STAR HardProbes PWG

[Nihar Sahoo <nihar AT rcf.rhic.bnl.gov>]

Hello Youqi,

Thank you for your update and this information.

I have the following comment and questions on your new updated results 
(plots) and also your notes. 

> Regarding systematics,
> - You might have noticed that the systematic errors for multifold have 
> gone up by a bit. This is because I realized that before, when doing
> herwig and pythia8 shape variations, I was using pythia6 mass 
> distribution for the misses. Now I changed it so that the misses 
> contribution
> for prior shape variation is also weighted by the mass ratio of herwig 
> (pythia8) over pythia6.

Good that you found out this.
If I understand correctly, you have three MCs: Herwig, Pythia8, and 
Pythia6. You used each of these MC mass distributions for the mass shape 
variation for sys uncertainties. Earlier, you used Pythia6 for all these 
cases, but now you corrected it with their respective mass shapes. Is 
that correct? 
Could you show (include in your backup) us those mass distribution 
variations using these three different MC priors? Curious to see the 
difference due to different fragmentations in the mass distribution. 

> - After talking with Isaac, I learned that unfolding systematics due to 
> variation of iteration number and variation of prior shape were treated
> as correlated in previous analyses, while I originally had these added 
> in quadrature. Now I also treat them as correlated by just taking the
> largest contribution to the unfolding systematic as the overall 
> unfolding systematic, and add it in quadrature with detector 
> systematics.

Could you please separate out I) statistical uncertainty, II) Correlated 
Sys, and III) Uncorrelated Sys in your plot ( using Style2 in slide#16) 
without adding in quadrature? Please use a smaller marker size to see 
the stat. Error bar (even if it is small).  


> - Regarding the question whether there's anything still missing that's 
> raised during the meeting yesterday, I forgot to mention that we 
> haven't included detector and generator level pT shape smearing. This 
> is included in Raghav's and Isaac's analyses because they did 1D 
> reweighting, but we are not sure if it should be included for 
> multidimensional unfolding.

 Hmm, Is not it that the total detector effects (tracking efficiency and 
pT smearing) are considered using this multifold while you create 
something like the response matrix? What am I missing here? 


Comments on your slide#12 (from this email preliminary templet slides)

1. Slide#12: As you have mentioned, you have varied only in the 
embedding, not in the data. General practice is to vary in the data. But 
not sure if that will be accurately translated to the variation in the 
data. It is interesting. i) Then how do you use tracking efficiency 
(+-4%) variation in embedding to get systematic uncertainties? ii) Can 
you please do a test where you apply the same variation in the data and 
use the respective variation in the embedding and then check if you get 
approximately the same sys. variation between the two cases ?(just for 
one case which one has a bigger effect). 

2. I like Style-4 (slide18) of figure-1 if you don't want to shift the 
published results. In this case, I would suggest using an open black 
star for published results and a filled red marker for your new 
Multifold results. Then you plot your red filled star top on the 
published results (open back mark). In this case, you don't need to 
shift the published results, and no confusion, and will look good. 

3. SLide19, Fig-1 ratio plot: In this plot, assuming statistical 
uncertainties cancel out. Are these bands only the ratio of systematic 
uncertainties? Can you use a separate marker style here in order to 
avoid your mass distribution red star style? 

4. SLide#21: Thank you for including raw distribution here. It looks 
like there is a noticeable difference between raw and Multifold levels. 

5. Slide#23: Thank you for including PYTHIA8 curves. I like this plot 
and the comparison. Pythia8 and Data are consistent. You could point out 
that further study is ongoing to explore mass distribution between q vs. 
g using this |Q| cut. This is the main physics of this |Q| cut here. 
Right? (Can you label "PYTHiA8" as "PYTHIA8 Detroit tune" or …STAR 
tune?)

