Okay, so now I can see your slides. Yeah, in full screen mode. Perfect. Okay. You
are ready, you can start.
And it's Michael, I'm very glad to be here, even virtually hope to be in Paris
one day again. And really thank Allison all the coordinators for this opportunity.
So, in TMS we're wedged in in understanding wide variety of systems.
draw attention was brought to this possibility of, of understanding very
small systems, whether they
behave collectively.
Our interest essentially came from the observation of the rich in high
multiplicity PvP collisions. And this sort of really two aspects of this. One of them
is is whether we do see some approach to hide dynamics when 100 Amex becomes
applicable and they also the questions of what is the initial state There's a small
system look like
ah
What is it? What is the power spectrum of fluctuations inside a small system. And so
that's also what we're hoping to find
from these studies. So
so this this talk will focus on vn and cumulus measurements. And these sort of
flow correlations have been very helpful in standing, the pressure that's in it in
in heavier inclusions, and instead, we want to use these techniques to look for
collectivity in smaller systems. So today, I'll pretty much focus on proton land and
PvP and how we can try to subtract non flow effects
in those in those small systems.
So first timers, Chris TPP pled
So, a basic measurement would be to look at the second moment the v2, and we can do
this with just two particles four, six or eight or even all particles in the event
using the NGS and zeros. And so here on the left we see proton proton versus
proton lead versus lead lead. And we see this general rise of v2 with a number of
tracks. Now, in lead lead period, we see a difference between the v2 with a just two
particles and a larger PD cap, and then the higher order measurements of v2, and
we believe that this is because of the these high order v four v 242. Six are
better at subtracting non flow in Low multiplicity, these two sets of
measurements tend to come together. And and potent, potent. We don't see such a
difference between the two
the different types of measurement. So
let's look at another way of looking at this data. We can look at v2 v3 v4. And
there's different ways of tackling this one is to try to subtract the very low
multiplicity results from from the v2. And this by definition forces, v2 sub to go to
zero at Denver tax was this year. But when we look at these measurements, we see non
dual vetoes even down to very small values. Until again, this question of, of
always seeing is this real collectivity and try to explore this more.
So we've got also looked at different particles, and not just all hydrants. So
here we have charged hydrants versus neutral counts versus lambdas, 90 lambdas.
And we see different distributions, but when we scale by these numbers by the
number of quarks and look like the kinetic energy divided by the number of quarks, we
see this sort of universal scaling which has also been seen, especially in in heavy
hand collisions. And when we look at this in P, P, again, we see the same thing it's
clear difference in v2. For different product features a functional PT,
functional particles, we would express
expect this in a hydrogen amical situation.
But when we scale by the number of quarks, we get similar kinds of distributions for
the different add ons in proton lead and lead, lead, lead lead. Now hold on and
lead lead this agreement is better, of course, and see that there's some
deviation in the product lead for the two zeros. It's still the fact that the
particles are so nicely like the Omega so right on looks suggestive.
So let's go to slide number nine. So
here we're going to compare v2 and v3. And in
total on that and the lead, again, versus the number of tracks. And again, we're
we're doing different numbers of higher order correlations, both in v2 and v3. And
again, we see the the higher order correlations seem to cut down v2, which is
can we expect to be getting rid of non flow, but it all methods seem to converge
below about 100 tracks. So, another way of looking at these data is to try to look at
these ratios of v4 to v2. This is believed to be sensitive to the ratios of the
geometrical eccentricities.
And when we look at this ratio for over v.
So, v n for particle correlations of a VM from two particle correlations, we see a
gradual decrease with this is enough agreement with what we expect from the
scaling eccentricities. So, that that is very
here we see even higher order we see if we compare different ratios now, like we have
p 26324 and v two eight, a v2 six as a ratio v2 for the future
fy Two, two, we
were pretty nice height. with very high an ATV, we're very high statistics data, a
slight increase with these trends and the prediction is a reasonable agreement with
with the ratio of geometrical eccentricity. So that's nice. So, we
suddenly we've been trying to move towards using their cumulant methods to subtract
non flow contributions. And so we have these cumulative four particles, which of
two orders and an M, and they can be, they come as a ratio of the average cosine of
these, this column here, which can be broken down into n times the difference of
two particles, multiplied by m times a difference of four particles of two other
particles.
And then it could be talked about in the ratio of the
of
products of Viet.
