Difference between revisions of "LB SageBrushWork PostDefense"

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This seems much cleaner and clearly shows the time cuts
 
This seems much cleaner and clearly shows the time cuts
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==10% Sage/Se Mixture Time Cuts==
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==0.1% Sage/Se Mixture Time Cuts==
 
==0.1% Sage/Se Mixture Time Cuts==

Revision as of 18:59, 27 August 2018

Time Cuts

The first step in the PAA process is to identify the time cuts used for the split run. This must be done for all samples (50%,10%,0.1%, and 0.04%) Let's do the 50% sample first

50% Sage/Se Mixture Time Cuts

The 50% Se/Sage mixture was measure on Detector B (unshielded, so watch the SNR) on 5/24/17 for a total of 2130.540 seconds. The outer pure witness Se was measure first, and sub-run was roughly 300 seconds for the samples of interest, and 60 seconds for the Co-60 flag. The root command used to draw the timing information was

TTree* tree = MPA;

MPA->Draw("evt.Chan:evt.Sec>>hist2","evt.ADCid == 1");

which produced the histogram below

LB 50 Percent SeSage TimeCutInfo.png

This seems a little sloppy, lets try a 1D histogram instead to see if the cuts are more clear

ROOT Command: MPA->Draw("evt.Sec>>hist","ADCid==1","");

This produced the histogram below

LB 50 Percent SeSage TimeCutInfo 1DHistogram.png

This seems much cleaner and clearly shows the time cuts

10% Sage/Se Mixture Time Cuts

0.1% Sage/Se Mixture Time Cuts

The 0.1% Se/Sage mixture was measured on Detector A (shielded) on 5/24/17 for a total of 2130.540 seconds. The mixture was measured first, and a sub-run was roughly 300 seconds for the Se samples and 60 seconds for the Co-60 flag. The root commands used were

TTree* tree = MPA;

MPA->Draw("evt.Chan:evt.Sec>>hist2","evt.ADCid == 0");

which produced the histogram below

0 1 Percent SeSage TimeCutInfo.png

This seems a little sloppy, so let's repeat the procedure for the 50% sample

ROOT Command:ROOT Command: MPA->Draw("evt.Sec>>hist","ADCid==0","");

This produced the histogram below

0 1 Percent SeSage TimeCutInfo 1DHistogram.png

This is again much better than the 2D histogram.