanarity, energy balanceand energy resolution

are improved by installation of Calorimeter.

eT jet1 − eT jet 21 2 ⋅(eT jet1 + eT jet 2)

jet1jet2

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Jet Finding in Pb+Pb

Generate samples of PYTHIA Dijets using PYTHIA8 CellJet algorithm(R=0.7) Embed these jets in Heavy-Ion events generated by HYDJET++ generator Find Back-to-Back Jets using CellJet corrected for Heavy-Ion experiment(CellJet’) calculate S/(S+B), efficiency, jet-energy resolution and parton-energy resolution

HYDJET++ event

S/(S+B)efficiency

energy resolution

PYTHIA8 Dijet event Jet

Finding

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HYDJET++(HYDrodynamics plus

JETs) HYDJET++ is one of the event generators for

relativistic Heavy Ion Collision. The soft part : "thermal” hadronic state FASTMC The hard part : hard part of

HYDJET(PYTHIA6.4xx + PYQUEN1.5)

I choose the option “Hydro+ Jet (without quenching)”,and assume these events don’t have high energy Jets.

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CellJet’(Jet Finding Algorithm)

1. divide η-φ space in [0.1, 0.1] cells2. calculate transverse energy (eTcell) in each cell3. BKG selection (BKG=〈 eTcell〉

(eTcell<“threshold”)×(1+v2*cos(dφ)) )4. subtract BKG from eTcell (eTcell = eTcell –

BKG(centrality,φ)) 5. select candidates of jet-seed by eTcell > ”eTseed”6. calculate sum of eTcell in the cone(with “Cone-

Radius”) which center positioned at jet-seed (eTsum=ΣeTcell)

7. requirement : eTsum>”Min-eT”8. define the survivors as found jets

input parameters in CellJet :“threshold”, “Cone-Radius”, “Min-eT” and “eT-seed”

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threshold, coneRadius

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Cone

-Rad

ius

Threshold[GeV]

100GeV Jet 0-

10%30-40%

60-75%

Single jet resolution = ΔeT/eT select “Cone-Radius” and “threshold” with better resolution

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S/(S+B)efficiencyS/

(S+B)*effciency

Min-eT, eTseed• S/(S+B) ≡ Nreal/Nfound

• efficiency ≡ Nreal/Nembed

Nreal : # of found Back-to-Back Jets from PYTHIA DijetNfound : # of found Back-to-Back Jets by CellJet’Nembed : # of embedded DiJet (1)

definition of Back-to-Back Jet|dφ-π|<0.3

Comparison with PYTHIA-Jetsdistance btw embedded jet and

found jet < 0.15|eTpythia jet-eTfound jet|/eTpythia jet <

0.45

Select “Min-eT” and “eTseed” with better S/(S+B)*efficiency

In other centrality and other energy,the same trend is seen.

0-10%50-100GeV

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parameter settingparameter valuethreshold 15GeVConeRadius centrality functioneT-seed 50GeV*0.15 = 7.5GeVMin-eT 50GeV*0.5 = 25GeV

50GeV Jet configurationeT-seed & Min-eT should be

constant

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Energy ResolutionSingle Jet Energy

Resolution

compare found Jet eT with embeded Jet eT

Parton Energy Resolution

compare found Jet eT with primary parton eT

25%(central) 12%(peripheral)

30%(central)17%(peripheral)

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DiJet: S/(S+B), efficiency

mid-central~peripheral Good S/(S+B) and efficiency

central ~40% noise

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Summary / Plan J-Cal performance at Back-to-Back Jet physics

For Back-to-Back Jet physics, Calorimeter opposite side of ALICE EMCal(J-Cal) will give good performance.

How to find Back-to-Back Jets in Heavy Ion Experiment try “CellJet’” algorithm search other better method

primary-parton energy estimation energy resolution ~30%(central) with Jet-Quenching?

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backup slide

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coplanarityR=0.2 R=1.0

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energy balanceR=0.2 R=1.0

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parton energy resolution

R=0.2 R=1.0

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quark jet fraction fraction of quark/gluon which is created from most

hard pp collisions (sqrt(s)=5.5TeV) as a function of pTHat

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Energy Resolution correlation btw PYTHIA eTJet & PYTHIA+HYDJET inclusive eTJet

calculate the correction factor resolution = RMS of “(eTPYTHIA_Jet – eT’corrected)/(eTPYTHIA_Jet)” select “Cone-Radius” and “threshold” with better resolution

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threshold, coneRadius

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50GeV

100GeV

150GeV

0-10%

20-30%

40-50% 60-75%

Cone

-Rad

ius

Threshold[GeV]

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Min-eT, eTseed50~100G

eV

100~150GeV

150~200GeV

0-10%

20-30%

40-50% 60-75%

Min-eT/pTHat

eTse

ed/M

in-e

T

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ConeRadius Estimation in PbPb

with Charged Particles pT>2GeV particles PYTHIA + HYJING

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Jet Energy Resolution

in pp Using charged Particles Jet (not Parton) Energy resolution Jet energy : sum of energy All Final particles in R=1.