So I think we can start with the presentation. So the first speaker is iden
groomer from Atlassian. Who will present electronically the case of light states
and the rate for please item, you already share the screen. Thanks for speaking. Hi,
I'm here. Yeah.
Right. Yes, thanks for the introduction.
I'll be presenting results from both Atlas and CMS today on the B SMU and the Tao
two, three new results. So this will cover both CMS and Atlas. Like I was saying
they're very similar detectors. They do have some differences though. The the
inner diameter on CMS is four centimeters with 80 million readout channels for the
inner tracker, and the Atlas is 3.3 with 100 million, but maybe most significant
for this talk is the The difference in the magnetic field of 3.8 Tesla for CMS and to
Tesla for for the ATLAS detector. So to jump right into the BS to me of the
result, the Atlas result can be found at this link here, and it's performed on 26.3
inverse femto barns effectively at 13 TV in the 2015 and 2016 data as well as the
25 inverse of two barns from the run one data and CMS also here is shown with the
link to their paper here, and 36 inverse femto barns are used in 2016 data
separated into two categories, just based on operational instabilities experienced
with the microstrip detector in CMS. So, that's separated into 2016 A and 2016 B
and then the 25 interoceptive burns from run one are also Included in this CMS
results, and I'll discuss that further. So the motivation for looking at BST mew is
primarily the smallness and precision of the predictive branching fractions. And
you can see the Standard Model predictions here on the slide for the branching
fractions vs mew and B to review at orders of 10 to the minus nine and 10 to the
minus 10 respectively. We can also probe the standard model in measuring the
effective lifetime. So CMS has a nice result on the effective lifetime of the
BST mew and the experimental world average for the heavy state heavy mass Eigen
state. lifetime of BS is what is shown on the slide. any significant deviations from
the standard model would would indicate new physics. So, these could occur in in
models such as MSM more minimal flavor violation. And a couple of Fineman
diagrams of these if these types of models are shown on this slide as well. The
branching fraction is measured using the master equation here on the slide, you
have the yield of B sub d a b or b sub s. And, and its efficiencies, the event
efficiencies times the acceptance and then this is measured with respect to the
normalization channel, B plus two j cy k plus, which is abundant and has a very
well measured branching fraction. And so we also then have the hadron ization
fraction in the master equation as well. The analysis for both CMS and Atlas are
performed as blind analyses where we conceal the signal regions and then set
all of the procedures for performing the analysis and extracting the signal until
until those are set and then and then unblind the data You can see the blinding
regions here are in dotted lines with the signal Monte Carlo for B sub s as well as
be to me view, Monte Carlos, and those are fit with double Gaussians does the signal
regions are defined slightly differently between Atlas and CMS but but it's a it's
a similar idea. And Monte Carlo simulations are generated for the signals
as well as the background regions. And then there's also a Monte Carlo generated
for the P plus two j sy k candidates reference channel.
