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Dear Raffaella,
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<div class="">I checked the pi+ pi- channel on the data and MC samples you produced:</div>
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<div class="">Regards,</div>
<div class="">Timothy</div>
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<div class="">On Jan 25, 2022, at 7:36 AM, Raffaella De Vita <<a href="mailto:Raffaella.Devita@ge.infn.it" class="">Raffaella.Devita@ge.infn.it</a>> wrote:</div>
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<div class="">*Message sent from a system outside of UConn.*<br class="">
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Dear All,<br class="">
In addition to the data sample mentioned in the previous email, MC samples from SIDIS events have been produced, using GEMC 4.4.2 and the new Coatjava release 7.1.0. The detector configuration used in the simulations is the one of RG-B Spring19 (inbending)
and background files are from RG-B 10.6 GeV, 50 nA.<br class="">
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For convenience, we used a preexisting set of Lund files for SIDIS on proton target but, if you can provide another set of Lund files for other reactions, we can produce other samples.<br class="">
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The reconstructed DSTs are for the A/B samples are in /volatile/clas12/users/devita/mlt17. Specifically:<br class="">
- Sample A with and Without background:<br class="">
/volatile/clas12/users/devita/mlt17/reconA/nobg<br class="">
/volatile/clas12/users/devita/mlt17/reconA/bg<br class="">
- SAmple V with and without background:<br class="">
/volatile/clas12/users/devita/mlt17/reconB/nobg<br class="">
/volatile/clas12/users/devita/mlt17/reconB/bg<br class="">
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Let me know if you have any question.<br class="">
Best regards,<br class="">
Raffaella<br class="">
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<blockquote type="cite" class="">On 14 Jan 2022, at 21:14, Raffaella De Vita <<a href="mailto:devita@ge.infn.it" class="">devita@ge.infn.it</a>> wrote:<br class="">
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Dear All,<br class="">
After the tagging of the last coatjava release, 7.1.0, which includes AI-assisted tracking, a sample of runs from Spring19 was processed with both conventional and AI-assisted tracking to asses the gain in statistics we have with AI on this data set.<br class="">
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DSTs and skims for these runs are available in:<br class="">
Sample A:<br class="">
DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/reconA<br class="">
Skims: DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/trainA<br class="">
Sample B:<br class="">
DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/reconB<br class="">
Skims: DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/trainB<br class="">
where the A/B samples are the results obtained with the two tracking approaches. The labels are generic to promote a sort of blind assessment.<br class="">
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Skims are the same used lately by RG-B and defined in /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/trainA/train/README.json<br class="">
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It would be great if you could run your analysis on this sample and report the results you get at the next software meeting.<br class="">
Best regards,<br class="">
Raffaella<br class="">
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