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

1. black circles: pp2006 data
2. open green: MC-QCD-TuneA, partonic pt 4-35
3. solid green:  MC-QCD-Perugia0, partonic pt 4-35
4. open red MC-prompt-photon-TuneA, partonic pt 3-35
5. solid red MC-prompt-photon-Perugia0, partonic pt 3-35

Event selection

1. di-jets from the cone jet-finder algorithm
2. photon and jet are opposite in phi:
      cos (phi_gamma-phi_jet) < -0.8
3. pt away side jet > 5GeV
4. detector eta of the away side jet: |eta_jet_det| < 0.8
5. data : L2e-gamma triggered events
6. Monte-Carlo: emulated L2e-gamma triggered condition
7. 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)