STAR Flow, Chirality and Vorticity PWG

["Wang, Fuqiang" <fqwang AT purdue.edu>]

Jagbir,

 

See comments below.

 

Best regards,

Fuqiang

 

 

> -----Original Message-----

> From: jagbir <jagbir AT rcf.rhic.bnl.gov>

> Sent: Friday, May 14, 2021 3:01 PM

> To: Wang, Fuqiang <fqwang AT purdue.edu>

> Cc: esumi.shinichi.gn AT u.tsukuba.ac.jp; ptribedy AT rcf.rhic.bnl.gov;

> jiangyong.jia AT stonybrook.edu; levanfinch AT gmail.com; aihong AT bnl.gov;

> aggarwal AT pu.ac.in; STAR Flow, Chirality and Vorticity PWG <star-fcv-

> l AT lists.bnl.gov>; star-cme-focusgroup-l AT lists.bnl.gov

> Subject: Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New

> York time zone)

>

> Dear Fuqiang,

>

> Thank you for your nice reply with analogy. Please see my reply below:

>

> 1. These plots are simply Delta gamma, right? Then they are expected to be non-

> zero. I don't understand the statement here "the correlated background is zero".

> What do you mean?

>

> The correlated background is obtained by restoring the charges of shuffled and

> flipped charges in each event which in this case means one gets original default

> AMPT event in which delta gamma is zero. So, the correlated background is zero.

>

[Fuqiang Wang] I'm confused. Why does default AMPT give Delta gamma = 0?

 

> 2. How did you obtain the points on slide 25? Is it red-black and blue-black of

> some sort from slide 24? How were the black points on s25 obtained?

>

> All points on slide 25 are for different samples (i.e., Fix-1(Red),

> Fix-2(Blue) and AMPT(Black)) obtained from slide 24 as discussed earlier i.e.,

>

> (delta_gamma_data - delta_gamma_shuffle - delta_gamma_corr)/delta

> gamma_data

>

> delta_gamma_shuffle is not shown in slide 24. This presentation is regarding the

> comments.

> Black points are for default AMPT.

[Fuqiang Wang] Does the default AMPT have Delta gamma = 0 as you said above?

>

> 3(a). f_DbCs from events shuffled +/- particles <-> Nch from events shuffled

> charged/neutral particles

>

> We consider f_DbCS from data itself in different centrality bins not just from

> Shuffled.

>

> 3(b). We take difference between real signal and shuffled signal.

>

> We first take difference between gamma_OS and gamma_SS for data as well as

> for charge shuffled events. So we get two delta gamma, one for data (without

> shuffled) and other for charge shuffled events. Now the difference is taken

> between the delta gamma data and delta gamma charge shuffled to get f_CME.

> How do you take difference between real signal and shuffled signal?

>

> 3(c). You're seeing positive Delta gamma in large f_DbCs events;

>

> We see positive Delta gamma in large f_DbCs in data as well as in charge

> shuffled.

>

> 3(d). I'm seeing neutral/charged>1/2 in peripheral events and <1/2 in central

> events. I'll see this even when neutral/charged=1/3 is independent of centrality

> (not to say possibly centrality-dependent neutral/charged).This is called

> selection bias.

>

> Did you get these number from running AMPT and how many events were used?

> Are you seeing this in shuffled events? How it can happen let me understand this.

> I hope during shuffle you keep number of charged particles and neural particles

> same in each event. If it is so how this ratio of neutral/charged can change after

> shuffle. Centrality bin you define by the number of charged particle. So if

> number of charged particle in each event remain the same, as you keep Nch and

> neutral same during shuffle, so the centrality bin should remain the same. So this

> ratio of neutral/charged should remain the same in peripheral events as well as

> in central events you had before shuffle. You have wrote about neutral/charged

> for charge shuffled events. You did not write any thing about real events

> whereas we discussed both real data and charge shuffled.

>

> During shuffle I keep the number of positive and negative particle same in each

> event and also keep flow in. Alice collaboration used event shape engineering to

> probe CME signal (Phys. Lett. B777, 151 (2018)).

> Here, each centrality is divided into 10 bins depending on Q value. Is this

> selection bias?

>

[Fuqiang Wang] Because you brought up the analogy of f_DbCs to centrality, so I was using neutral/charged to tell you that your enhanced f_DbCs events are mostly, if not all, selection bias. The neutral/charged in my example serves different purpose from the +/- in your analysis. Please think about it.

 

> Thank you,

>

> With Best Regards,

> Jagbir Singh

> Panjab University

> Chandigarh

>

>

> On 2021-05-11 20:53, Wang, Fuqiang wrote:

> > Jagbir,

> >

> > Please see my comments below.

