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Slow particles analysis. Acceptance/efficiency factors Embedding tracks Raw 1/N ev 1/ p T d 2 N/d dp T at mid-rapidity PR01, PR00 data Hijing data reconstruction STAR spectra todo list. F. X[cm]. E. D. C. B. A. Z[cm]. Algorithm.
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Slow particles analysis • Acceptance/efficiency factors • Embedding tracks • Raw 1/Nev1/pT d2N/ddpT at mid-rapidity • PR01, PR00 data • Hijing data reconstruction • STAR spectra • todo list
F X[cm] E D C B A Z[cm] Algorithm Algorithm is tuned for finding particles which range out in plane E To find efficiency and acceptance embedding single tracks within full MC events is done within “window”: x x p window size depends on Zvert centrality bin: 15% Z vertex: -7cm to 15cm each arm done separately adding tracks until reconstruction is successful (with 4 or 5 hits / track)
Angular Acceptance Zvert Zvert primary cos, uniformly distributed between bands.
Momenta Ranges momentum p,p K+,K- +,- Zvert momenta uniformly distributed within bands
Efficiency/acceptance examples 1/eff within embedding window for pions within full 4/angular window size SpecN o SpecP Zvert Zvert
Experimental check for efficiency factors SpecN o SpecP Zvert Zvert distributions of reconstructed pions scaled by arm-efficiency
Number of reconstructed tracks in PR01 and PR00 data Selected 15% most central with Zvert from -7cm to 15cm PR01: 216000 ev. PR00: 25800 ev.
dE/dx for reconstructed pions: PR01 vs MC after energy recalibration by 1.13
Raw 1/Nev1/pT d2N/ddpT at mid-rapidity ||<0.25, Zvert from 5cm to 15cm, Nev=11700/ 97900 for PR00/PR01 Enough data only for pion PR01 sample at midrapidity
Reconstruction of PR01 MC data 15% centrality, Zvert: -7cm-15cm Nev=18600 primary/all = 0.54 slow pion = pion having hits in A-D or A-E
Reconstruction of PR00 MC data Nev=12400 primary/all = 0.59
STAR 1/Nev1/pT d2N/ddpT for h-+h+ 130GeV centrality 5% ||<0.1 A(1+pT/p0)n pT[GeV/c] crude estimate of PHOBOS -point @ 52MeV: 7700 * 0.59(Hijing bkg) * 1.17(15%->6%) = 5300
todo • Calculation of background factors - embedding of , K, p in proportions to increase statistics of bkg tracks. • Recalculate efficiency and bkg factors with embedding into experimental data. • Reconstruction of more PR01 data (crucial for K , p and negative ptls).