The STAR experiment

In the 2003+2004 jet cross section and A_LL paper we quoted a 5% systematic uncertainty on the absolute BTOW calibration.  For the 2005 jet A_LL paper there is some interest in reducing the size of this systematic.

I went back to the electron ntuple used to set the absolute gains and started making some additional plots.  Here's an investigation of E_{tower} / p_{track} versus track momentum.  I only included tracks passing directly through the center of the tower (R<0.003) where the correction from shower leakage is effectively zero.

Full set of electron cuts (overall momentum acceptance 1.5 < p < 20.):

dedx>3.5 && dedx<4.5 && status==1 && np>25 && adc>2*rms && r<0.003 && id<2401

I forgot to impose a vertex constraint on these posted plots, but when I did require |vz| < 30 the central values didn't really move at all.




Here are the individual slices in track momentum used to obtain the points on that plot:







Electrons with momentum up to 20 GeV were accepted in the original sample, but there are only ~300 of them above 6 GeV and the distribution is actually rather ugly.  Integrating over the full momentum range yields a E/p measurement of 0.9978 +- 0.0023, but as you can see the contributions from invididual momentum slices scatter around 1.0 by as much as 4.5%

Next Steps?  -- I'm thinking of slicing versus eta and maybe R (distance from center of tower).

I ran a couple of TStopwatch tests on the Run 5 common trees.  Here are the specs:

Hardware:  Core Duo laptop, 2.16 Ghz

Trees:  805 runs, 26.2M events, 4.4 GB on disk

Languages:  CINT, Python, compliled C++

I also tested the impact of using a TEventList to select the ~11M JP1 and JP2 events needed to plot deta and dphi for pions and jets.  Here's a table of the results.  The times listed are CPU seconds and real seconds:

	Chain init  + TEventList generation	Process TEventList
CINT	156 / 247	1664 / 1909
Python	156 / 257	1255 / 1565
Compiled C++	154 / 249	877 / 1209

I tried the Python code without using a TEventList.  The chain initialization dropped down to 50/70 seconds, but reading in all 26M events took me 1889/2183 seconds.  In the end the TEventList was definitely worth it, even though it took 3 minutes to construct one.

Conclusions:

1. Use a TEventList.  My selection criteria weren't very restrictive (event fired JP1 or JP2), but I cut my processing time by > 30%.
2. I had already compiled the dictionaries for the various classes and the reader in every case, but this small macro still got a strong performance boost from compilation.  I was surprised to see that the Python code was closer to compiled in performance than CINT.
   

Time	Talk	Presenter
16:00	Embedding description and policy (draft?) ( 00:10 ) 1 file	Jerome Lauret (BNL)

• Cu+Cu re-production- 87.5 days

  • Cu+Cu 62 GeV production – 15+ days

PREFACE

This is a report of the current status of trying to understand the distortions due to the electrical short(s) in the TPC inner field cage east (IFCE) in the current run (for historical info, see Field Cage Shorts

See http://www.star.bnl.gov/protected/strange/salur/EPOS/

See Aneta's recent link here:

http://www.star.bnl.gov/protected/spectra/aneta/SpectraMeetings/20070502/KaonGlobalTracks_20070502.html

Quick status reprots from all those with SQM abstracts submitted.

Time	Talk	Presenter
12:00	SQM Analyses Reports ( 00:25 ) 0 files	Betty, Marek, Christine, Jiaxu, Ant, Jun
12:25	Kaon discrepancy status ( 00:15 ) 2 files	Lee, Jun
12:40	EPOS and STAR d+Au data ( 00:15 ) 0 files	Sevil
12:55	AOB ( 00:05 ) 0 files