STAR HardProbes PWG

[David Stewart <0ds.johnny AT gmail.com>]

Yes -- thanks, for reference see prior email on Friday, and perhaps also the paper webpage here. I'd repeat the Friday email, but I think that the information that I gave regarding which tracking uncertainties to use is redundant to the discussion in this current email thread.

Best,

Dave

On Mon, Oct 2, 2023 at 1:22 PM Ma, Rongrong via Star-hp-l <star-hp-l AT lists.bnl.gov> wrote:

Hello Sooraj

Thanks for the responses. It will be useful to publish some guidances on this matter for analyzers. For example, some official numbers or procedures will be beneficial for the ongoing discussion within GPC #359. I believe Dave sent a note to the PWG about this already.

Best

Rongrong

On Oct 2, 2023, at 12:54 PM, Sooraj Radhakrishnan <skradhakrishnan AT lbl.gov> wrote:

There is an additional issue here. The 1% uncertainty is for very loose cuts. There could be analyses that cannot use such loose cuts for baseline. In that case, would need to use the 5% as baseline tracking uncertainty and quote the impact of any cut variations on top of that. 

Sooraj

On Mon, Oct 2, 2023 at 9:41 AM Sooraj Radhakrishnan <skradhakrishnan AT lbl.gov> wrote:

Hi Rongrong,

   That is a good point. There have been some discussions on this

From Petr's study what we see is that the overall efficiency in finding tracks (with very loose cuts on track quality) between data and embedding is quite close, and the uncertainty is less than 1%. The nHitts and DCA distributions differ though between data and embedding. This introduces mismatch between data and embedding when using typical analysis cuts and thus the uncertainty. This uncertainty for typical cuts we use (nHits >15, DCA< 2cm) is pT independent, 5%, as you can see on his slide 11 here https://drupal.star.bnl.gov/STAR/system/files/TrkEff.pdf. Since we cant define tracks without quality cuts, this is a reasonable value to use as tracking efficiency uncertainty

However, there are a few things to consider here. The uncertainties extracted also have some dependence on the method. For example, these are for Kaons and for tracks that end in the TPC. So may not be appropriate for typical tracks, particularly when we are looking at say nHits dependence. So an alternate approach could be that, we can use the 1% as baseline uncertainty and then do comparisons of the final corrected results for different cut variations. This would be an indirect way of accounting for tracking efficiency uncertainty, but is also reasonable

Hope this helps

Best,

Sooraj

On Mon, Oct 2, 2023 at 7:31 AM Ma, Rongrong <marr AT bnl.gov> wrote:

Hello Sooraj

From your last sentence, are you suggesting analyzers to use a pt-independent over 5% uncertainty OR a possibly pt-dependent uncertainty from varying quality cuts? If the embedding matches with data well or the track quality cuts are very loose, the latter could yield very small uncertainty. Are we ready to claim that? Maybe I misunderstood your suggestion. Could you clarify since this discussion has wide-spread impacts?

Thanks. 

Best

Rongrong

On Sep 29, 2023, at 9:52 PM, Sooraj Radhakrishnan <skradhakrishnan AT lbl.gov> wrote:

Hi Helen,

   Thanks for the email. I was looking at Dmitry's thesis and the note with detailed study he had on the TPC tracking efficiency https://drupal.star.bnl.gov/STAR/files/tracking_efficiency_uncertainty_2_0.pdf. Dmitry, as he explains in the note (L.226), is looking at only some particular aspects of tracking inefficiency. The analysis is done by comparing the efficiency of tracks embedded into real data and of tracks embedded into PYTHIA + zero bias. From a tracking efficiency perspective, both these use the same detector description, geometry and material and the difference is mainly from effects of pileup and other noise in the data. This certainly is giving insight into a particular feature of our track reconstruction, however, its not all of the uncertainties associated with tracking. In fact, this is more a feature than an uncertainty. We do have impact from occupancy and we see multiplicity dependence of tracking, but that is not taken as an uncertainty. 

For now, I am not aware of other studies looking into tracking uncertainty than from the TPC tracking uncertainty task force. The value they have, for before the iTPC, is 5%. But as you said, this is possibly an overestimate for p+p and would be good to do an evaluation in a p+p dataset. The other estimate is the 5% that has been for long as an estimate of the tracking uncertainty. 

