You have left
Okay, thank you for introduction and I will start with the outline of the
presentation. So, so, I will I would like to present four measurements you know
start with the left arm measurement which is focused on production production and
electronic furniture distribution in certain events, then we will continue with
some past checks differential measurements, measurement is focused on
differential measurement cross sections and gathered on the doctor sections and
even with all atonic measurements which is focused on differential section. So, let's
stop it go to measurement. This measurement is done in a new channel. This
means that it is required exactly one elect And random neon opposites charges in
event selection and this major event is entered into the proton proton collisions
taken in 2015 and 2016. So, this corresponds to the monitor to the basics.
And the strategy is to extract the DT value section from the set of the two
equations which are on this slide and, and this cross section is extracted together
with the parameter epsilon Venus is the probability that we required from the
electronic decay is constructed as jet and so, these two equations the first equation
is with events with exactly one v jets and the second To switch to technique jets and
and to the me also, because this is the right hand side of this equation. So, then
you have to take that times cross section this will give us total number of events
and then it is multiplied by efficiencies. So, the efficiency of immune
reconstruction This includes also branching ratio to immune channel and that
is this epsilon V which is already described and CB corresponds to small
correlation between lagging states and you can see that it is very close to one when
one corresponds to no correlations, no correlation. So, now let's have a look on
results of this measurement. So, the central value is 126.4. ico ban And
uncertainties are classified into four sources. and here we can see that the
uncertainty related to luminosity is dominant. And in order to know in order to
reduce this uncertainty we we are this measure this session was measured in in
2015 to 17 2016 separately in the first step and then these two measurements were
combined using best linear unbiased estimator. And this reduced the final
artifact certainty from about 2.7% to 4%. And this makes matters very precision. It
is I think, it is the best from topless experiment and under on the right we can
see Comparison with next text ad go through plus next next week predictions.
Comparison with the last results and agreement is very good. Now Now let's have
a look on differential cross sections. These sections were measured in the finish
and finish off a space at particle level. And here we can see left on et. And the
plot on the left shows the shape of measured data. This is indicated by like
points and distributions are compared with various predictions with different
configurations and with different parameters and with different data sets.
And in general, we see that they are dancing in variations over data ratios and
this is also confirmed in chi square test for web development.
Below 0.05 for all predictions, except the one at this seminar, last week I had a PDF
set. So so this is for the electron measurement. And let's continue with
differential measurement in lepton politics channel. This measurement use
uses exactly the same data set but it is demographic channel and then two
topologies which were used to reconstruct the
reconstructed DVR system.
This is the full TT VR system reconstruction. So both both of blacks are
reconstructed results. pathology is focused on long term PT and where three
quads from top decay are concerning you is in three different jets while the boosted
topology Focus on high entropy theory regime where we have the top and make up
the case by itself very similar directions and direction and they are reconstructed
with the with the single large radius jet distributions aren't fully to particle and
bottom level. So let's move on can fiducial face spaces outside particular
those are other elective at spectra result on the left and boosted on the right. You
can see different ranges of spectra result in the rest of the project we start at
zero at boosted we started in 350 gV, but then shift to the ipts much the tail in is
much longer in the boosted so
So, these measurements can
provide different information and the trends in in the ratio plots are similar
in both both cases in both reconstructions but they are actually consistent. They are
not significant according to PayScale dot test. Our predictions are actually good
data.
Now let's have a look on double differential sections. This is TT bad PT
in bits of at band mass. So, on the left we have pt, pt spectra in various bands of
TT bar mass. And this is the information about Vinson sim diligent and also we can
also we spend this internal PT but PT distributions are scaled by factor
syndicated in Beckett's you know the to avoid some overlaps and on the right hand
side then there is they are they show plots for individual bins of Tiki Bar mass
and you can see the differences between the predictions and also differences
between predictions and data are very large. So, so, it is very hard to validate
such differential sections and actually our predictions fail to describe this
according to chi square test if you are inside of a better logo below 0.01. Now,
this measurement also measured at the bottom this bottom number and there it is,
this was used also to compare them with next next to median for the predictions
and on the left that is pretty bad at Distribution Center in this competitive
market must be tightened also with this next next reading or the predictions and
but we see that here we have a good agreement of the magic spectrum with
predictions and the plot on the right is particularly interesting because it is to
start to test sensitivity to different next week's reading for the PDF sets and
also possible addition of next meeting or directory corrections and and you can see
here the different points corresponding to different predictions with with or without
actually corrections etc. But they are very similar and the conclusion is that
sensitivity is very low in kinematic tential based measurement. Okay, so now
let's continue with this is all from differential measurement. composition and
continuity includes projection measurement. And this is done with a with
float on two data sets eight to 10 1318 months one and two. And, but but results
are only determined at a scale and strategy is to classify selected events
into four signal regions according to number of jets and number of big jets as I
said as shown in the table. And then, in these three regions we have Yes,
differential variables which are then using which are used to extract cross
sections
by using simultaneous profiling to fit.
So, let's have a look on this distributions differential distributions
on the top if you have breakfast distributions in difference
acknowledgments and also defended in each region views the different different
variable which has the best sensitivity to or has seen them best for for the
measurement of the debarker section and the parameters of interest, this parameter
of interest this ratio of the tobacco section over the standard model prediction
and all sources of uncertainties, they can assess as parameters in the fits below we
can see posterior distributions which and they are the agreement is improved after
faith. Now, this can be seen. Just notice that the survey mentioned the ratio plots
is different.
