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Hadron production in hard scattering Event GeneratorGEANT.

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Presentation on theme: "Hadron production in hard scattering Event GeneratorGEANT."— Presentation transcript:

1 Hadron production in hard scattering Event GeneratorGEANT

2 JETSET:Single particle production in hard scattering High probability to detect leading hadron in the forward detector The primary hadrons produced in string fragmentation come from the string as a whole, rather than from an individual parton. - Before - After quarkTarget remnant DIS: Q 2 >1GeV 2 W 2 >4 GeV 2 (10) y<0.85 LUND Fragmentation Functions

3 HERMES low P T high P T PDF side: gaussian

4 z MC: PYTHIA in combination with JETSET; PDF:CTEQ-6 DATA: unpolarised p-target Q 2 > 1GeV 2, W 2 >10 GeV 2, z>0.2, 2 1GeV 2, W 2 >10 GeV 2, z>0.2, 2

5 CLAS data vs LUND-MC CLAS data (4.3GeV) and LUND-MC comparison 0.5 1GeV 2, W 2 >4 GeV 2, z>0.5,y 1GeV 2, W 2 >4 GeV 2, z>0.5,y<0.85

6 LUND event-II Lund ID ep -> e + -> e pK Particle number in the event Parent and first daughter line numbers p K*+ charge and status p x p y p z Momentum in GeV, E m V x V y V z, Vertex in cm K

7 Exclusive + at 6 GeV PYTIA-6 + 2

8 Exclusive production background from PYTHIA Pions from string (direct) present the lower limit for current fragmentation events Filled (open) symbols represent pions from exclusive (all) vector mesons. electron 0 sample clean at large z (non-string pions are mainly from semi-inclusive +, )

9 GEANT simulation Angular acceptance for charged tracks for CLAS+IC configuration Maximum angle ~50 o Minimum angle ~14 o 13 o 50 o

10 Background studies for CLAS with IC CLAS data GEANT+background target IC edge shielding Background accounting procedure tested with e1dvcs CLAS GEANT-MC + background consistent with data

11 Acceptance moments from MC generated reconstructed Extract acceptance moments from MC CLAS HERMES

12 3 methods to analize the azimuthal moments fit I II III Different methods have different sensitivity to acceptance corrections

13 LUND MC with Long. Pol. Target: SSA for + sin and sin2 moments arising from the Collins effect added in MC using predictions from Efremov et al. Phys.Rev.D67:063511,2003 Simulated and reconstructed SSA moments consistent distributions from MC vs 5.7 CLAS data. Fiducial cuts on e, + and smearing applied. CLAS-Data

14 Summary Monte-Carlo generators have become an essential tool for feasibility studies, simulation of anticipated physics and background rates, acceptance and other corrections. Detailed simulation of processes of interest is crucial to keep under control systematic errors due to, both detector and physics background contributions LUND-MC combined with GEANT-simulation of detector response provide test of procedures for global analysis and extraction of physics observables.

15 Support slides….

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