Spin PWG

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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:

all<em>bg</em>subtracted
sigma<em>bg</em>subtracted

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

 Goal:

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

Justification:

2008.12.09 pp Run 8 vs. Run 6 SMD shower shapes

Ilya Selyuzhenkov December 09, 2008

Yield Extraction and Correction systematic

Goal:

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
Etc/GMT-4
Thursday, 6 November 2008
phone 317-263-8800 1 077795# 1, at 17:00 (GMT), duration : 01:30

Agenda posted at meeting list

Run 9 triggering

Carl has prepared a trigger description for 200 GeV.

Run 9 Preparation and Jobs List

Green = complete   Red = currently critical

SPIN 2008 Talk for Neutral Pions

Hi all-

My Spin 2008 talk and proceedings can be found below.

 Update:

v2 reflects updates based on comments from SPIN pwg and others

Concerning the 'floating' mass peak and Zgg

 Objective:

Explore the pt-dependent mean mass position in data and MC and perhaps draw some conclusions about the quality of our simulations.

Details:

Special Attention Ought to be Paid to Zgg

The collaboration has concerns about the SMD, and not without reason.  They, they SMDs, have been notoriously hard to understand and model.

Mean pT in z bins

I looked into the mean transverse momentum for pions and jets in each of my z bins. First, here’s a comparison of data (black points) and Monte Carlo (red lines) for the BJP1 trigger:

It looks good to me, so I went on to compare simulations for jet patch and minimum-bias triggers:

In hindsight, this plot makes perfect sense — the trigger hardens the pT spectrum for the jets, so each JP z bin (which integrates over 10-25 GeV) has a higher average jet p_{T} than the MB version.

Now, this 3 GeV p_{T} shift means that we’re biasing the sample in each z bin towards higher x. This is almost certainly the source of the observed trigger bias in the Monte Carlo asymmetries for π+. So, what’s the next step?