> >

> > Best regards,

> > Fuqiang

> >

> >> -----Original Message-----

> >> From: jagbir <jagbir AT rcf.rhic.bnl.gov>

> >> Sent: Tuesday, May 11, 2021 7:44 AM

> >> To: esumi.shinichi.gn AT u.tsukuba.ac.jp; ptribedy AT rcf.rhic.bnl.gov;

> >> jiangyong.jia AT stonybrook.edu; levanfinch AT gmail.com; aihong AT bnl.gov;

> >> aggarwal AT pu.ac.in; Wang, Fuqiang <fqwang AT purdue.edu>

> >> Cc: STAR Flow, Chirality and Vorticity PWG

> > <star-fcv-l AT lists.bnl.gov>; star-cme-

> >> focusgroup-l AT lists.bnl.gov

> >> Subject: Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am

> > (New

> >> York time zone)

> >>

> >> Dear Fuqiang,

> >>

> >> Thanks for your nice comments. Please find below my reply to your

> > comments.

> >>

> >> 1. Effectively, your signal after subtraction of correlated

> > background will

> >> average to zero within a centrality bin.

> >>

> >> Not true, In case of Fix-1 and Fix-2 substracting the correlated

> > background

> >> which is obtained from default AMPT, signal is not zero within

> > centrality bin as

> >> the correlated background is zero (Slide 18 & 19).

> >>

> > [Fuqiang Wang] These plots are simply Delta gamma, right? Then they

> > are expected to be non-zero. I don't understand the statement here

> > "the correlated background is zero". What do you mean?

> >

> >> 2. You divide this centrality bin into 10 bins according to your

> > dumbbell variable,

> >> in real event and in shuffled event. You take the difference of two,

> > so you're

> >> deemed to have some bins positive and other bins negative. You are

> > always

> >> going to have CME signal no matter what (except the rare case where

> > all bins

> >> are zero).

> >>

> >> Not true, In slide 24 (slide 25 for f_{CME}) we do not see any CME

> > signal for

> >> default AMPT.

> >>

> > [Fuqiang Wang] How did you obtain the points on slide 25? Is it red -

> > black and blue - black of some sort from slide 24? How were the black

> > points on s25 obtained?

> >

> >> 3. I don't think you can take such a liberty to claim positive bins

> > as CME signal

> >> and ignore negative bins.

> >>

> >> We are categorising events depending on the back-to-back charge

> > separation as

> >> one divides events in to different collision centralities depending

> > on the impact

> >> parameter or event multiplicity. The positive bin corresponds to

> > gamma positive

> >> for opposite-sign charge pairs and gamma negative for same-sign

> > charge pairs

> >> which means same sign charge pairs are strongly correlated whereas

> > opposite-

> >> sign charge pairs are weekly correlated which is considered as the

> > CME signal.

> >> The negative bin corresponds to opposite-sign charge pairs strongly

> > correlated

> >> (negative gamma) and same-sign charge pairs weekly correlated

> > (positive

> >> gamma) those evens look

> >> like normal events i.e, no CME signal.

> >>

> > [Fuqiang Wang] Let me use your analogy of f_DbCs binning ßà centrality

> > binning:

> > Your selection is f_DbCs ßà my selection is Nch f_DbCs from events

> > shuffled +/- particlesßà Nch from events shuffled charged/neutral

> > particles Delta gamma ßà neutral/charged ratio We take difference

> > between real signal and shuffled signal.

> > You're seeing positive Delta gamma in large f_DbCs events; I'm seeing

> > neutral/charged>1/2 in peripheral events and <1/2 in central events.

> > I'll see this even when neutral/charged=1/3 is independent of

> > centrality (not to say possibly centrality-dependent neutral/charged).

> > This is called selection bias.

> > I cannot claim those neutral/charged>1/2 events as some exotic

> > physics, and ignore the neutral/charged<1/2 events (or vice versa).

> >

> >> Thanking you,

> >>

> >> With best regards,

> >> Jagbir Singh

> >> Panjab University

> >> Chandigarh

> >>

> >> On 2021-05-06 13:23, jagbir wrote:

> >> > Dear all,

> >> >

> >> > These are our email exchange from December last year. We have

> > answered

> >> > all the comments earlier.

> >> > Please check.

> >> >

> >> > Thank you,

> >> > Jagbir Singh

> >> > Panjab University

> >> > Chandigarh

> >> >

> >> >

> >> > On 2020-12-17 16:40, jagbir wrote:

> >> >> Dear Fuqiang,

> >> >>

> >> >> Please find my replies here below:

> >> >>

> >> >> In the rightmost data points, the f_cme signals appear negative

> >> >> beacuse of substracting the correlated background. But we

> > interpret

> >> >> CME-like signal if gamma_ss is negative and gamma_os is positive

> >> >> which is the case for leftmost data points whereas for the

> > rightmost

> >> >> data points gamma_ss is positive and gamma_os is negative, so

> > these

> >> >> rightmost points do not correspond to CME-like.

