2010.06.30 Py-tunes (GEANT+L2e-gamma trigger) vs. Run 6 data
Related posts
- Michael's Perugia 0, Pro-pT0, and CDF Tune A comparison
- Previous comparison without trigger condition in simulations
- Tests of L2e-gamma trigger emulation with single photon Monte-Carlo
Data samples and colour coding
- black circles: pp2006 data
- open green: MC-QCD-TuneA, partonic pt 4-35
- solid green: MC-QCD-Perugia0, partonic pt 4-35
- open red MC-prompt-photon-TuneA, partonic pt 3-35
- solid red MC-prompt-photon-Perugia0, partonic pt 3-35
Event selection
- di-jets from the cone jet-finder algorithm
- photon and jet are opposite in phi:
cos (phi_gamma-phi_jet) < -0.8 - pt away side jet > 5GeV
- detector eta of the away side jet: |eta_jet_det| < 0.8
- data : L2e-gamma triggered events
- Monte-Carlo: emulated L2e-gamma triggered condition
- MC scaled to 3.164^pb based on Pythia luminosity (no fudge factors)
Figure 1: Reconstructed photon candidate pt (no pt_gamma cut, pt_jet > 5GeV)
L2e-gamma condition simulated in Monte-Carlo
Figure 2: Yield ratios (no pt_gamma cut, pt_jet > 5GeV)
Black: data[pp2006] / QCD[Perigia0]
Green: QCD[Perigia0] / QCD[CDF-Tune-A]
Red: g-jet[Perigia0] / g-jet[CDF-Tune-A]
Figure 3: Vertex z distribution (pt_gamma>7GeV, pt_jet > 5GeV)
Figure 4: Simulation yield vs. partonic pt (no pt_gamma cut, pt_jet > 5GeV)
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