1 / 20

Efforts by Yonsei towards ALICE

Efforts by Yonsei towards ALICE. Y. Kwon (Yonsei Univ.). NA. LHC. SPS. ALICE. WA. pQCD & factorization?. (for sufficiently large scale). Factorization:. hadron. High pT particle. hadron. parton distribution functions x a = momentum fraction of parton a in hadron A.

alyn
Download Presentation

Efforts by Yonsei towards ALICE

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. Efforts by Yonsei towards ALICE Y. Kwon (Yonsei Univ.)

  2. NA LHC SPS ALICE WA

  3. pQCD & factorization? (for sufficiently large scale) • Factorization: hadron High pT particle hadron parton distribution functions xa = momentum fraction of parton a in hadron A cross-section at parton level e.g.: fragmentation z = fraction of c momentum to hadron D cross-section at hadron level

  4. 2 by 2 parton kinematics?

  5. Good agreement with NLO pQCD Important baseline for Au+Au PbSc Direct Photons in p+p

  6. thermal: Decay photons hard: Schematic Photon Spectrum in Au+Au

  7. e+ Compton e- g* q g g g q p0 p0 e+ g* g e- Compton g q g q The Idea • Start from Dalitz decay • Calculate invariant mass distribution of Dalitz pairs invariant mass of Dalitz pair invariant mass of Dalitz pair invariant mass of virtual photon invariant mass of virtual photon form factor form factor phase space factor phase space factor • Now direct photons • Any source of real g produces virtual gwith very low mass • Rate and mass distribution ~ similar • No phase space factor for mee<< pT photon

  8. Method • Material conversion pairs removed by analysis cut • Combinatorics removed by mixed events 0-30 90-140 200-300 140-200 MeV Rdata ÷ ÷ ÷ • Calculate ratios of various Minv bins to lowest one: Rdata • If no direct photons: ratios correspond to Dalitz decays • If excess:direct photons

  9. g*direct/g*inclusive 0-20 % Significant 10% excess of very-low-mass virtual direct photons

  10. ALICE Set-up TRD Size: 16 x 26 meters Weight: 10,000 tons TOF HMPID ITS PMD Muon Arm PHOS TPC

  11. TRD(Transition Radiation Detector) • |η|<0.9, 45°<θ<135° • 18 supermodules in Φ sector • 6 Radial layers • 5 z-longitudinal stack  total 540 chambers  750m² active area  28m³ of gas • In total 1.18 million read-out channels FROM C. Adler -- Hadron Collider Physics, Les Diablerets, 4-9 July 2005

  12. TRD(Transition Radiation Detector)(What is transition radiation?) “Transition radiation is emitted whenever a charged particle crosses an interface between two media with different dielectric functions.” - L.Durand, Phys. Rev. D 11, 89(1975) • Predicted : Ginzburg & Frank, 1946 • Observed : Goldsmith & Jelly, 1959(optical) • It’s sizeable(X-rays) for relativistic particles. FROM A. Andronic -- an overview for students, GSI, Feb. 6th, 2007

  13. TRD working principle The total energy loss by TR for charged particle : depends on its Lorentz factor γ = E / mc2 Usefullness of TR : For discrimination the electron from hadons in the momentum range between 1GeV/c and 100GeV/c. Cut through one side of a TRD readout chamber FROM P. Shukla -- ICPA-QGP'05, Kolkata, 8-12

  14. 1 Event signals of Electron and Pion FROM P. Shukla -- ICPA-QGP'05, Kolkata, 8-12 February 2005

  15. TRD working principle FROM P. Shukla -- ICPA-QGP'05, Kolkata, 8-12 February 2005

  16. Pattern Recognition? Neural network! Neural-network - A simple Modeling of the biological neuron - Being used in various fields for data analysis and classification - Examples : Image analysis, Financial movement’s prediction, Sales forecast, Particle physics

  17. Current Neural Network Input Hidden layer output Adc[1] Adc[2] Pion Or electron Adc[3] Adc[20]

  18. Comparison of methods

  19. Summary • We consider • LHC : New frontier for perturbative QCD, • Direct g : an interesting subject, • Virtual g : the best path to measurement, • TRD : hardware for electron IDentification, • Neural network : software for electron ID. • Our endeavor just started… Where would we reach in the end?

More Related