> >> >> So, for the rightmost data points, we can not interpret it as

> >> >> negative f_cme signal.

> >> >> The rightmost points correspond to normal behavior where opposite

> >

> >> >> sign charged particles are correlated and same sign charged

> > particles

> >> >> are uncorrelated.

> >> >>

> >> >> Thank you,

> >> >>

> >> >> With regards,

> >> >> Jagbir Singh

> >> >>

> >> >> On 2020-12-16 03:40, Wang, Fuqiang wrote:

> >> >>> Jagbir,

> >> >>>

> >> >>> Thanks for the plot. So you interpret the leftmost points as

> > from

> >> >>> CME and extract a CME fraction from it. What physics would you

> >> >>> interpret the rightmost data points where the signals appear

> > negative?

> >> >>>

> >> >>> Best regards,

> >> >>> Fuqiang

> >> >>>

> >> >>>

> >> >>>

> >> >>>> -----Original Message-----

> >> >>>> From: jagbir <jagbir AT rcf.rhic.bnl.gov>

> >> >>>> Sent: Tuesday, December 15, 2020 8:55 AM

> >> >>>> To: Wang, Fuqiang <fqwang AT purdue.edu>

> >> >>>> Cc: STAR Flow, Chirality and Vorticity PWG

> >> >>>> <star-fcv-l AT lists.bnl.gov>; star-cme-

> > focusgroup-l AT lists.bnl.gov;

> >> >>>> aggarwal AT pu.ac.in

> >> >>>> Subject: Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed)

> > 9:30am

> >> >>>> (New York time zone)

> >> >>>>

> >> >>>> Dear Fuqiang,

> >> >>>>

> >> >>>> Please find my replies below:-

> >> >>>>

> >> >>>> ------------------------------

> >> >>>>

> >> >>>>       1. because your selection is predominated by statistical

> >> >>>> fluctuations yet

> >> >>>>       you're applying a cut on those statistical fluctuations.

> >> >>>>

> >> >>>>       Our selection is not by statistical fluctuations but

> > based on

> >> >>>> fractional

> >> >>>>       Dumbbell charge separation in the data. However, similar

> > type

> >> >>>> of charge

> >> >>>>       separation can be due to statistical fluctuations, to

> > account

> >> >>>> for that

> >> >>>>       we are using charge reshuffle. Now we are having about

> > 160M

> >> >>>> events.

> >> >>>> It is

> >> >>>>       seen that observed delta gamma in the data is large

> > beyond

> >> >>>> statistical

> >> >>>>       fluctuations than those of charge reshuffle for  the top

> >> >>>> 0-20%

> >> >>>> Db+-max

> >> >>>>       bins. The plot you asked is attached here with email.

> >> >>>>

> >> >>>> ------------------------------

> >> >>>>

> >> >>>>       2. I mean the max Dbmax_shuffle bin is a random

> > collection of

> >> >>>> events from

> >> >>>>       this centrality bin.

> >> >>>>

> >> >>>>       The max Dbmax_shuffle bin is not a random collection of

> >> >>>> events from

> >> >>>>       this centrality bin. As explained earlier we generated

> > charge

> >> >>>> reshuffle

> >> >>>>       events by reshuffling charges of partices in the real

> > data in

> >> >>>> a given

> >> >>>>       collision centrality. So, charge reshuffle events are

> >> >>>> completely independent

> >> >>>>       sample from real data sample in  given centrality though

> >> >>>> number of

> >> >>>>       positive/negative charged partciles are kept same in each

> >

> >> >>>> reshuffle event

> >> >>>>       corresponding to real data event. Again  Dbmax_shuffle

> > bins

> >> >>>> are made

> >> >>>>       according to the fractional Dumbbell charge separation in

> > the

> >> >>>> charged

> >> >>>>       reshuffle event sample for a given collision centrality.

> >> >>>>

> >> >>>> ------------------------------

> >> >>>>

> >> >>>> Thank you,

> >> >>>> Jagbir Singh

> >> >>>>

> >> >>>>

> >> >>>> On 2020-12-14 22:46, Wang, Fuqiang wrote:

> >> >>>> > Jagbir,

> >> >>>> >

> >> >>>> > Please see my replies below.

