1 / 23

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

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 .

bian
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


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

  2. 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-partonenergy Simulation with PYTHIA and HYDJET++

  3. Jet Finding in pp • CellJet algorithm • track by track energy smearing • charged particles : ALICE TPC+ITS momentum resolution(assumepion mass) • neutral particles : ALICE EMCal energy resolution • find jet using Visible(neutral+charged) or Charged particles

  4. 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 = • partonenergy resolution = ΔeT/eT jet1 Coplanarity, energy balance and energy resolution are improved by installation of Calorimeter. jet2

  5. Jet Finding in Pb+Pb • Generate samples of PYTHIA Dijets using PYTHIA8 CellJetalgorithm(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 PYTHIA8 Dijet event S/(S+B) efficiency energy resolution Jet Finding HYDJET++ event

  6. 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.

  7. CellJet’(Jet Finding Algorithm) • divide η-φ space in [0.1, 0.1] cells • calculate transverse energy (eTcell) in each cell • BKG selection (BKG=〈eTcell〉(eTcell<“threshold”)×(1+v2*cos(dφ)) ) • subtract BKG from eTcell (eTcell = eTcell – BKG(centrality,φ)) • select candidates of jet-seed by eTcell > ”eTseed” • calculate sum of eTcell in the cone(with “Cone-Radius”) which center positioned at jet-seed (eTsum=ΣeTcell) • requirement : eTsum>”Min-eT” • define the survivors as found jets input parameters in CellJet : “threshold”, “Cone-Radius”, “Min-eT” and “eT-seed”

  8. threshold, coneRadius • Single jet resolution = ΔeT/eT • select “Cone-Radius” and “threshold” with better resolution 100GeV Jet 0-10% 30-40% 60-75% Cone-Radius Threshold[GeV]

  9. Min-eT, eTseed Nreal : # of foundBack-to-Back Jetsfrom PYTHIA Dijet Nfound : # of found Back-to-Back Jets by CellJet’ Nembed : # of embeddedDiJet (1) • S/(S+B) ≡ Nreal/Nfound • efficiency ≡ Nreal/Nembed Select “Min-eT” and “eTseed” with better S/(S+B)*efficiency definition of Back-to-Back Jet |dφ-π|<0.3 Comparison with PYTHIA-Jets distance btw embedded jet and found jet < 0.15 |eTpythia jet-eTfound jet|/eTpythia jet < 0.45 0-10% 50-100GeV S/(S+B) efficiency S/(S+B)*effciency In other centrality and other energy, the same trend is seen.

  10. parameter setting 50GeV Jet configuration eT-seed & Min-eT should be constant

  11. Energy Resolution Single Jet Energy Resolution Parton Energy Resolution compare found Jet eT with primary parton eT • compare found Jet eT with embeded Jet eT 30%(central) 17%(peripheral) 25%(central) 12%(peripheral)

  12. DiJet: S/(S+B), efficiency • mid-central~peripheral • Good S/(S+B) and efficiency • central • ~40% noise

  13. 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?

  14. backup slide

  15. coplanarity R=0.2 R=1.0

  16. energy balance R=0.2 R=1.0

  17. parton energy resolution R=0.2 R=1.0

  18. quark jet fraction • fraction of quark/gluon which is created from most hard pp collisions (sqrt(s)=5.5TeV) as a function of pTHat

  19. 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

  20. 60-75% 40-50% 20-30% 0-10% 50GeV threshold, coneRadius 100GeV Cone-Radius 150GeV Threshold[GeV]

  21. 0-10% 20-30% 40-50% 60-75% 50~100GeV Min-eT, eTseed 100~150GeV eTseed/Min-eT 150~200GeV Min-eT/pTHat

  22. ConeRadius Estimation in PbPb • with Charged Particles • pT>2GeV particles • PYTHIA + HYJING

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

More Related