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<p style="margin-top:0;margin-bottom:0">If we can use random trigger data for the beam background, the MC CPU time can be cut by 90% and the disk space can be reduced by 90% as well.</p>
<p style="margin-top:0;margin-bottom:0"><br>
</p>
<p style="margin-top:0;margin-bottom:0">Have we done any comparison between MC beam background and random trigger data? Take wab-beam MC, perform signal evolution and take one trigger window randomly. This should be random trigger MC equivalent to random trigger
data. I would like to see this comparison.</p>
<p style="margin-top:0;margin-bottom:0"><br>
</p>
<p style="margin-top:0;margin-bottom:0">Takashi </p>
</div>
<hr style="display:inline-block;width:98%" tabindex="-1">
<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Hps-analysis <hps-analysis-bounces@jlab.org> on behalf of Maurik Holtrop <maurik@physics.unh.edu><br>
<b>Sent:</b> Thursday, March 7, 2019 5:51:44 AM<br>
<b>To:</b> Nelson, Timothy Knight<br>
<b>Cc:</b> hps-analysis@jlab.org<br>
<b>Subject:</b> Re: [Hps-analysis] HPS Analysis meeting March 5 @ 9am/noon PST/EST</font>
<div> </div>
</div>
<div class="" style="word-wrap:break-word; line-break:after-white-space">Good Morning,
<div class=""><br class="">
</div>
<div class="">I think the implementation details that we have in general for doing the readout after getting the energy deposits from SLIC is where merging the MC and data becomes difficult. </div>
<div class=""><br class="">
</div>
<div class="">Perhaps a different perspective would make this task a whole lot easier. We should think about it in terms of MC being merged with Data, rather than looking at it as trying to merge Data with MC. Instead of merging at some in-between state of
the data inside the readout chain, I think we should merge data at the EVIO level. At that level the data structure is well defined and it is clear what to do with the merging. There should already be a path to go from SLIC through readout to EVIO. Though
I am afraid that hasn’t been exercised much (if at all), at least it is a clear step. The advantage of merging at the EVIO level in the data chain is that it will be much easier to verify that this is done properly. You can take low luminosity events and
merge in pulser data to simulate high luminosity runs. We can take the MC -> EVIO and then analyze this (recon) as if it is data (without merging anything) and it should give the same results as we would get in our current MC chain. </div>
<div class=""><br class="">
</div>
<div class="">We should discuss this more next Tuesday in our software meeting.</div>
<div class=""><br class="">
</div>
<div class="">Best,</div>
<div class=""><span class="x_Apple-tab-span" style="white-space:pre"></span>Maurik</div>
<div class=""><br class="">
</div>
<div class=""><br class="">
<div>
<blockquote type="cite" class="">
<div class="">On Mar 6, 2019, at 10:31 PM, Nelson, Timothy Knight <<a href="mailto:tknelson@slac.stanford.edu" class="">tknelson@slac.stanford.edu</a>> wrote:</div>
<br class="x_Apple-interchange-newline">
<div class=""><span class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none; float:none; display:inline!important">Hi
Bradley,</span><br class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none">
<br class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none">
<span class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none; float:none; display:inline!important">I
think this is even easier in the SVT where the chain in MC and data already work the same way. This is basically because a lot of work went into a very high-fidelity digitization chain for silicon before HPS even came along. I remember from work that Kyle
did that there were some difficult things to think through for the ECal in terms of how ECal samples and pulses are smeared in MC, which is not quite like what the effects are like in data.</span><br class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none">
<br class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none">
<span class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none; float:none; display:inline!important">Tim</span><br class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none">
<br class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; text-align:start; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px; text-decoration:none">