> >> >>>> >

> >> >>>> > Best regards,

> >> >>>> > Fuqiang

> >> >>>> >

> >> >>>> >

> >> >>>> >

> >> >>>> >> -----Original Message-----

> >> >>>> >> From: jagbir <jagbir AT rcf.rhic.bnl.gov>

> >> >>>> >> Sent: Monday, December 14, 2020 11:18 AM

> >> >>>> >> To: Wang, Fuqiang <fqwang AT purdue.edu>

> >> >>>> >> Cc: STAR Flow, Chirality and Vorticity PWG

> >> >>>> >> <star-fcv-l AT lists.bnl.gov>;

> >> >>>> >> star-cme-

> >> >>>> >> focusgroup-l AT lists.bnl.gov; aggarwal AT pu.ac.in

> >> >>>> >> Subject: Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed)

> >

> >> >>>> >> 9:30am (New York time zone)

> >> >>>> >>

> >> >>>> >> Dear Fuqiang,

> >> >>>> >>

> >> >>>> >>     Please find my replies below:-

> >> >>>> >>

> >> >>>> >> 1.   I understand your motivation doing that but I don't

> > agree this is

> >> >>>> >> the right approach

> >> >>>> >>     (I think it causes biases).

> >> >>>> >>

> >> >>>> >>     Please let me know why this is not the right approach

> > and

> >> >>>> >> what kind of biases you meant.

> >> >>>> > [Fuqiang Wang] because your selection is predominated by

> >> >>>> > statistical fluctuations yet you're applying a cut on those

> >> >>>> > statistical fluctuations.

> >> >>>> >

> >> >>>> > Can you plot (data-chrgR. Bkg) and (Correlated bkg) vs (Dbmax

> >

> >> >>>> > bin) on slide 25 so we can see the details better?

> >> >>>> >

> >> >>>> >>

> >> >>>> >>

> >> >>>> >> 2.   you have only one point left. Your f_cme is basically

> > the

> >> >>>> >>       (Delta gamma of those events in that Dbmax bin)

> >> >>>> >>       - (Delta gamma of a random collection of events in the

> >

> >> >>>> >> same centrality bin which happen

> >> >>>> >>       to have the same Dbmax_shuffle bin)

> >> >>>> >>       - (Delta gamma of those same random events calculated

> >> >>>> >> after the charges are shuffled)

> >> >>>> >>       Do I understand it correctly?

> >> >>>> >>

> >> >>>> >>     If only one point is left as you wrote, please see the

> >> >>>> >> explanation

> >> >>>> >> below:

> >> >>>> >>

> >> >>>> >>     Here, there is nothing like random collection of events

> > in

> >> >>>> >> the same centrality bin.

> >> >>>> > [Fuqiang Wang] I mean the max Dbmax_shuffle bin is a random

> >> >>>> > collection of events from this centrality bin.

> >> >>>> >

> >> >>>> >>     We select events depending on Db+-max i.e., depending on

> > the

> >> >>>> >> back-to-back charge

> >> >>>> >>     separation fDbCS = Db+-max-1. As you wrote only one

> > point,

> >> >>>> >> in that case it is the

> >> >>>> >>     top 10% Db+-max events corresponding to maximum

> > back-to-back

> >> >>>> >> charge separation events.

> >> >>>> >>     It is similar to selecting events in particular

> > collision

> >> >>>> >> centrality depending on

> >> >>>> >>     the impact parameter or event multiplicity. As we have

> >> >>>> >> selected in the data top 10%

> >> >>>> >>     Db+-max corresponding to maximum back-to-back charge

> >> >>>> >> separation events, in  same way

> >> >>>> >>     we select events from charge reshuffle in the same

> > collision

> >> >>>> >> centrality for top 10%

> >> >>>> >>     Db+-max(here Db+-max of charge reshuffle) corresponding

> > to

> >> >>>> >> maximum

> >> >>>> >> back-

> >> >>>> >> to-back

> >> >>>> >>     separation. Now we get delta_gamma_data of real data

> > events

> >> >>>> >> corresponding to top

> >> >>>> >>     10% Db+-max of data and delta_gamma_sta of charge

> > reshuffle

> >> >>>> >> events corresponding to top

> >> >>>> >>     10% Db+-max of charge reshuffle for a given collision

> >> >>>> >> centrality which gives

> >> >>>> >>     us delta_gamma due to statistical fluctuations. Now for

> >> >>>> >> correlated background we

> >> >>>> >>     look for real events in the data corresponding to the

> > top

> >> >>>> >> 10%

> >> >>>> >> Db+-max

> >> >>>> >>   of charge

> >> >>>> >>     reshuffle in a given centrality and get delta_gamma_cor

> > from

> >> >>>> >> those real

> >> >>>> >>     data events.

> >> >>>> >>

> >> >>>> >>     Now the f_CME is obtained as

> >> >>>> >>

> >> >>>> >>     f_CME = N1*(delta_gamma_data - delta_gamma_sta -

> >> >>>> >> delta_gamma_cor)/(delta_gamma_data * N)

> >> >>>> >>

> >> >>>> >>     Where N1 is number of events in top 10% Db+-max and

> >> >>>> >>     N is total number of events in a given collision

> > centrality.