Also we can use sub event methods to try to break down our acceptance and then also
try to get rid of short range correlations to the effect of sub sub event. So here we
see data from proton, proton, proton lead and lead lead as a function of the number
of tracks for these different order correlators. And if we start perhaps on
the on the right, you see the two three correlator going down with multiplicity
two for color going up. And so that change occurring around about 100 tracks. We see
in code on lead we see again this rapid drop below 100 and then a flattening
doesn't rise like that, but it is it flattens, and then the PS two data looks a
different kind of shape.
Above 100 so not so,
not quite the same as as I suppose a lead and the lead lead I should say that the
poteau lead clip access is somewhat compressed in multiplicity. So, now we can
another technique is to normalize these key words by the RMS of the v2 and the v3
and here we see proton proton proton lead.
This rapidity between point three to three gv
and this is the second third correlator can see a nice agreement between proton
lead and lead lead. That's not such a good agreement with with PGP. And again for the
two for a moment again we see pulled on ladder poaching lead ladder high
multiplicity But somewhat different in pp. So, if we sort of qualify this, this
defense as a, we can add to this the scale scale accumulates we can try to cut harder
by using the sub event method to suppress non flow even further. And we see again
that we have these cumulants seem to have got rid of non flow above about 100 below
100 D no sub event method shoots up. So, this is s two three and a similar
situation we've seen in the s document two four. I've wanted to for work in the know
some event method shoots up, whereas the higher multiple sub event methods Much
more flat. So this is suggested that the killer math, the suburban method is
helping to get rid of modular.
We can quantify this by looking at the difference between the three and two
suburban methods as a function of two sub event. And we see for the two, three
correlator, almost no difference. So it's doing a very good job of suppressing non
flow, there is a difference in
for the two for correlator. Between
and we, this this might be possible because we may be seeing an effect of the
event plan t correlation today. Not sure why there's this difference in the two
four correlated but event plan D correlation may be reason.
So finally, to our conclusions.
We've been trying to explain that the wide acceptance of CMS and ISIS two data sets
to Canada in multiple ways to try to suppress non flow. The data seem to be
suggesting that collectivities present in PP and perhaps p systems PNP systems with
tracks of the order of 100. It's, it's still, I'd certainly agree with the last
speaker that its situation in PvP is not clear. In the future, we will have a
larger tracker and we will try to push to
even smaller systems.
Thank you everybody for your attention.
Okay, thank you, Michael, for a very nice talk. So now we have time for discussion.
If you have a question, please press the right hand button. Okay, so we have one
bye you.
Okay, so now you are unmuted please ask your question.
Hello, very nice results from CMS. I hope you can hear me.
Yes, I have questions.
Yes. Oh, great. I have a small question slide elevens. So this this results are
really beautiful with the position man is from CMS in Chula ATV. However, I guess
the conclusion really depends on the correlation between V and eccentricity
coefficient, because we know that the empty lead, we might not have a strong
correlation or linear correlation between the two. Therefore, these conclusion might
be a little bit a little bit too strong. If you compare initial state to the final
state. Yeah.
So I do hope set that inventory we can have some smaller systems where we can
control we have we have more variation in the geometry. I think that has been an
advantage to the rep program.
And hopefully,
we can we can have that more inventory. I agree with you that it's It might be nice
to have an oxygen oxygen on this plot perhaps.
That would be very interesting.
Yeah. So I, I agree with you that this is rather theoretical dependent.
Do we have more questions? Sorry, I couldn't respond. I have a question on
slide eight. I want to know what is the variable on the x axis?
Oh, so what is it is the kinetic energy. So what you do is you take the total
energy of the particle and you subtract the transverse, the mass of the system. So
it's, it's, it's the kinetic kinetic transverse energy, which is p x the square
root of p x squared plus p y squared minus m squared. I'm sorry. I apologize. I
apologize for that. To find, and then it's divided by the number of cooks. So you
divide by two for me zones, and you divide by FIFA barians. So I apologize that
wasn't introduced to the problem. Thank you.
All right, do we have time for one more question to this presentation?
Okay, I don't see any. Okay. There's another one here.
Yeah, please go on
version one, slide nine. I don't know if there's new development in understanding
of the low morphism region, while we see v two four is higher than v two two.
It's like mine
because from from the Federation, corner view, it's very hard to understand if v
two four is higher than the two to
eight Yeah, I would. You You You mean the lead lead placed here?
Give me this point. I wouldn't. I would bet that it's the tie with it. I think
within the systematic, it's consistent. I agree. I agree with you. But I think we
have the data in tables and I can look to see if it's statistically. It there's
actually a significant difference, but I don't think so. This so i
i wouldn't I would base that on done and the one point there.
All right. Thank you, Michael. I think we have to switch to the last presentation.