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Thanks, John!</div>
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I've generated all the H singles files to look at, but I still need the currents filled out in the spreadsheet, and I need to grab the "good events". </div>
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The H data/SIMC ratios look pretty good with the target boiling corrections (see spreadsheet "Summary" tab). I used a weighted average: Sum_i(n_i*f_i)/Sum_i(n_i) where f_i came from the Carlos's boiling factor: -0.0006*I+1 for the relevant current of the run
(as Deepak updated in the spreadsheet). n_i is the number of good events in that run. All H runs are 1 within statistical uncertainty except for the single Q2=9.5 large collimator run 3188. </div>
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-Holly</div>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Color_transp <color_transp-bounces@jlab.org> on behalf of John Matter <jcm6fv@virginia.edu><br>
<b>Sent:</b> Wednesday, June 5, 2019 12:12 AM<br>
<b>To:</b> color transp<br>
<b>Subject:</b> [Color_transp] pass2 singles efficiency</font>
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<div dir="ltr">Hello,
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<div>My most recent efficiency estimates for pass2 singles are now in the "Singles Run" tab of the pass spreadsheet.</div>
<div><a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__docs.google.com_spreadsheets_d_17bz05O-5FPwtIYuMA3KCc2lL6IX-5FhQlpqTzUO3XwVqR2o_&d=DwMFaQ&c=CJqEzB1piLOyyvZjb8YUQw&r=XtVl8BY42jbbWh0Vu1ygqgFBYEJMENirtKAh3P_9ayw&m=z6t8nfx08rEm2rvjrv-JQCsBKwupWVD_V13pQFvPM1k&s=7aN74UsNit0WamefIxurJn70QvsNXGCZ8LOmgMuk1Z8&e=">https://docs.google.com/spreadsheets/d/17bz05O_PwtIYuMA3KCc2lL6IX_hQlpqTzUO3XwVqR2o/</a><br>
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<div>The current code I have made it easiest to calculate over all runs for a (target,Q^2) pair, but I can calculate by run instead tomorrow.</div>
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<div>These are the cuts I used:</div>
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<div><b>HMS Cherenkov (calculated per delta bin, then weighted)</b></div>
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<div>should = (H.gtr.beta > 0.8 && H.gtr.beta < 1.2) && (H.cal.etottracknorm > 0.8 && H.cal.etottracknorm < 1.15) && (H.kin.primary.W > 0.85 && H.kin.primary.W < 1.03) && (H.cal.eprtrack>0.1)</div>
<div>did = should && (H.cer.npeSum>0)</div>
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<div><b>HMS Calorimeter (</b><b>calculated per delta bin, then weighted)</b></div>
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<div>should = (H.gtr.beta > 0.8 && H.gtr.beta < 1.2) && (H.cer.npeSum>0) && (H.kin.primary.W > 0.85 && H.kin.primary.W < 1.03) && (H.cal.eprtrack>0.1)</div>
<div>did = should && (H.cal.etottracknorm > 0.8 && H.cal.etottracknorm < 1.15)</div>
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<div><b>SHMS NGC (</b><b>calculated per delta bin, then weighted)</b></div>
<div>should = <b>(</b>P.gtr.beta > 0.6 && P.gtr.beta < 1.4) && (P.hgcer.npeSum<0.1) && (P.cal.eprtrack<0.1)</div>
<div>did = should && (P.ngcer.npeSum<0.1)</div>
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<div><b>SHMS Tracking</b></div>
<div>should = (P.hod.goodscinhit==1) && (P.hod.betanotrack > 0.5 && P.hod.betanotrack < 1.4) && ((P.dc.1x1.nhit + P.dc.1u2.nhit + P.dc.1u1.nhit + P.dc.1v1.nhit + P.dc.1x2.nhit + P.dc.1v2.nhit) < 21) && ((P.dc.2x1.nhit + P.dc.2u2.nhit + P.dc.2u1.nhit + P.dc.2v1.nhit
+ P.dc.2x2.nhit + P.dc.2v2.nhit) < 21) && (P.ngcer.npeSum<0.1) && (P.cal.eprtrack<0.1)</div>
<div>did = should && (P.dc.ntrack>0)</div>
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<div><b>HMS Tracking</b></div>
<div>should = (H.hod.goodscinhit==1) && (H.hod.betanotrack > 0.5 && H.hod.betanotrack < 1.4) && ((H.dc.1x1.nhit + H.dc.1u2.nhit + H.dc.1u1.nhit + H.dc.1v1.nhit + H.dc.1x2.nhit + H.dc.1v2.nhit) < 21) && ((H.dc.2x1.nhit + H.dc.2u2.nhit + H.dc.2u1.nhit + H.dc.2v1.nhit
+ H.dc.2x2.nhit + H.dc.2v2.nhit) < 21) && (H.cer.npeSum>0) && (H.cal.etottracknorm > 0.8 && H.cal.etottracknorm < 1.15)</div>
<div>did = should && (H.dc.ntrack>0)</div>
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<div><b>Hodoscope</b></div>
<div>I copied these from the report output. These are calculated by the THcHodoEff class which (briefly stated) calculates 3/4 efficiency only using events with tracks that pass through the center of the paddles.</div>
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<div dir="ltr">- John</div>
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