> >> >>>> >>

> >> >>>> >> Thank you,

> >> >>>> >> With regards,

> >> >>>> >> Jagbir Singh

> >> >>>> >>

> >> >>>> >> On 2020-12-14 10:32, Wang, Fuqiang wrote:

> >> >>>> >> > Jagbir,

> >> >>>> >> >

> >> >>>> >> > Thanks for your answers.

> >> >>>> >> >

> >> >>>> >> > To your questions:

> >> >>>> >> >> Please clarify the following

> >> >>>> >> >>       Of course you've also removed the large

> > charge-shuffle

> >> >>>> >> >> background which is basically

> >> >>>> >> >>       an autocorrelation effect (sort to speak) due to

> > the

> >> >>>> >> >> Dbmax (and

> >> >>>> >> >> Dbmax_shuffle)

> >> >>>> >> >>       selection bias.

> >> >>>> >> > I was just saying it in passing, referring to the fact

> > that

> >> >>>> >> > you're largely selecting on statistical fluctuations and

> >> >>>> >> > trying to remove the auto-correlation effect by shuffling.

> > It wasn't a

> >> question.

> >> >>>> >> >

> >> >>>> >> >>       Please explain the following:

> >> >>>> >> >>       So is your finite signal really due to the

> > difference

> >> >>>> >> >> between the average of ratios

> >> >>>> >> >>       and the ratio of averages (or perhaps also due to

> >> >>>> >> >> residual effect from shuffling)?

> >> >>>> >> > I was referring to the fact that if you had a single Dbmax

> > bin (i.e.

> >> >>>> >> > taking average first and then ratio) then you'd get zero

> >> >>>> >> > signal by definition. You now have 10 bins and take ratios

> >

> >> >>>> >> > first in each bin and then take average of the ratios, and

> > get a positive

> >> signal.

> >> >>>> >> > During the focus meeting discussion, it was made clear

> > that

> >> >>>> >> > your analysis required multiple Dbmax bins, not taking

> > average

> >> >>>> >> > of all bins, but only those with Delta gamma > 0. So now I

> >

> >> >>>> >> > think I understand technically how you did it. I

> > understand

> >> >>>> >> > your motivation doing that but I don't agree this is the

> > right

> >> >>>> >> > approach (I think it causes

> >> >>>> biases).

> >> >>>> >> > So let me try to understand better:

> >> >>>> >> > On slide 9 of your focus meeting presentation

> >> >>>> >> >

> > https://drupal.star.bnl.gov/STAR/system/files/CME_FOCUS.pdf,

> >> >>>> >> > you

> >> >>>> >> > state:

> >> >>>> >> > (1) If Delta gamma_bkg. is negative then it is taken as

> > zero.

> >> >>>> >> > (2) If gamma_SS is not negative and gamma_OS is not

> > positive

> >> >>>> >> > then delta gamma = 0.

> >> >>>> >> > Now to slide 25, let's take one centrality say 40-50%, you

> >

> >> >>>> >> > have the blue points (signal) and red+green points (bkg).

> > The

> >> >>>> >> > 8 points to the right of this centrality: all of them have

> >

> >> >>>> >> > negative bkg and negative Delta gamma, so they are not

> > counted

> >> >>>> >> > in your calculation of CME fraction. Now you're left with

> > the

> >> >>>> >> > two leftmost points. Do both points satisfy (2) above? I

> > know

> >> >>>> >> > both points seem to have

> >> >>>> >> > bkg>0 & Delta

> >> >>>> >> > gamma>0 but it's unclear if they satisfy SS<0 & OS>0.

> > Assume

> >> >>>> >> > gamma>they do,

> >> >>>> >> > then you're taking average of these two data points. For

> > the

> >> >>>> >> > sake of simplicity, let me say you have only one point

> > left.

> >> >>>> >> > Your f_cme is basically the (Delta gamma of those events

> > in

> >> >>>> >> > that Dbmax bin)

> >> >>>> >> > - (Delta gamma of a random collection of events in the

> > same

> >> >>>> >> > centrality bin which happen to have the same Dbmax_shuffle

> >

> >> >>>> >> > bin)

> >> >>>> >> > - (Delta gamma of those same random events calculated

> > after

> >> >>>> >> > the charges are shuffled) Do I understand it correctly?