The background is composed of common tutorial background, which is a dominant
common story of background. The it consists of muons from uncorrelated hadron
decays, and it's characterized by not having much dependence on the debut on
invariant mass. A BDT is used to separate the continuum background for both CMS and
Atlas. The BTT discriminator values are shown on this slide. indicated the
boundaries are indicated with the arrows here. So, you have the sideband data
compared to the signal MonteCarlo a value greater than closer to one indicates more
signal like the partially reconstructed the Ks contribute as as a background here
in the analysis, you can see them in this a lot of information here on this slide
for the partially reconstructed decays these have mostly accumulate in the low
sideband region of the of the analysis. And the peaking background is also shown
here in the middle plot. You have the hadrons misidentified as nuanced in the
background. And so, these are these are simulated with Monte Carlo as well. The
reference channel extraction is shown here on the slide. This is B plus two j cy k
plus for both CMS and Atlas and The the extractions are shown here. So, the
backgrounds that contribute to the fit of the of the signal here are the P plus two
j cy k plus decays as the signal that can be that can be both suppressed to be plus
two j Sai pi plus the partially reconstructed decays and the continuing
background as well. And in CMS, the data is split between the 2016 A and 2016 b but
it's also further split into pseudo rapidity regions of the most forward new
on the yields for Atlas and CMS are also shown on this slide, but this is just
showing the reference channel yields. And then finally, the signal extraction and
results are presented on this slide. The Standard Model expectation for atlases 91
events for N sub s, the B sub s yield and N sub D is taking And then compared to to
the extraction of the Atlas results 80 and minus 12 for density. CMS is also
determined for each each BDT bin and data subset category that I explained in the
previous slide. And and their results for the yield are presented here as well. And
so, this has shown for Atlas for the highest vdt been and for CMS for all bins
in in all data subset categories including one the branching fractions are compared
here. So you have the BW on the vertical axis and the vs to medium on the
horizontal axis and, and the confidence level lines are shown in the in the curves
on the plot as well. The central point is shown in black for the combination of run
one and run two and compare it to the standard model and read in both in both
Results there. So, the the boxes show the final results of the Bs dimeo measurements
are shown in the upper lines and the the upper limits on the branching fractions of
the two new are also shown here. For Atlas, the name on construction is used
for, for performing the comparison of the
for performing the results of the printing fraction limit.
The lifetime measurement from CMS was presented in their paper as well. So a two
dimensional unbid maximum likelihood fit is performed on both the decay time the
proper decay time and the diamond on mass. And this fit includes the signal and each
background component, as you can find on the slides here that combinatorially
peaking and semi metallic decay again. So the tau two Mumia results is presented
here 1.7 and And you can compare it to the experimental world average of the heavy
mass I can state lifetime 1.6 time
picoseconds
I'm going to shift over to tau two three mew now. And so for Atlas the paper you
can find here in the journal and this is performed with 20.3 inverse femto barns of
at the center of mass energy ATV. And the CMS results is also presented today and
this is what 33 inverse femto burns 13 TV data. motivation for performing this
analysis is the is that if we were able to see charged leptons flavor violation, it
would be a major breakthrough in our understanding, and the branching fraction
is expected to be very small, by the standard model. You can see it's Let's
suppose it's predicted to be less than 10 to the minus 14, but some extensions to
the Standard Model lead to branching fractions many orders of magnitude greater
than this and and could be in within reach of experimental confirmation. And so,
these these branching fractions could be held up to 10 to the minus 10 or 10 to the
minus eight. And a couple of Fineman diagrams and models beyond the standard
model are shown or shown here. Atlas analysis uses a source of left tailed
leptons from decaying from a W boson to a towel and a neutrino and the town neutrino
from the W bosonic. appears in the analysis as a missing transverse energy.
You can see the diagram here on the right where the W goes on is produced in the
primary vertex and subsequently decays to a townie hotel and neutrino which is
picked up as the missing inverse energy, that missing transverse energy. And the
nuance subsequently that when a tau decays to three neurons, this is characterized by
also having a small opening angle cone around those three neurons. The branching
fraction is calculated with respect to the WW yield and here we have the acceptance
and the efficiencies. So, this is the master equation for this analysis. Atlas
picks up on pre selects events three with three new on vertex vertices and our a
three neon vertex and it and these events are required to meet blue selection
criteria. These selections include the three neon mask vertex fit, and or the
three neon vertex fit as well as the missing energy selections. The full
selection lists as can be found In the background and the backup slides, a BDT
discriminator is trained on a signal Monte Carlo and the background events in the BDT
training region, you can see the feed at training regions in this in this bullet
here, and a loose cut on the BDT is applied where x zero is set equal to minus
0.9, where BDT runs between minus one and one and this just removes a very
background like events. Finally, tight selection criteria are applied on top of
this. So, tight selection and the loose PDT cut are applied to look at the
analysis variables. So, you see the analysis variables here for the transverse
missing energy as picked up by the tracker and the significance of the three neon
vertex that
usually means Thank you.
