[Clas12_rgb] [EXTERNAL] Re: Sample of RG-B Spring19 runs processed with AI-assisted tracking
Raffaella De Vita
Raffaella.Devita at ge.infn.it
Wed Jan 26 08:31:27 EST 2022
Dear Timothy,
Thanks for sharing these results. If I’m not mistaken, they are quiet consistent with what Harut got on a fraction of the statistics. Have you looked also at the simulations with background?
We plan to spend part of tomorrow software meeting to go through all these results and, if you are available, it would be great if you could present your work as well.
Thanks again,
Raffaella
> On 26 Jan 2022, at 00:43, Hayward, Timothy <timothy.hayward at uconn.edu> wrote:
>
> Dear Raffaella,
>
> I checked the pi+ pi- channel on the data and MC samples you produced:
>
> <PastedGraphic-62.png>
>
> <PastedGraphic-63.png>
>
> Regards,
> Timothy
>
>
>
>> On Jan 25, 2022, at 7:36 AM, Raffaella De Vita <Raffaella.Devita at ge.infn.it <mailto:Raffaella.Devita at ge.infn.it>> wrote:
>>
>> *Message sent from a system outside of UConn.*
>>
>>
>> Dear All,
>> 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.
>>
>> 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.
>>
>> The reconstructed DSTs are for the A/B samples are in /volatile/clas12/users/devita/mlt17. Specifically:
>> - Sample A with and Without background:
>> /volatile/clas12/users/devita/mlt17/reconA/nobg
>> /volatile/clas12/users/devita/mlt17/reconA/bg
>> - SAmple V with and without background:
>> /volatile/clas12/users/devita/mlt17/reconB/nobg
>> /volatile/clas12/users/devita/mlt17/reconB/bg
>>
>> Let me know if you have any question.
>> Best regards,
>> Raffaella
>>
>>
>>> On 14 Jan 2022, at 21:14, Raffaella De Vita <devita at ge.infn.it <mailto:devita at ge.infn.it>> wrote:
>>>
>>> Dear All,
>>> 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.
>>>
>>> DSTs and skims for these runs are available in:
>>> Sample A:
>>> DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/reconA
>>> Skims: DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/trainA
>>> Sample B:
>>> DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/reconB
>>> Skims: DSTs: /volatile/clas12/users/clas12/mlt17/rgb_spring2019/torus-1/dst/trainB
>>> 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.
>>>
>>> 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
>>>
>>> It would be great if you could run your analysis on this sample and report the results you get at the next software meeting.
>>> Best regards,
>>> Raffaella
>>
>>
>>
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