> >> >>>> >> >

> >> >>>> >> > Best regards,

> >> >>>> >> > Fuqiang

> >> >>>> >> >

> >> >>>> >> >

> >> >>>> >> >

> >> >>>> >> >> -----Original Message-----

> >> >>>> >> >> From: jagbir <jagbir AT rcf.rhic.bnl.gov>

> >> >>>> >> >> Sent: Sunday, December 13, 2020 10:12 AM

> >> >>>> >> >> To: Wang, Fuqiang <fqwang AT purdue.edu>

> >> >>>> >> >> Cc: STAR Flow, Chirality and Vorticity PWG

> >> >>>> >> >> <star-fcv-l AT lists.bnl.gov>;

> >> >>>> >> >> star-cme-

> >> >>>> >> >> focusgroup-l AT lists.bnl.gov; aggarwal AT pu.ac.in

> >> >>>> >> >> Subject: Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020

> > (Wed)

> >> >>>> >> >> 9:30am (New York time zone)

> >> >>>> >> >>

> >> >>>> >> >> Dear Fuqiang, all,

> >> >>>> >> >>

> >> >>>> >> >>    Sorry for not answering your email. Infact, I did not

> > look this

> >> >>>> >> >>    email. Please go through my replies below:

> >> >>>> >> >> ------------------------

> >> >>>> >> >>

> >> >>>> >> >>   1. A few events do not satisfy this cut so not

> > including in

> >> >>>> >> >> it

> >> >>>> >> >> Db+-max

> >> >>>> >> >>      but in overall calculations all events are included.

> >

> >> >>>> >> >>

> >> >>>> >> >>   2. Yes

> >> >>>> >> >>

> >> >>>> >> >>   3. We reshuffle charges in each event. We donot

> > randomize

> >> charges

> >> >>>> >> >>      according to the positive/negative charge ratio of

> > the

> >> >>>> >> >> given event.

> >> >>>> >> >>      In fact, we pick up one event and reshuffle

> >> >>>> >> >> positive/negative charges

> >> >>>> >> >>      keeping theta,  phi, number of postive charges and

> >> >>>> >> >> number of negative

> >> >>>> >> >>      charges as such. After this we calculate gamma

> > correlator.

> >> >>>> >> >> This procedure

> >> >>>> >> >>      is repeated for each event. The Db+-max of reshuffle

> >  is

> >> >>>> >> >> a bit bit wider

> >> >>>> >> >>      than the  real distribution which may be due to some

> >

> >> >>>> >> >> correlations in the

> >> >>>> >> >>      real data whereas reshuffle is purely randomize.

> > Db+-max

> >> >>>> >> >> binning is

> >> >>>> >> >>      done on the basis of same fractions.

> >> >>>> >> >>

> >> >>>> >> >>   4. Let me explain this point

> >> >>>> >> >>

> >> >>>> >> >>      We pick up a real data event and calculate following

> >

> >> >>>> >> >>      i)  Dbmax+- of real data event

> >> >>>> >> >>      ii) reshuffle charges in an event

> >> >>>> >> >>

> >> >>>> >> >>      iii) again calculate Dbmax+- and termed it Db+-max

> > of

> >> >>>> >> >> charge reshuffle

> >> >>>> >> >>      iv)  calculate gamma of real data event

> >> >>>> >> >>      v)   calculate gamma of reshuffle event

> >> >>>> >> >>

> >> >>>> >> >>      Now for a given centrality

> >> >>>> >> >>      Steps i) to v) repeated for each event. Db+-max

> > (data)

> >> >>>> >> >> and

> >> >>>> >> >> Db+-max(reshuffle)

> >> >>>> >> >>      sliced into ten percentile bins.

> >> >>>> >> >>      Now average gamma is found in every sliced Db+-max

> >> >>>> >> >> (data) and

> >> >>>> >> >> Db+-max(reshuffle)

> >> >>>> >> >>      from the respective event samples. It should be

> > noted

> >> >>>> >> >> that events in the top

> >> >>>> >> >>      say 10% Db+-max(data) are not the same as in the top

> > 10%

> >> >>>> >> >> Db+-max(reshuffle) i.e,

> >> >>>> >> >>      real events in the top 10% Db+-max(data) are

> > different

> >> >>>> >> >> from those top 10%

> >> >>>> >> >>      Db+-max(reshuffle). Now the correlated background is

> >

> >> >>>> >> >> caculated from the real events

> >> >>>> >> >>      corresponding to the top 10% Db+-max(reshuffle)

> > events.

> >> >>>> >> >>

> >> >>>> >> >>       Please clarify the following

> >> >>>> >> >>

> >> >>>> >> >>       Of course you've also removed the large

> > charge-shuffle

> >> >>>> >> >> background which is basically

> >> >>>> >> >>       an autocorrelation effect (sort to speak) due to

> > the

> >> >>>> >> >> Dbmax (and

> >> >>>> >> >> Dbmax_shuffle)

> >> >>>> >> >>       selection bias.

> >> >>>> >> >>

> >> >>>> >> >>   5.  Db+-max distribution is sliced in to ten percentile

> >

> >> >>>> >> >> bins which represent

> >> >>>> >> >>       different amount of charge separation in each

> > sliced

> >> >>>> >> >> db+-max bin.

