Hadron production in hard scattering Event Generator GEANT

Hadron production in hard scattering Event Generator GEANT

JETSET: Single particle production in hard scattering High probability to detect leading hadron in the forward detector DIS: Q 2>1 Ge. V 2 W 2>4 Ge. V 2 (10) y<0. 85 LUND Fragmentation Functions - Before - After Target remnant quark The primary hadrons produced in string fragmentation come from the string as a whole, rather than from an individual parton.

LUND Fragmentation Functions HERMES low PT PDF side: gaussian <k. T 2> high PT

HERMES: Fragmentation and Multiplicities Tuning of JETSET FF parameters to multiplicities in acceptance Multiplicities p+ p- HERMES-MC Tune-2 Tune-3 JETSET-std MC: PYTHIA in combination with JETSET; PDF: CTEQ-6 DATA: unpolarised p-target z 2>10 Ge. V 2, z>0. 2, 2<ph<15 Ge. V Q 2 > 1 Ge. V 2, W P K- K+ z T K+ K- PT

CLAS data vs LUND-MC 0. 5<z<0. 8 CLAS data (4. 3 Ge. V) and LUND-MC comparison LUND-MC tuned at higher energies Q 2 > 1 Ge. V 2, W 2>4 Ge. V 2, z>0. 5, y<0. 85

LUND event-II Particle number in the event charge and status Lund ID Parent and first daughter line numbers K*+ px py pz Momentum in Ge. V, E m L K+ p p- g ep -> e’LK*+ -> e’ p-p. K+p 0→ 2 g Vx Vy Vz, Vertex in cm

Exclusive r+ at 6 Ge. V PYTIA-6 + 2 p

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

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

Background studies for CLAS with IC Background accounting procedure tested with e 1 dvcs CLAS data IC edge target shielding GEANT+background CLAS GEANT-MC + background consistent with data

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

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

LUND MC with Long. Pol. Target: SSA for p+ CLAS-Data sinf and sin 2 f moments arising from the Collins effect added in MC using predictions from Efremov et al. Phys. Rev. D 67: 063511, 2003 f distributions from MC vs 5. 7 CLAS data. Fiducial cuts on e, p+ and smearing applied. Simulated and reconstructed SSA moments consistent

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.

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