STAR HardProbes PWG

[Youqi Song <youqi.song AT yale.edu>]

Hi Barbara and Nihar,

Please find my updated slides here https://drupal.star.bnl.gov/STAR/system/files/hq_1022_v2.pdf

Response to comments (unmentioned ones are already implemented in the slides):

- Make sure you are fine in terms of time.

I'm planning to practice these two days, and if I run out of time, I will move slides 13-22 to backup. And if that's not enough, I will also move slide 31 to backup.

_"Data" -> can you please mention what data that is? Do you mean this is
pp200 Gev run12 data?
_ Please give some information about this "data"?

 (Previously on slide 9, now on slide 12). This "data" is PYTHIA6+GEANT simulation, so I put it in quotation marks. I could show these distributions for the actual data, but I assume that would require me to put in systematic and statistical uncertainties for all these observables in, which might not be necessary for the goal of this slide, which is simply to show that MultiFold is unfolding 6 observables simultaneously and is unbinned. The difference between the red and the black is to show the need for unfolding and the effect of unfolding.

Can you say something about this weights? Like where and how do you get
this?

(Previously on slide 12, now still on slide 12). These weights are exactly the output of MultiFold. (Would you like me to elaborate more on this?)

There are two small plots, not visible at all.
Can you please make it bigger and clear, and mention how it is related
to your neural network technique?

 (Previously on slides 18-19, now still on 18-19). I removed one of the plots and made the other one bigger. The choice of these neural network activation functions are default from the original OmniFold paper.

_ M>1 GeV/c^2 -> Do you use the same cut for unfolding while training
simulated from the real data? Or while making response matrix.

 (Now on slide 26). I used the same cuts for PYTHIA6+GEANT simulation.

_ I recall, we had a discussion earlier that we need systematic
uncertainty along with your statistical uncertainty for these plots in
order to validate this closure. Any progress in that direction.

_ For your jet pT case, there is a difference at some bins, I think if

you use your systematic uncertainties then it would be consistent. Any

comment?

 (Previously on slide 27, now on slide 29). I don't think this was brought up before for my analysis. Maybe it was for Monika's? The difference in pT here is mostly because the normalization is done per jet, not per event as what's usually done for pT, so a small deviation at the low pT bin will cause a large deviation in the opposite direction at high pT.

_"embedding jets into 2 statistically independent samples " -> what are
those 2 statistical ind. samples? Need some explanation.

 I added slides 27-28 to clarify this. The statistically independent samples are drawn randomly from matched jet pairs from PYTHIA and embedding.

_Be prepared for it if somebody ask any comment on systematic
uncertainty comparison between two unfolding methods. Can you please
mention here what would be your answer?

I would say that the systematic uncertainty is roughly the same between RooUnfold and MultiFold, just by eyeballing the error band sizes on slide 30.

_I think it is important to show right plot with "STAR preliminary".

(Now on slide 31). I also put the figure here: https://drupal.star.bnl.gov/STAR/system/files/20_25_all_err2_0925.pdf

 

 _"Wider jets tend to have lower |Q|" -> how do you get this conclusion?

Since I used a track-pT-weighted definition of jet charge, a high pT track will tend to make jet |Q| larger. And if a track has a high pT within a jet, it is likely to be in roughly the same direction as the jet, so the jet is more likely to be collimated, so collimated jets tend to have large |Q| and wider jets tend to have lower |Q|.

 

_ "Different fragmentation patter" -> do you mean it is because of their
different jet Mass?

(Now on slide 33). I meant that it's because of both their jet mass and charge. I think jet charge also relates to fragmentation since it contains information about the track pT's.

Best,

Youqi

On Sun, Oct 2, 2022 at 2:01 PM Youqi Song <youqi.song AT yale.edu> wrote:

Hi Barbara and Nihar,

Thanks for the suggestions! I will respond to the comments and update a new version of slides by tomorrow. Nihar, since you suggest that I show the uncertainty plot as a preliminary figure, I remade it and attached it to this email. Please let me know if you have any comments for this figure.

Best,

Youqi

On Sun, Oct 2, 2022 at 10:17 AM Nihar Sahoo via Star-hp-l <star-hp-l AT lists.bnl.gov> wrote:

Hello Youqi,

Please find my comments on your nice presentation slides!

Slide4-5:
"Jet substructure measurements tell us …" -> "Jet substructure
measurements can tell us …"
(It can tell us something related to frag. and hadronization, but not
definitely)

Slide8:
_Iterative Bayesian Unfolding (please give reference)
_"but this is this is the …" -> "but this is the …"

Slide9:
_"Data" -> can you please mention what data that is? Do you mean this is
pp200 Gev run12 data?
_ Please give some information about this "data"?
_This slide appears abruptly after slide8, can you please introduce some
information here?
Slide10-11:
All these expressions for Qj, M, zg, Rg, need to one slide discussion
before showing the results. (Expressions are in small text size, will
not be visible for audiences)
Can you please add one slide before slide9-10?

Slide12:
Can you say something about this weights? Like where and how do you get
this?

Slide18-19:
There are two small plots, not visible at all.
Can you please make it bigger and clear, and mention how it is related
to your neural network technique?

Slide24,25,26:
_mention which year pp data?
_R=0.4 -> jet resolution parameter (R)=0.4
_There are three different eta, (TPC, BEMC, and jet eta); make it clear
_ M>1 GeV/c^2 -> Do you use the same cut for unfolding while training
simulated from the real data? Or while making response matrix.

Slide27,
_ I recall, we had a discussion earlier that we need systematic
uncertainty along with your statistical uncertainty for these plots in
order to validate this closure. Any progress in that direction.
_"…centered at the value for 3 iterations " -> Not clear, can you please
rephrase this and explain a bit more? I think you have put the
statistical bar only in the case of 3rd iteration results. Is that
correct? If yes, then mention that stat. Error for other iterations are
the same.
_"embedding jets into 2 statistically independent samples " -> what are
those 2 statistical ind. samples? Need some explanation.
_ For your jet pT case, there is a difference at some bins, I think if
you use your systematic uncertainties then it would be consistent. Any
comment?

Slide28:
_This slide needs to come after Slide30-31
_"Tracking uncertainty " -> "Uncertainty in tracking efficiency" 
(people may ask you why only -4% not +4%)
_I think it is important to show right plot with "STAR preliminary".

Slide29:
_Remove "Preliminary results:" ; "Fully corrected jet M" make it bigger.
_"... but MultiFold also gives us something else!" I think you can drop
this and clearly mention what is that "something else"
_Be prepared for it if somebody ask any comment on systematic
uncertainty comparison between two unfolding methods. Can you please
mention here what would be your answer?
_ Jet M _expression_ make it bigger; Or just remove it if you add one
slide as I commented before.
_ I like this plot now.

Slide30-31:
_Remove "Preliminary results:" ;
_You could move these slides before slide29 where you can discuss one
projection results of jet M.
_"Wider jets tend to have lower |Q|" -> how do you get this conclusion?
_ "Different fragmentation patter" -> do you mean it is because of their
different jet Mass?

Slide33:
_"apply boosted decision trees on fully corrected data... " -> what is
"boosted decision tree"?
_ remover "…" at the end. Or say something what is your plan?

Cheers
Nihar

On 2022-09-30 01:11, webmaster--- via Star-hp-l wrote:
> Dear Star-hp-l AT lists.bnl.gov members,
>
> Youqi Song (youqi.song AT yale.edu) has submitted a material for a review,
> please have a look:
> https://drupal.star.bnl.gov/STAR/node/61209
>
> Deadline: 2022-10-11
> ---
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