> >> >>>> >> >> Let us

> >> >>>> >> >>       say we have Db+-max = 2, in this case fractional

> >> >>>> >> >> dumbbell charge separation

> >> >>>> >> >>       f_DbCS = Db+-max-1=1 i.e., 100% back-to-back charge

> >

> >> >>>> >> >> separation i.e.,

> >> >>>> >> >>       positive charged particles on one side of the

> > dumbbell

> >> >>>> >> >> and negative charge

> >> >>>> >> >>       particles on other side of the dumbbell. So,

> > computing

> >> >>>> >> >> gamma in different

> >> >>>> >> >>       Db+-max and calculating things is different from

> > just

> >> >>>> >> >> making a single wide

> >> >>>> >> >>       bin as you mentioned. This method is designed to

> > get

> >> >>>> >> >> CME-like enriched sample

> >> >>>> >> >>       in given collision centrality as one divides all

> > events

> >> >>>> >> >> into different collision

> >> >>>> >> >>       centralities depending on either the impact

> > parameter

> >> >>>> >> >> or event multiplicity but

> >> >>>> >> >>       one does not study all events taken together

> > without

> >> >>>> >> >> making different

> >> >>>> >> >>       collision centrality classes. However, for a single

> >

> >> >>>> >> >> wide

> >> >>>> >> >> Db+-max bin as you

> >> >>>> >> >>       wrote we will get zero signal.

> >> >>>> >> >>

> >> >>>> >> >>       Please explain the following:

> >> >>>> >> >>

> >> >>>> >> >>       So is your finite signal really due to the

> > difference

> >> >>>> >> >> between the average of ratios

> >> >>>> >> >>       and the ratio of averages (or perhaps also due to

> >> >>>> >> >> residual effect from shuffling)?

> >> >>>> >> >>

> >> >>>> >> >>

> >> >>>> >> >> Thank you,

> >> >>>> >> >>

> >> >>>> >> >> with regards,

> >> >>>> >> >> Jagbir Singh

> >> >>>> >> >>

> >> >>>> >> >>

> >> >>>> >> >>

> >> >>>> >> >> On 2020-11-18 23:18, Wang, Fuqiang wrote:

> >> >>>> >> >> > Hi Jagbir,

> >> >>>> >> >> >

> >> >>>> >> >> > Your results are quite interesting. I have a few

> > further

> >> >>>> >> >> > questions about the details of your analysis:

> >> >>>> >> >> > 1. For each event you have Dbmax with the condition of

> >> |Dbasy|<0.25.

> >> >>>> >> >> > You bin events of each centrality in Dbmax. You use all

> >

> >> >>>> >> >> > events in your analysis (i.e. you're not throwing away

> >> >>>> >> >> > events based on Dbmax or Dbasy), right?

> >> >>>> >> >> > 2. In your calculation of gamma=<...>/v2c for a

> > particular

> >> >>>> >> >> > Dbmax bin of a given centrality, the v2c is calculated

> >> >>>> >> >> > using those events only, right?

> >> >>>> >> >> > 3. For the charge reshuffle, you reshuffle the charges

> > of

> >> >>>> >> >> > all events, and repeat your analysis from step 1 (i.e.

> > you

> >> >>>> >> >> > treat this as a completely separate "new" data sample),

> >

> >> >>>> >> >> > right? Did you "randomize" the charges according to the

> >

> >> >>>> >> >> > positive/negative charge ratio of the given event? On

> > s11,

> >> >>>> >> >> > the Dbmax_shuffle distribution is a bit wider than the

> > real

> >> >>>> >> >> > distribution, do you understand why? How do you bin the

> >

> >> >>>> >> >> > Dbmax and Dbmax_shuffle into

> >> >>>> >> >> > 10 bins, respectively (same bin edges or same

> > fractions)?

> >> >>>> >> >> > 4. Your correlated background gamma is calculated for

> > the

> >> >>>> >> >> > Dbmax bin where Dbmax is from the charge-shuffled

> > events,

> >> >>>> >> >> > but using restored charges, right? If so, then you're

> >> >>>> >> >> > effectively taking gamma difference between Dbmax_i

> > events

> >> >>>> >> >> > and Dbmax_shuffle_i events (which are different

> > events),

> >> >>>> >> >> > right? Of course you've also removed the large

> >> >>>> >> >> > charge-shuffle background which is basically an

> >> >>>> >> >> > autocorrelation effect (sort to

> >> >>>> >> >> > speak) due to the Dbmax (and Dbmax_shuffle) selection

> > bias.

> >> >>>> >> >> > 5. You divide Dbmax (and Dbmax_shuffle) into 10 bins

> > and do

> >> >>>> >> >> > your analysis in each bin separately, and then take the

> >

> >> >>>> >> >> > weighted average for your f_cme result. You could just

> > use

> >> >>>> >> >> > a single wide Dbmax (and

> >> >>>> >> >> > Dbmax_shuffle) bin, then in principle you should get

> > zero

> >> >>>> >> >> > signal because the correlated "background" is your real

> >

> >> >>>> >> >> > signal since they are now identical event sample. So is

> >

> >> >>>> >> >> > your finite signal really due to the difference between

> > the

> >> >>>> >> >> > average of ratios and the ratio of averages (or perhaps

> >

> >> >>>> >> >> > also due to residual effect from

> >> >>>> shuffling)?

