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test, according to Jan's request

this is a test entry
don't pay too much attention to it
here's another line
and another
not less than 5, Jan commands
so I do 6
 

PID Stability

I plot the nSigmaPion distributions for the 859 ppProduction and ppProductionMinBias runs passing 2005 jet QA. Tracks included in each histogram passed the following cuts:

  • pT > 2.0
  • |eta| < 1.0
  • |dcaG| < 1.0
  • nFitPoints > 25

Here’s a summary of the means from each run:

PID summary

I’ve also attached a PDF of the run-by-run plots at the bottom of the page (pid-stability.pdf). The group of runs around index 800 correspond to fill 7305 (highlighted in red on page 53 of the pid-stability PDF), and the large jump around index 95 coincides with the beginning of fill 7048.

I’m not so concerned about the latter group, as fills 7048 and 7055 were already excluded from analysis by the RHIC Polarimetry group. I am wondering, though, if it’s safe to analyze fill 7305. I tried the triple-Gaussian fit for data from this fill, which results in a 0.7 sigma offset for the pions. The Chi2/dof is certainly good enough:

F7305 recalibration

I went ahead and did these fits for every fill in my analysis and posted the results at the bottom of the page (pid-by-fill.pdf). The fit parameters were configured as

fit = ROOT.TF1('fit','gaus(0)+gaus(3)+gaus(6)', -6.0, 6.0)
fit.SetParameter(0, h.GetMaximum() * 0.9)
fit.SetParameter(1, 0.0)
fit.SetParameter(2, 1.0)
fit.SetParameter(3, h.GetMaximum() * 0.5)
fit.SetParameter(4, -1.0)
fit.SetParameter(5, 1.0)
fit.SetParameter(6, h.GetMaximum() * 0.05)
fit.SetParameter(7, 2.)
fit.SetParameter(8, 1.0)

I’m a little surprised at the fit results for these fills (i.e. pion means are often around -0.2 or lower), but I’m no expert when it comes to this stuff. Here’s a summary plot of means for the pion Gaussians in each of the fill-by-fill fits:

Fill Summary

Summary

nSigmaPion distributions are well-described in all cases by a triple-Gaussian fit, and are generally stable within a given RHIC fill. A few fills have distributions which appear to be shifted relative to the remainder of the dataset, in particular F7305.

Update 2008-02-05

I decided to change the PID selection window in my analysis to use the results of these fill-by-fill fits. Now, instead of using a fixed [-1,2] window in nSigmaPion, I center the window on my calculated pion mean for that fill, and the width of the window is normalized by the width of the pion Gaussian. The overall effect is hardly noticeable: pion identification efficiency (based on these fits) improves by 0.6%, and background p/K/e contamination drops by an even smaller amount. The actual numbers using my final runlist are

Efficiency: 81.9%
Background: 9.1%

Update 2008-03-07

I had been using the RunLog_onl DB to get fill/run mappings. I believe some entries in this database are incorrect; for more information, see this HN post. I just updated the results on this page to reflect what I now believe to be the correct mappings for fills 7127, 7128, 7129, 7134, 7136, and 7138.

Data Sample

WORK IN PROGRESS

The analysis uses 839 runs, totaling 7,965,962 events (MB|JP1|JP2), 2,073,334 pions, and 2.2 pb^-1 of integrated luminosity. The run QA effort builds on the work of the jetfinding group, documented here. In addition to the QA requirements imposed by the jet group, I checked the stability of the dE/dx distributions. That work is documented here, but in summary I concluded that the PID information is usable in all the runs that passed jet QA, and that the PID window should be centered on the mean of the pion Gaussian for each fill.

Event Cuts

  • BBC online time difference in [7,8,9]
  • spin DB (StSpinDbMaker) says spin information is OK for bunch crossing
  • online trigger in [96011, 96221, 96233]
  • offline trigger emulator agrees with online trigger decision

Track Cuts

  • pT > 2.0
  • |eta| < 1.0
  • |dcaG| < 1.0
  • nFitPoints > 25
  • nSigmaPion in the range [-1,2] * sigma centered on pion mean

Ideas for more information here

  • event counts by trigger and/or trigger overlap
  • histogram showing effect of each cut

Photon Analysis Progress for the week of 1/21/08-1/25/08

There were two issues to be dealt with this week.  First, we had trouble extracting the calorimeter information from the MuDst, which did not seem to have an StEmcCollection.  Initially we b

BEMC MIP peaks by eta ring for 2008 (FastOffline)

Using some 2008 FastOffline data (production_dAu2008), approximately 420k events, I produced looked for the mip peak in each eta ring. The spectra clean up nicely with the correct pedestals.

Running Spiffy Single Particle MC

One of the difficulties in using single-particle monte carlo in analysis is that tracking will

Kalman 102 : 1D tracking

I have developed some interest in Kalman tracking.

Found this writeup 

A summary of our Photon XS Measurement Efforts

The starting points for our work attempting to measure the photon cross section were a set of papers (OPAL: hep-ex/0305075, ZEUS:

Investigating pT behavior in our MC

The spill-over plots from the previous post raise the question of why the partonic pT spreads so much.  These new plots show more detail on the pT contributions at each stage of the event.

2006 L2Gamma EEmc trigger simulation

12/17/2007

1. Specify runs / timestamps to simulate