So, okay
I think this is an offer For this and I will just continue with the results. So,
also the measurement measure session in the English, but in the full face basis,
it doesn't need an 3140 coupon, they can certainly uncertainties about 4.46% in
photo finisher, last section that uncertainty is a little bit smaller this
4.1% because there is not so much extrapolation and and this this results
are with particular language model predictions and also with other published
measurements. And this measurement also provides dependency of the tobacco
sections of the mass which can be used to measure of mass in in the future.
You have three minutes left
Okay, thank you. So, the last is organic, last measurement is organic. And here I
would like to point out that this is for the first time in that experiment, we
measured organic differential plus a section in another channel in the rest of
topology that is still relevant in the in the event selection it is requested at
least six jets in an event in order to be able to reconstruct for Tiki Bar system,
and exactly two of these jets must be detected in order to reduce Multijet
background and Ashtanga toccata is applied in order to reduce the other events from
other channels. And in order to reconstruct the device's system it is
needed to fit through the combination of light jets And this is done with the
combination minimizes the chi square this describes which is shown on this slide. So
let's have a look on the results. So on the sorry, nearly everything of PT the
products are, according to PT. So under Latvia detector distribution, here we can
see how much they don't have in basic knowledge and that the dominant background
originates is from Multijet processes. And it is, it is determined using data driven
techniques called ABCD method. In the plot in the middle we have future particle face
base distribution. And here you can see that the uncertainties are around 10%. So,
so this is actually good results with the fact that mentioned In this channel source
for basic tinnitus challenging and now we have
nice results and also on the right we have we have
measurement from face by face distribution and you can see that Transcender
predictions over data are similar in in in fiducial and face space but but it's
expect this shows that that predictions are still in good agreement except of the
Sherpa and pilots plus be tired with with relation down Okay. So now I would like to
continue in double differential intersections here df dT by dt in bins of
number of jets So, so this it was possible to measure differential motion even in
translate nine or more jets and
I'm afraid you Have to speed up the time
good. So, this is
sorry okay. So, I just
say that the chi square test shows very, very bad agreement between prediction data
and this assertion is also sensitive and I will try to summarize the presentation.
So, so, so the printed measurements are in all three main entity back channel. The
darker sections were measured in lepton patch sets and in depth on channel a bit
improve pedic decision or Atlas. Differential measurements now includes a
double referential cross section which are monsen more sensitive to the level that
predictions and also other or MC modelling can PDF it and it is important to mention
also the techniques leading up to the etheric corrections that are tested in
electronics. It's gentle and it was founded that it has almost no impact on in
the in the given kinematic range. And, and since I present it or other measurement
now I will skip this part and so think Thank you. Thank you for your attention.
And I'm sorry, I'm, I was a bit longer with this presentation and I don't have a
link to the zoom but I will try to create this this zoom link now and attach it to
the slides or to the agenda directly.
Okay, perfect. Thank you very much.
Are there any questions to this presentation?
I have one.
I was I was wondering if I look at slide 11. If Can you go back to your slide 11
where you show profit profit distributions. I was impressed by the
amount of constraints you get in in the systematic uncertainties, could you
elaborate on that which which systematic uncertainty in particular get constraints,
it is clear from the above distribute the rescue plots that the systematic
uncertainty seems to be an overestimation. But I wonder what that sources or what are
the sources?
Yeah, we have actually some sources of of the uncertainties on the slide. Those are
the main sources and some of them are are significant are reduced. That's right. But
that could be also other effects that we are exactly to the same distributions,
which are used in the fate and that could be some other effects of this has to be
also validated with some different distribution and it was validated, but I
don't have these plots, but so, there could be some other effect of this. But
here we can see that what are the main sources
so, I'm not familiar reading of this, this kind of clock, but should I read the data
points that shrink down which shows the constraint on the
data that is the profit is
or the profit is valid.
mentioned display shows actually how this parameter the change in the parameter. So
for example, for the sixth level responses parameter is shifted the last in the fate.
So it is shower modal migration that
is showing auto migration So constraint a lot. I think there's this Chevron modeling
concern of certainty. It is actually to two sources one of them is constraint but
other one not too much.
I see the two months
yes and
yes. So, I would like to explain that for the brief it in a post with uncertainties
most of the reduction actually does not come from the constraints of the
systematic uncertainties but by taking into account the correlations of the
numerous parameters that are estimated during the fitting procedure.
Okay, can you go back to slide 11 again,
so, I'm comparing the band and the above and the bottom. So you're saying that some
of the correlations are not taking into account at the above?
Well in the above which assume that they are datasets parameters aren't
uncorrelated, so we added them in quadrature. But in the post feed, we
actually can get the correlations of the nuisance parameters for these
distributions. And we can build the plots, taking into account the correlations and
this is by far the dominant source of the reduction of the uncertainty.
Okay, okay. Thank you. You're welcome. Thank you.
Okay, great, thanks to one. And then I think we have to move on. Thanks, Peter.
And if you can make webinar linked on your slides and re upload your slides for later
that would be nice.