<blockquote type="cite" class="" style="font-family:Helvetica; font-size:14px; font-style:normal; font-variant-caps:normal; font-weight:normal; letter-spacing:normal; orphans:auto; text-align:start; text-indent:0px; text-transform:none; white-space:normal; widows:auto; word-spacing:0px; text-decoration:none">
On Mar 6, 2019, at 5:40 PM, Yale, Bradley T <<a href="mailto:btu29@wildcats.unh.edu" class="">btu29@wildcats.unh.edu</a>> wrote:<br class="">
<br class="">
To do MC+pulser correctly, the FADC samples need to be combined pre-readout, and then readout those combined samples. The machinery already exists to combine the hits and other collections post-readout and then reconstruct them, but this isn't quite correct.<br class="">
<br class="">
I think the question is whether the information still exists in an already-readout data event to combine the samples with MC. Then a driver can be made to do this, or the existing readout modified.<br class="">
<br class="">
Alternatively (and more simply), the MC readout step could be broken up to convert SimHits->RawHits, combine the MC raw hits with those from data, cluster the result, and then continue the chain. The energy deposition would still not be quite correct though,
and I'm not sure how the SVT hits should be handled.<br class="">
From: Hps-analysis <<a href="mailto:hps-analysis-bounces@jlab.org" class="">hps-analysis-bounces@jlab.org</a>> on behalf of Stepan Stepanyan <<a href="mailto:stepanya@jlab.org" class="">stepanya@jlab.org</a>><br class="">
Sent: Wednesday, March 6, 2019 6:37 PM<br class="">
To: John A. Jaros<br class="">
Cc: <a href="mailto:hps-analysis@jlab.org" class="">hps-analysis@jlab.org</a><br class="">
Subject: Re: [Hps-analysis] HPS Analysis meeting March 5 @ 9am/noon PST/EST<br class="">
<br class="">
Dear John,<br class="">
<br class="">
Yes, it is not simple but doable. Needless to say, CLAS, only year since running, already has beam background merging from data. In fact it works for both cases BG-on-MC and BG-on-data, where the later one is used to validate the method using the low luminosity
runs with high luminosity background overplayed. In fact I think we should do this for upcoming HPS run, take low luminosity runs regularly for validation of the reconstruction at high luminosity.<br class="">
<br class="">
Another method I proposed couple of months ago to use to avoid a large (x10 of data) amount of MC is the event mixing. Using an electron and a positron from different events, with some kinematic constraints (e.g. invariant mass), we can generate “infinite”
number of fake v0’s. These v0's will have correct beam background, correct/real resacattering effects of individual tracks, and no physics. So everything related to the background and rescattering (e.g. vertex tails) can be studies with large statistics using
these fake v0’s, no need for huge amount of MC.<br class="">
<br class="">
Regards, Stepan <br class="">
<br class="">
<blockquote type="cite" class="">On Mar 6, 2019, at 5:32 PM, Jaros, John A. <<a href="mailto:john@slac.stanford.edu" class="">john@slac.stanford.edu</a>> wrote:<br class="">
<br class="">
We should. It isn't completely straightforward, but we should.<br class="">
<br class="">
<br class="">
-----Original Message-----<br class="">
From: Hps-analysis [<a href="mailto:hps-analysis-bounces@jlab.org" class="">mailto:hps-analysis-bounces@jlab.org</a>] On Behalf Of Stepan Stepanyan<br class="">
Sent: Wednesday, March 06, 2019 1:25 PM<br class="">
To: <a href="mailto:hps-analysis@jlab.org" class="">hps-analysis@jlab.org</a><br class="">
Subject: Re: [Hps-analysis] HPS Analysis meeting March 5 @ 9am/noon PST/EST<br class="">
<br class="">
Hi all,<br class="">
<br class="">
An old idea - why we cannot use beam background from the data, using the random trigger events?<br class="">
<br class="">
Stepan<br class="">
<br class="">
<br class="">
On 3/6/19 3:27 PM, Solt, Matthew Reagan wrote:<br class="">
<br class="">
<br class="">
Hi Takashi,<br class="">
<br class="">
<br class="">
<br class="">
<br class="">
Thanks for thinking about this. You are correct in saying that a x10 sample of tritrig-wab-beam is computationally difficult (if not impossible using our resources). However, I think training on a x10 sample of tritrig is sufficient. The goal of these ML studies