Cheers
Nihar




On 2022-09-23 20:29, Youqi Song via Star-hp-l wrote:
> Hi all,
>
> I have updated my slides for the preliminary request at:
> https://drupal.star.bnl.gov/STAR/system/files/prelim_request_092222_0.pdf.
>
> A few things that I would like to point out:
>
> Regarding systematics,
> - You might have noticed that the systematic errors for multifold have
> gone up by a bit. This is because I realized that before, when doing
> herwig and pythia8 shape variations, I was using pythia6 mass
> distribution for the misses. Now I changed it so that the misses
> contribution for prior shape variation is also weighted by the mass
> ratio of herwig (pythia8) over pythia6.
> - After talking with Isaac, I learned that unfolding systematics due
> to variation of iteration number and variation of prior shape were
> treated as correlated in previous analyses, while I originally had
> these added in quadrature. Now I also treat them as correlated by just
> taking the largest contribution to the unfolding systematic as the
> overall unfolding systematic, and add it in quadrature with detector
> systematics.
> - Regarding the question whether there's anything still missing that's
> raised during the meeting yesterday, I forgot to mention that we
> haven't included detector and generator level pT shape smearing. This
> is included in Raghav's and Isaac's analyses because they did 1D
> reweighting, but we are not sure if it should be included for
> multidimensional unfolding.
>
> Regarding plotting,
> - For fig. 1, I made the mass distribution plot with the same data
> points in 4 different styles.- For fig. 1 ratio plot, the error band
> is now centered at 1 and is the quadrature of RooUnfold's and
> MultiFold's unfolding systematics, divided by the mean values from
> RooUnfold.
> - For fig. 2, I also included a plot of the M vs Q correlation with
> raw data before unfolding.
> - For fig. 3, I have pythia8 curves plotted together with my unfolded
> mass distributions.
>
> Please let me know if you have any comments/suggestions.
>
> Best,
> Youqi
>
> On Wed, Sep 21, 2022 at 5:47 PM Youqi Song <youqi.song AT yale.edu>
> wrote:
>
> > Hi all,
> >
> > I have uploaded my slides here:
> > https://drupal.star.bnl.gov/STAR/blog/youqi/multifold092222
> >
> > Best,
> > Youqi
> >
> > On Wed, Sep 21, 2022 at 5:04 PM Tong Liu via Star-hp-l
> > <star-hp-l AT lists.bnl.gov> wrote:
> >
> > Hi all,
> >
> > Please find my pdf in this post:
> https://drupal.star.bnl.gov/STAR/blog/tongliu/Tong-Lius-HP-PWG-updates
> > Tong Liu
> > Ph.D. Student '2023
> > Physics Dept., Yale University
> >
> > Tel: 203-435-2130
> >
> > On Wed, Sep 21, 2022 at 3:29 AM Nihar Sahoo via Star-hp-l
> > <star-hp-l AT lists.bnl.gov> wrote:
> > Hello All,
> >
> > We got requests from Youqi and Tong to present their results for the
> > Hot
> > Quark conference.
> > And during Youqi's talk at the collaboration meeting, we did not get
> >
> > time to have Q&A.
> > So let's meet this week to discuss their updates.
> >
> > Youqi and Tong, can you please send link of your slides in this
> > thread
> > again?
> > (I didn't get your previous emails, the reason I do not know)
> >
> > If anybody wants to discuss their results, please let us know.
> >
> > HP-pwg weekly meeting Drupal page:
> https://drupal.star.bnl.gov/STAR/pwg/Hard-Probes/Weekly-HP-PWG-meeting
> > Zoom Meeting link:
> https://bnl.zoomgov.com/j/1611419615?pwd=VW1hNm43ZDd5d2EvK2R4aEJsQ2ZNZz09
> > [1]
> >
> > Meeting ID: 161 141 9615
> > Passcode: 744968
> >
> > Thank you
> > Barbara, Yi, Sooraj, Nihar
> >
> > On 2022-09-19 22:13, Nihar Sahoo via Star-hp-l wrote:
> > > Hello All,
> > >
> > > Last week we discussed a lot at the collaboration meeting, If
> > there is
> > > no urgent matter to discuss,  let's cancel this week's HP pwg
> > meeting.
> > > Have a great week.
> > >
> > > Thank you
> > > Barbara, Yi, Sooraj, and Nihar
> > > _______________________________________________
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