So the results are shown here on this slide you have the BDT distribution, the
optimal BDT cut is found based on optimizing the x spected upper limit of
the branching fraction that's set to 9.0 point 933. You can see the second Monte
Carlo difference between the background as well here and the three Mian mass
distribution is shown on this slide. You have the loose selection criteria the
loose PDT cut and the tight selection criteria data shown in the black points
and one event passes the tight selection criteria plus the tight BDT cut a fit to
the BDT. The sideband data is also shown here just to show you what the background
looks like in the signal region. And an observed upper limit on this branching
fraction is 3.76 times 10 to the minus seven and a 90% confidence level. The CMS
results is shown on this slide the production of the of the center This is
from D marathons two to town neutrino as well as B. So, the production of these is
shown on these bullets here. The events are selected based on two neurons in a
track and the branching fractions are measured with respect to the normalization
channel D to phi pi, the data are separated based on mass resolution
categories. So, you have three nice resolution categories and a BDT is trained
in each each one of the categories and, and you can see the BDT output in this
slide here. The BDT regions are optimized based on the search sensitivity and signal
extraction. And And so, the top two bins are used for for signal extraction. The
mass resolution distributions are shown here you have the three different
categories for each of the mass resolutions. The signal Monte Carlo, the
signal here shown in red is normalized as if the branching fraction were set to be
minus 10 to the minus seven. And the yields are shown in the signal and data
categories for the full mass range, as well as the signal range in parentheses.
The upper limit for the cmas results is 8.8 times 10 to the minus eight at a 90%
confidence level. And so this is a very nice result as well. So the summary of the
results are shown here you have the branching fraction measurements of the BS
to mew as well as the upper limits of the bmu from both Atlas and CMS Atlas in blue
and CMS and read. The effective lifetime measurement measured by CMS is shown here.
And the upper limits on the Tao the three new branching fractions from from both
Atlas and CMS results are
are nicely done and performed here.
So thanks very much for your attention. Please, please let me know if you have
questions.
Thank you very much for this very nice presentation and also for respecting the
time contracts. So question, you should raise your hand using the bottom in the
bottom part of the screen. I have a question to start this time the discussion
on about the B zero result on page number B nine. You can go back to your 1999 huh?
Yes, yeah, from the plus side. So I have a difficulty with this all you have both.
Either on one or two, you have a central radio, let's say that is negative. So
he's, for sure. Of course he's not physical. It's saying not so I can
Question that are related to this fact. So, the first thing is if you study some
possible sources of these effects that can be maybe related to background subtraction
something like that. And the second question is, how did you manage these,
this effect a when you go to the limit says you start from a number that cannot
be
say should be a fluctuation cannot be
the same from numbers.
So, I can I can say that Atlas is fully aware that it's an unphysical to have a
negative branching fraction, but it's but it is certainly possible to have this
statistical this particular statistical value can take on negative values. And so
the reason that the name on construction is implemented to perform to show the
upper limit on the branching fraction Exactly for this. So it's handled by
instead of just doing likelihood contours. We apply the name on
bands in this analysis.
Thank you. I don't know. And the other thing, do you think that can be some
background that is not completely described since you have the same
negative, not the same, but you have the negative values both for the wrong one
around to try to understand why this isn't? Why do you think?
So? I mean, I,
I think that the negative value is just a function of the statistic itself. So it's
a low, low branching fraction compared to BS. And
I think, with more statistics, we'll be able to probe this further.
Thank you very much. So are there any other question? Try to either end you have
time just for one very short. Otherwise you can move. Oh, yes.
There is a question. Yes.
Okay. There is one. Ah, Gregor, try to try to speak.
Quick question. Is there any reason you're not measuring the effective lifetime in
Atlas, you should be able to do this similar precision down CMS.
I think that there's no reason Atlas can't do this.
I think we got triggered. I think it's a nice day like 10 cuts.
I
sorry, I mean,