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Subject: STAR Flow, Chirality and Vorticity PWG
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Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone)
- From: jagbir <jagbir AT rcf.rhic.bnl.gov>
- To: "Wang, Fuqiang" <fqwang AT purdue.edu>
- Cc: star-cme-focusgroup-l AT lists.bnl.gov, levanfinch AT gmail.com, aggarwal AT pu.ac.in, "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)
- Date: Thu, 20 May 2021 22:37:24 +0530
Dear Fuqiang,
Thanks for your reply. Please see my reply below:
1. I may have misunderstood you, but Delta gamma != 0 in default AMPT.
You are right Delta gamma != 0 in default AMPT as shown in slide 19. But while calculating the f_CME we use:
f_CME = ( delta_gamma_data - delta_gamma_shuffle - delta_gamma_corr )/delta_gamma_data
delta_gamma_shuffle and delta_gamma_correlated are backgrounds presented in earlier presentation. Here, f_CME comes out to be round zero for the default AMPT (slide 25) using the SDM.
2. Selection bias is obvious--it happens when you use the same particles to make selection and look for signals.
Here, since we are looking for the back-to-back charge separation on an event-by-event basis which is similar to the searching for the back-to-back high transverse momentum particle (high pt) trigger and associated particle pt trigger. Here, one uses different ranges of pt for trigger particle and associated particle. So, in these situations one uses the same particles to make selection and look for
signals. I am using the similar procedure for the charge shuffled events and f_CME is obtained as mentioned above subtracting charge reshuffle and correlated backgrounds.
3. In such cases you cannot pick and choose. You have to take into account all data, not just those f_DbCS with positive Delta gamma only.
I am using all data in a given centrality with the condition that gamma correlator for same sign charge pairs should be negative whereas for opposite sign charge pairs it should be positive as required for the CME.
Thank you,
With Best regards,
Jagbir Singh
On 2021-05-19 00:26, Wang, Fuqiang wrote:
Jagbir,
I may have misunderstood you, but Delta gamma != 0 in default AMPT.
This is because of background, and is precisely the reason why people
including yourself are using more sophisticated methods.
Selection bias is obvious--it happens when you use the same particles
to make selection and look for signals. In such cases you cannot pick
and choose. You have to take into account all data, not just those
f_DbCS with positive Delta gamma only. Another good example is
refmult. If you go look at the dN/deta from STAR data, you will see a
step at eta=+-0.5, and this is because the centrality is defined by
refmult within |eta|<0.5.
The LHC event shape engineering by Q-vector is not a selection bias
because forward detectors are used for the Q-vector, not the particles
of interest used for signal analysis.
Best regards,
Fuqiang
-----Original Message-----
From: jagbir <jagbir AT rcf.rhic.bnl.gov>
Sent: Tuesday, May 18, 2021 7:38 AM
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,
Thanks for your reply. Please see my reply below:
1. I'm confused. Why does default AMPT give Delta gamma = 0?
Because there is no CME in default AMPT.
2. Does the default AMPT have Delta gamma = 0 as you said above?
Yes
3. 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.
I brought up the analogy with centrality to make my point, as selecting events
with impact parameter is not a selection bias, like that selecting events with
f_DbCS is not a selection bias. f_DbCS is a event characteristic as impact
parameter. Small impact parameter leads to high multiplicity events whereas
large impact parameter give rise to small multiplicity events. As I wrote ALICE
collaboration divided the each collision centrality further in to ten bins according
to the Q value (Phys. Lett. B777, 151 (2018)). It selects larger flow events with
large Q value. Elliptic flow increases with increasing Q.
You did not tell me wether or not it is a selection bias.
4. I did not understand your statement "enhanced f_DbCS events are mostly, if
not all, selection bias".
5. Regarding The neutral/charged
I'm seeing neutral/charged>1/2 in peripheral events and <1/2 in central events.
You did not write how you got these numbers. Is it from simulation?
It can not happen in shuffling as I wrote earlier.
Thank you,
with Best Regards,
Jagbir Singh
Panjab University
Chandigarh
On 2021-05-16 06:22, Wang, Fuqiang wrote:
> 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 us__ing__ 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 diff__erent 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
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
jagbir, 05/06/2021
- Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone), Fuqiang Wang, 05/07/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
jagbir, 05/11/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
Wang, Fuqiang, 05/11/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
jagbir, 05/14/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
Wang, Fuqiang, 05/15/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
jagbir, 05/18/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
Wang, Fuqiang, 05/18/2021
- Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone), jagbir, 05/20/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
Wang, Fuqiang, 05/18/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
jagbir, 05/18/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
Wang, Fuqiang, 05/15/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
jagbir, 05/14/2021
-
Re: [Star-fcv-l] FCV PWG meeting, 18/Nov/2020 (Wed) 9:30am (New York time zone),
Wang, Fuqiang, 05/11/2021
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