It would be great if the tracking uncertainty task force could look into the 2017 p+p dataset. And since the procedure is now more mature, this can hopefully be done relatively fast. I can check with Petr and the task force what the prospects are. But for now, the choices are the 5% or as some analyses have done, evaluating the impact of track quality cuts on the final corrected observables 

thanks

Sooraj

On Fri, Sep 29, 2023 at 11:35 AM Ma, Rongrong via Star-hp-l <star-hp-l AT lists.bnl.gov> wrote:

Hello All

Maybe I can also chime in here. 

I think there are two types of systematical uncertainties related to tracking efficiency:

i) uncertainty in the absolute tracking efficiency, i.e. fraction of tracks not reconstructed at all in the embedding (missing between boundaries, for example)

ii) how well the embedding can reproduce the track properties in data, such as NHitsFit, DCA distribution, etc. This relates to the track loss due to track quality cuts. 

I think these two are closely related, but not the same. Type i) is inherent to our simulation model (TPC boundary, material budget, etc) which could be common to all datasets, while type ii) is related to how well the simulation is tuned for a specific dataset. The cut variations that people usually do should probe more of the type ii) uncertainty. I think Dmitri's study falls into this category as well, which concluded the uncertainty to be about 1% (page 114 of his thesis) for the DCA cut. To assess type i) uncertainty, one needs to know the absolute efficiency from data, which I believe the tracking task force is trying to achieve using K->3pi decays.

During Petr's collaboration talk, it was suggested to use both type i) (5%) and type ii) (cut variations) uncertainties in analysis, before they come up with a new, updated number. The 5% number is old and a bit hand-waving, but I am not sure if we have evidence that it should be something else. Maybe I missed some recent updates. 

Best

Rongrong

On Sep 29, 2023, at 1:33 PM, Leszek Kosarzewski via Star-hp-l <star-hp-l AT lists.bnl.gov> wrote:

Hi Sooraj, Nihar and Helen

Thank you for your explanations. My understanding was that the 5% is independent of the dataset, but it's good to know that it should be similar for p+p. Let's see if we get additional information from Petr. If I remember correctly, the tracking efficiency group tried to follow Dimitry's studies and that was their conclusion. It would be nice to reduce the uncertainty and I can update it in the next step during GPC review. On the other hand, the tracking group did a lot of work and I don't think their conclusions are limited to the specific datasets, but useful for other studies as well.

Best regards, Leszek

pt., 29 wrz 2023 o 13:23 Helen Caines via Star-hp-l <star-hp-l AT lists.bnl.gov> napisał(a):

Hi,

 Since I brought this up at the meeting, let me chip in where my question came from. The Spin group in the past made a detailed study of the pp (its 2012 data I think) and concluded that the tracking efficiency uncertainty was smaller than we usually quote. They were exploring this, to my memory, to try to beat down the uncertainty on the jet cross-section measurements. 

I’m sure many were involved, but Dmitri Kalinkin sticks in my mind as one of the lead analyzers of this study. Indeed his thesis (

https://drupal.star.bnl.gov/STAR/files/phd-thesis.pdf ) shows  around page 112 that the data-simulation match is very good and the uncertainty therefore less. This is in-line with a previous study that showed that for pp the uncertainty on the tracking efficiency is 3.3% (that was from another Spin/Cold QCD thesis from Texas A&M. These are statements from theses so maybe further studies showed a different final conclusion, but I thought we should check.

For Leszek’s study maybe this difference doesn’t matter, but it seems a shame to artificially inflate the uncertainties on our pp results by assuming uncertainties from Au-Au, which naively one can understand as  possibly being larger

Helen

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On Sep 29, 2023, at 1:05 PM, Sooraj Radhakrishnan via Star-hp-l <star-hp-l AT lists.bnl.gov> wrote:

Hi Leszek, Nihar,

   The tracking efficiency task force has studied the efficiencies for 2018 and 2019 Au+Au datasets. Petr can comment more details and if other datasets were looked at. Also, as you can see from the links Nihar shared, for the 2018 case, the evaluations are limited by the smaller r range without the iTPC. For typical cuts used in analyses, the uncertainty is around 5% for the 2018 dataset. So for your case 5% uncertainty on tracking, that we typically use, is still a good choice 

Best,

Sooraj

On Thu, Sep 28, 2023 at 9:47 PM Nihar Sahoo via Star-hp-l <star-hp-l AT lists.bnl.gov> wrote:

Hello Leszek,

After going through Petr's presentation slides, the uncertainty on
efficiency was calculated based on AuAu data and that has both DCA and
nhits dependence.
For DCA < 2 cm and nhits >15, that is 5%.
But we need to make sure if this number is true for pp data too.

