Log entry time 11:47:25 on March 12,1999

Entry number 282

The plots below are for the hydrogen data at Q^2=0.6 (GeV/c)^2.  The

discriptions are as follows:

Note: Multiple plots: Each plot on a page is a different t bin (8 for now). The 

	sequence is:

			1	2

			3	4

			5	6

			7	8



	for a t range of .02:.1 in .01 steps.



	The cuts used were the same as those in the latest cuts file Jochen provided with the following exceptions:



	missmass: .93:.95

	hsdelta: abs(hsdelta)<8.5

	Q^2 and W:  CUT 29 w*1000..ge.2358-760*q2

		    CUT 30 w*1000..le.2382-650*q2

		    CUT 31 w*1000..ge.2073-270*q2

		    CUT 32 w*1000..le.2137-240*q2





	This set of plots shows the final cross sections as a function of t and phi.  The color code is:



	color:		setting:   High epsilon



	black		high -2.77

	red		high 0.0

	green		high 2.0

	blue		high 4.0



				   Low epsilon



	black		low 0.522

	red		low 2.0

	green		low 4.0



The SIMC ntuple variable for the cross section I used was "sigmc" which is the center of mass cross section (sig in physics.f) before gamma is applied.  I scaled this variable by 2*pi*1.0e6 to put it into the proper units.  So what is plotted is:



		sigma_data = Ratio*sigcm*2*pi*1.0e6



******NOTE:   *********

	The cross sections are NOT scaled in W, Q^2, or epsilon.

*********************



These plots show us at least three important features:



1)   The phi disease has been great improved, but there is still a trace of it in some settings.



2)  If you look carefully you can see a definate cos(2*phi) structure in the data.   This was difficult to see in previous iterations and has improved with the  new SIMC outputs.  As this continues to improve (though probably not by much)  we will be able to produce better seperated cross sections.



3)  We can also see that there is a slight coorelation problem between settings.  If we can correct this, the phi dependent structure will improve and the errors for fits of the weighted average cross sections should also improve.



The large error bars are due to low statistics in that region for that setting.