STAR HardProbes PWG

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

Hello Youqi,

Please find my additional comments below.


Line#10: "non-perturbative processes like fragmentation and 
hadronization." -> "non-perturbative processes, like fragmentation and 
hadronization."
Line#18-19: "…and neutral energy towers from the Barrel Electromagnetic 
Calorimeter." -> "…and neutral particles from the Barrel Electromagnetic 
Calorimeter."
Line20-21: "We will present preliminary studies of jet substructure 
observables from this dataset, unfolded with MultiFold1, a machine 
learning method that simultaneously considers…" -> "We will present 
preliminary studies of jet substructure observables unfolded with 
MultiFold1, a machine learning method, that simultaneously considers…"
("From this dataset" not required; "a machine learning method" is a 
parenthetical element here, not "unfolded with MultiFold")
Line23: "…jet observables." -> "…jet observables in the STAR 
experiment."

Regards
Nihar


On 2022-06-18 00:35, Youqi Song wrote:
> Hi Nihar,
>
> Thanks for the comments! I have updated the abstract on the drupal
> page. I removed the sentense of jet substructure observables being
> useful for heavy-ions since I noticed that there's a character limit
> of 1300 and I am slightly over that. I am also not too sure how to
> include the reference of MultiFold since there doesn't seem to be a
> place for footnotes on the submission page wordbox.
>
> Best,
> Youqi
>
> On Fri, Jun 17, 2022 at 1:07 PM Nihar Sahoo via Star-hp-l
> <star-hp-l AT lists.bnl.gov> wrote:
>
> > Hello Youqi,
> >
> > My comment and suggestion on your nice abstract can be found below.
> >
> > Title: "UNFOLDING JET SUBSTRUCTURE OBSERVABLES WITH  MACHINE
> > LEARNING
> > METHOD IN STAR √s = 200 GEV pp COLLISIONS"
> > -> "UNFOLDING JET SUBSTRUCTURE OBSERVABLES WITH  MACHINE LEARNING
> > METHOD
> > AT √s = 200 GEV IN pp COLLISIONS IN STAR"
> >
> > Line#6_ "       …from a common initial parton …" -> "…from an
> > initial parton…"
> > Line#8-9: "jet substructure measurements can provide insights into
> > perturbative evolution of the parton, and  the ensuing
> > non-perturbative
> > processes." -> "jet substructure measurements in vacuum can provide
> > insights into the parton evolution and  the ensuing non-perturbative
> >
> > processes like the fragmentation and hadronization."
> > Line#18:                MultiFold  -> provide reference of PRL
> > paper.
> > Line#23: "We will compare the “MultiFolded” spectra of the
> > observables
> > with the previously published STAR data "  I think  better not to
> > promise too much at this moment. Otherwise You have good abstract;
> > so my
> > suggestion would be just to focus on MultiFold Method and procedures
> >
> > only on data. You can add all these comparison later stage if you
> > will
> > have.
> >
> > Besides, you could mention a couple of sentences in the first part
> > of
> > your abstract on "ML part of unfolding" like why it is useful and
> > important to adopt, etc? For example before line#12 or 17.
> >
> > Regards,
> > Nihar
> >
> > On 2022-06-09 02:28, 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/59908
> > >
> > > ---
> > > If you have any problems with the review process, please contact
> > > webmaster AT www.star.bnl.gov
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