Some of his presentation are here:
https://drupal.star.bnl.gov/STAR/system/files/TrkEff.pdf
https://drupal.star.bnl.gov/STAR/system/files/2023_PWG.pdf

Let's see if Petr can chime in, otherwise we can contact him offline to
know the details.

I believe this would be a minor correction to your data and that can be
fixed at the GPC level.
If you have paper and AN ready, then we can start looking at these.

I hope this helps you.

Thank you
Nihar



On 2023-09-29 00:39, Leszek Kosarzewski wrote:
> Hello Nihar
>
> Thanks for the feedback, I will update the paper page and finish the
> responses and I hope we can move on quickly with a GPC formation.
> Could you sent a link to that new estimate of the tracking efficiency
> systematic uncertainty in p+p?
>
> Best regards, Leszek
>
> czw., 28 wrz 2023 o 11:05 Nihar Sahoo via Star-hp-l
> <star-hp-l AT lists.bnl.gov> napisał(a):
>
>> Hello HP-pwg,
>>
>> Here is the link to the slides that I discussed.
>> Please note that we have included analyses those are STAR
>> preliminary
>> now.
>> If we have missed any, please inform us.
>>
>> https://drupal.star.bnl.gov/STAR/blog/nihar/HPpwg-analyses-status
>>
>> Thank you
>> Nihar for hp-pwg conveners
>>
>> On 2023-09-25 17:42, Nihar Sahoo via Star-hp-l wrote:
>>> Hello All,
>>>
>>> We will have our HP-pwg meeting this Thursday (28th Sep) at 10 AM
>> EDT.
>>> Let us know please if you want to present and discuss your
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>>> Send your presentation slides a few hrs before the meeting,
>> please.
>>>
>>> NOTICE: PAs are requested to update us their paper proposal plan
>> and
>>> timeline of their STAR preliminary results/current analyses.
>>>
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>>
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>>>
>>> Join ZoomGov Meeting
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>>
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>>> Isaac, Yi and Nihar
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Sooraj Radhakrishnan

Research Scientist,

Department of Physics

Kent State University

Kent, OH 44243

Physicist Postdoctoral Affiliate

Nuclear Science Division
Lawrence Berkeley National Lab
MS70R0319, One Cyclotron Road

Berkeley, CA 94720

Ph: 510-495-2473

Email: skradhakrishnan AT lbl.gov

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Sooraj Radhakrishnan

Research Scientist,

Department of Physics

Kent State University

Kent, OH 44243

Physicist Postdoctoral Affiliate

Nuclear Science Division
Lawrence Berkeley National Lab
MS70R0319, One Cyclotron Road

Berkeley, CA 94720

Ph: 510-495-2473

Email: skradhakrishnan AT lbl.gov

--

Sooraj Radhakrishnan

Research Scientist,

Department of Physics

Kent State University

Kent, OH 44243

Physicist Postdoctoral Affiliate

Nuclear Science Division
Lawrence Berkeley National Lab
MS70R0319, One Cyclotron Road

Berkeley, CA 94720

Ph: 510-495-2473

Email: skradhakrishnan AT lbl.gov

--

Sooraj Radhakrishnan

Research Scientist,

Department of Physics

Kent State University

Kent, OH 44243

Physicist Postdoctoral Affiliate

Nuclear Science Division
Lawrence Berkeley National Lab
MS70R0319, One Cyclotron Road

Berkeley, CA 94720

Ph: 510-495-2473

Email: skradhakrishnan AT lbl.gov

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David Stewart

Postdoctoral Fellow | Department of Physics, Wayne State University