is to distinguish between multiple scattered tracks that produce a downstream vertex (from a prompt trident) and a true displaced vertex. So on that principle alone, I think a x10 sample of tritrig should be enough for training.<br class="">
<br class="">
<br class="">
<br class="">
<br class="">
But of course we have to take wabs and beam backgrounds into account somehow. In principle, I will find a way to get rid of the tracks that pick up the wrong hit due to a beam background (a more sophisticated isolation cut), and make it such that wabs are not
such a big deal for the vertexing. I will of course need to justify that these will not be backgrounds in the vertexing analysis (with the ML method). One way to do this is to test on the full 100% tritrig-wab-beam sample. I think this should be enough to
justify just training on a very large sample of pure tridents, but someone may come with a counter argument.<span class="x_Apple-converted-space"> </span><br class="">
<br class="">
<br class="">
<br class="">
<br class="">
More ideas are welcome. Thanks.<br class="">
<br class="">
<br class="">
<br class="">
<br class="">
Matt Solt<br class="">
<br class="">
<br class="">
________________________________<br class="">
<br class="">
From: Hps-analysis <<a href="mailto:hps-analysis-bounces@jlab.org" class="">hps-analysis-bounces@jlab.org</a>> <<a href="mailto:hps-analysis-bounces@jlab.org" class="">mailto:hps-analysis-bounces@jlab.org</a>> on behalf of Maruyama, Takashi <<a href="mailto:tvm@slac.stanford.edu" class="">tvm@slac.stanford.edu</a>>
<<a href="mailto:tvm@slac.stanford.edu" class="">mailto:tvm@slac.stanford.edu</a>><span class="x_Apple-converted-space"> </span><br class="">
Sent: Wednesday, March 6, 2019 11:54:47 AM<br class="">
To: <a href="mailto:hps-analysis@jlab.org" class="">hps-analysis@jlab.org</a><br class="">
Subject: Re: [Hps-analysis] HPS Analysis meeting March 5 @ 9am/noon PST/EST<span class="x_Apple-converted-space"> </span><br class="">
<br class="">
<br class="">
After hearing Matt S. talk on Machine Learning, I realized there is a big problem in MC production. To train Machine Learning, you need a huge statistics of MC sample, especially if you want to train in each mass bin. Furthermore, the MC sample should have
beam-background overlaid; it should be tritrig-wab-beam not tritrig-without-wab-beam. A high statistics 1.05 GeV tritrig-wab-beam sample with roughly equivalent to 2015 data statistics was generated last year. It took about 3 weeks to just generate wab-beam
background and another week to generate tritrig-wab-beam recon files. It required 50 TB to store wab-beam.SLIC files. Since there were no 50 TB space, earlier wab-beam files were deleted as the tritrig-wab-beam recon files were completed. Since 2016 run
is higher energy and 4 times higher current, it will take more CPU time and need more disk space. If we clean-up disk space, MC production with data equivalent statistics could be doable, but significantly higher statistics (10x data) is difficult.<br class="">
<br class="">
Takashi <br class="">
<br class="">
-----Original Message-----<br class="">
From: Hps-analysis [<a href="mailto:hps-analysis-bounces@jlab.org" class="">mailto:hps-analysis-bounces@jlab.org</a>] On Behalf Of Graham, Mathew Thomas<br class="">
Sent: Tuesday, March 05, 2019 5:55 AM<br class="">
To: <a href="mailto:hps-analysis@jlab.org" class="">hps-analysis@jlab.org</a><br class="">
Subject: [Hps-analysis] HPS Analysis meeting March 5 @ 9am/noon PST/EST<br class="">
<br class="">
<br class="">
Hi All, <br class="">
<br class="">
Meeting today, here're the details:<span class="x_Apple-converted-space"> </span><br class="">
<br class="">
<br class="">
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><span class="x_Apple-converted-space"> </span><br class="">
<br class="">
* Bluejeans<span class="x_Apple-converted-space"> </span><br class="">
<br class="">
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* Meeting Rooms<span class="x_Apple-converted-space"> </span><br class="">
<br class="">
* JLAB: F228<br class="">
* SLAC: Ballam<br class="">
<br class="">
<br class="">
Agenda<br class="">
<br class="">
<br class="">
* Machine Learning in Vertexing Analysis - MattS<br class="">
* Relative SVT-ECal alignment in 2016 Data - Norman<br class="">
* Bugfixes in beamspot-constrained vertexing - MattG<br class="">
<br class="">
<br class="">
<br class="">
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