Spin PWG

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CNI summary analysis from fill 10373 to fill 10507

       In attachment shows the compare between polarimeter 1 and polarimeter 2 for blue (yellow) beam.  And also

Collaboration Meeting Presentation and wrap up.

 Attached is the presentation I gave at the collaboration meeting in late March.

Integral Delta G Study

 Using Werner's code I calculated A_LL for pi0 production over my eta range for 15 different integral values of Delta G.

All Errors

The plot below shows the total errors, statistical and systematic, for the cross section measurement.  The inner tick marks on the error bars represent the statistical errors.

CNI p-carbon polarimeters data comparison from fill 10300 to fill 10368

         The comparization is between blue1 and blue2, offline and onl

CNI p-carbon polarimetry

  sample plots of daily analysis:

  fill 10332:

New PID Asymmetries

Update: I coded up the statistical uncertainty calculation incorrectly in this post. I forgot to divide by the purity! The optimal cuts changed by a lot when I fixed that error. I also generalized the formula to account for the presence of signal in the sidebands, and I included the lowest p_{T} bin in the analysis. For more details see New PID Asymmetries II. Bottom Line — the results on this page are wrong!

In an earlier post I explained the new method for calculating identified particle yields that I’m using in my A_{LL} analysis. I began that study because I planned to calculate A_{LL} differently than I had been in the past. Specifically, I wanted to incorporate the proton/kaon/electron backgrounds into the statistical uncertainty instead of assigning a separate (statistics-limited) systematic uncertainty to account for their presence. I’m using the following formulas for A_{LL} and its statistical uncertainty:


where the p_{T}-dependent background fractions are defined as:

I wrote a small function to estimate the statistical precision on A_{LL} given the p_{T} bin, pion acceptance window, and sideband acceptance windows. I didn’t care about the absolute statistical precision, so I just used 1/sqrt(N) for the uncertainty on each A_{LL}. I used Minuit2 to minimize this function and extract the optimal acceptance windows, with the constraint that the purity in each sideband is never below 90%. In principle, this approach would yield four momentum-dependent cuts. In practice, the p+K sideband cut and the left side of the pion acceptance window only had a small momentum dependence, so for the sake of simplicity I keep them fixed. I also choose to fix the other two cuts in each p_{T} bin instead of letting them vary with momentum. In the end I employ the following cuts

pT binπ windowmax p+Kmin electron
3.18 - 4.56(-1.90, 2.40)-1.902.40
4.56 - 6.32(-1.90, 2.25)-1.902.50
6.32 - 8.80(-1.90, 2.00)-1.902.60
8.80 - 12.84(-1.90, 1.50)-1.902.60

These cuts are significantly wider than the (-1.0, 2.0) acceptance window I had been using in the past. Apparently the reduction in purity is more than offset by the extra efficiency.

The electron side of the acceptance window is interesting. As momentum increases the pion band moves closer to the electron band. As a result, we need to move the electron sideband cut further out to maintain the 90% purity. This cuts down on the electron background A_{LL} statistics. The minimizer compensates for that uncertainty by restricting the right side of the pion acceptance window and thus reducing the electron background fraction.

I compared the uncertainties obtained by the minimizer with the uncertainties from my old method (a flat (-1.0, 2.0) cut that does not subtract out the background asymmetries). It turns out that the uncertainties from the new method are actually smaller in every p_{T} bin. I haven’t calculated a systematic uncertainty for this method, but if there is one it will be far smaller than the systematic from the old method (~ background fraction * sigma of background A_{LL}). In other words, using the new method is a no-brainer.

Oh, and one plot, just because I think it’s pretty:

Preliminary Cross Section Plot

 The proposed final version of the cross section plot would look like this.


2009.03.02 Application of the neural network for the cut optimization (zero try)

Multilayer perceptron (feedforward neural networks)

Multilayer perceptron (MLP) is

l2-gamma EEMC monitoring

Instructions on how to produce eemc-l2-gamma monitoring plots by hands

  • Get l2 software
    Currently copied from ~rcorliss/l2/official-2009a

Run 9 commissioning plan

Run 9 500 GeV Commission plan (start of draft)  Not necessarily time ordered
or prioritized

Establish collisions

Spin PWG meeting (2/12/09)

The PDF for my slides is linked below.



BEMC Calibration Uncertainty


 To calculate the systematic uncertainty on the cross section due to the BEMC calibration uncertainty.


2008.12.09 pp Run 8 vs. Run 6 SMD shower shapes

Ilya Selyuzhenkov December 09, 2008

Yield Extraction and Correction systematic


Fully Corrected Yields

 Ok, now we're cooking.  Most of the ingredients are in place.

Reconstruction and Trigger Efficiency Correction Factor

 Now that I have my raw pion spectrum (see here) I need to proceed

Jigsaw Inv Mass Plots (final)

 As noted here and here, the pion peak is difficult to model using single-particle MC.  In single particle studies, the pion inv mass peak is reconstructed to narrow.

BEMC Related Studies

My initial attempt at pinpointing the causes of the 'floating' pion mass examined, as possible causes, the fit function, an artificial increase in the opening angle, and the BEMC energy resolution.

Spin Physcs PWG

2008-11-06 12:00
2008-11-06 13:30
Thursday, 6 November 2008
phone 317-263-8800 1 077795# 1, at 17:00 (GMT), duration : 01:30

Agenda posted at meeting list