Candidate Level Comparisons

Objective:

Show that, for an important set of kinematic variable distributions, the full QCD 2->2 Pythia MC sample matches the data.  This justifies using this MC sample to calculate 'true' distributions and hence correction factors.  All plots below contain information from all candidates, that is, all diphoton pairs that pass the cuts below.

Details:

    Data (always black points) Vs. T2_platinum MC (always red) (see here)

Cuts:

 

• Events pass L2gamma software trigger and (for data) online trigger.
• candidate pt > 5.5
• charged track veto
• at least one good strip in each smd plane
• Z vertex found
• | Z vertex | < 60 cm

 

Plots:

1a)

The above plot shows the Zgg distribution ((E1 - E2)/(E1 + E2)) for data (black) and (MC).  The MC is normalized to the data (total integral.)  Despite what the title says this plot is not vs. pt, it is integrated over all values of pt.

1b)

 

The above left shows Data/MC for Zgg between 0 and 1.  The results have been fit to a flat line and the results of that fit are seen in the box above.  The above right shows the histogram projection of the Data/MC and that has been fit to a guasian; the results of that fit are shown.

 

2a)

The above plot shows the particle eta for data pions (black) and MC pions (red).  The MC is normalized to the data (total integral.)  As you can see, there is a small discrepancy between the two histograms at negative values of particle eta.  This could be a symptom of only using one status table for the MC while the data uses a number of status tables in towers and SMD.

2b)

The above left plot shows Data/MC for particle eta, which is fit to a flat line.  The Y axis on this plot has been truncated at 2.5 to show the relevant region (-1,1).  the outer limits of this plot have points with values greater than 4.  The above right shows a profile histogram of the left plot fit to a gaussian.  Note again that some entries are lost to the far right on this plot.

3)

The above plot shows detector eta for data (black) and MC (red).  Again we see a slight discrepancy at negative values of eta.

3b)

The above left shows Data/MC for detector eta, and this has been fit to a flat line.  Again note that the Y axis has been truncated to show detail in the relevant range.  The above right shows a profile histogram of the left plot and has been fit to a guassian.

 4)

 

 

The above plot shows the raw yields (not background subtracted) for data (black) and MC (red) where raw yield is the number of inclusive counts passing all cuts with .08 < inv mass < .25 and Zgg < 0.7.  There is a clear 'turn on' curve near the trigger threshold, and the MC follows the data very nicely.  For more information about the individual mass peaks see here.

 

Conclusions:

The Monte Carlo sample clearly recreates the data in the above distributions.  There are slight discrepancies in the eta distributions, but they shouldn't preclude using this sample to calculate correction factors for the cross section measurement.