> >> >>>> >> >> >

> >> >>>> >> >> > This is a complicated analysis. It would be really good

> > to

> >> >>>> >> >> > have more discussions so the details can flesh out

> > better.

> >> >>>> >> >> >

> >> >>>> >> >> > Thanks,

> >> >>>> >> >> > Fuqiang

> >> >>>> >> >> >

> >> >>>> >> >> >

> >> >>>> >> >> >

> >> >>>> >> >> >> -----Original Message-----

> >> >>>> >> >> >> From: Star-fcv-l <star-fcv-l-bounces AT lists.bnl.gov> On

> >

> >> >>>> >> >> >> Behalf Of jagbir via Star- fcv-l

> >> >>>> >> >> >> Sent: Tuesday, November 17, 2020 10:49 AM

> >> >>>> >> >> >> To: ShinIchi Esumi

> > <esumi.shinichi.gn AT u.tsukuba.ac.jp>;

> >> >>>> >> >> >> STAR Flow, Chirality and Vorticity PWG

> >> >>>> >> >> >> <star-fcv-l AT lists.bnl.gov>

> >> >>>> >> >> >> Subject: Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020

> >

> >> >>>> >> >> >> (Wed) 9:30am (New York time zone)

> >> >>>> >> >> >>

> >> >>>> >> >> >> Dear ShinIchi, Prithwish and Jiangyong,

> >> >>>> >> >> >>

> >> >>>> >> >> >> I would like to give "Update on event by event charge

> >> >>>> >> >> >> separation in

> >> >>>> >> >> >> Au+Au collisions at 200GeV with STAR detector"

> >> >>>> >> >> >>

> >> >>>> >> >> >> Please add me to agenda.

> >> >>>> >> >> >> I will post my slides later.

> >> >>>> >> >> >>

> >> >>>> >> >> >> Thankyou,

> >> >>>> >> >> >> Jagbir Singh

> >> >>>> >> >> >>

> >> >>>> >> >> >> On 2020-11-16 15:57, ShinIchi Esumi via Star-fcv-l

> > wrote:

> >> >>>> >> >> >> > Dear FCV PWG colleagues We will have our weekly FCV

> >> >>>> >> >> >> > PWG meeting on coming Wednesday

> >> >>>> >> >> >> > 18/Nov/2020

> >> >>>> >> >> >> > 9:30AM (in BNL) at our usual time and place. So if

> > you

> >> >>>> >> >> >> > have anything to present, please let us know and

> > please

> >> >>>> >> >> >> > post your slide by

> >> >>>> >> >> Tuesday.

> >> >>>> >> >> >> > We'll talk about the "HLT express productions" in

> > the

> >> >>>> >> >> >> > beginning of the meeting as you see in the agenda

> > page.

> >> >>>> >> >> >> > Jiangyong, please send a link to your slide from

> > last week.

> >> >>>> >> >> >> >

> >> >>>> >> >> >> > The zoom room link, ID and password are in our usual

> >

> >> >>>> >> >> >> > drupal agenda page below.

> >> >>>> >> >> >> > Please also keep in mind that all the preliminary

> > plots

> >> >>>> >> >> >> > should have already been there in the summary area

> > below.

> >> >>>> >> >> >> > Best regards, Jiangyong, Prithwish and ShinIchi

> >> >>>> >> >> >> >

> >> >>>> >> >> >> > Meeting agenda page with zoom link :

> >> >>>> >> >> >> >

> > https://drupal.star.bnl.gov/STAR/blog/jjiastar/bulkcorr

> >> >>>> >> >> >> >

> >> >>>> >> >> >> > Preliminary page :

> >> >>>> >> >> >> >

> > https://drupal.star.bnl.gov/STAR/pwg/bulk-correlations/b

> >> >>>> >> >> >> > ulkco

> >> >>>> >> >> >> > rr-

> >> >>>> >> >> >> > pre

> >> >>>> >> >> >> > lim inary-summary

> >> >>>> >> >> _______________________________________________

> >> >>>> >> >> >> > Star-fcv-l mailing list Star-fcv-l AT lists.bnl.gov

> >> >>>> >> >> >> > https://lists.bnl.gov/mailman/listinfo/star-fcv-l

> >> >>>> >> >> >> _______________________________________________

> >> >>>> >> >> >> Star-fcv-l mailing list Star-fcv-l AT lists.bnl.gov

> >> >>>> >> >> >> https://lists.bnl.gov/mailman/listinfo/star-fcv-l