vector boson scattering and vector boson fusion.
So you can start whenever you want Heather.
you have to unmute Heather.
I do have to unmute. that might help, wouldn't it? okay. uh.
right. so I'm going to talk about vector boson fusion and vector boson
scattering measurements. and what uh I mean by this, of course, is that you have
incoming quarks that emit vector bosons and then those vector bosons interact at a
point, either fused into a single vector boson or scatter into two new vector
bosons. however, there is an incredibly important point I need to mention here
before we carry on is that we cannot directly measure these V B F or V B S
processes. so there's a significant amount of interference interference with other
diagrams that are of the same order of alpha electroweak and extracting the V B F
or V B S component is not a gauge invariant operation. so we cannot measure these
processes
directly. and instead what we do is measure electroweak production of V J J
of course V is a W boson, a Z boson or a photon, or V V J J. and I will try to use that
language throughout my talk to be technically correct, um I might fail.
so aside from our uh electroweak production V B F electroweak production diagram, I have
another one here, you can see it has the same order in alpha electroweak on the
bottom left, we also have a very, a very large amount of strong V J J production. in
general, this has a much higher cross section with one exception of the same
sign W W
production. so because it's so large, uh we have a huge task in understanding and
reducing this background that it's absolutely crucial to do an effective
electroweak V J J or V V J J measurement. um so that's why most of my talk is actually
going to be discussing these strong or QCD backgrounds um.
and I will use the word sort of strong and QCD interchangeably because different
analyses are talked about and call them different things sort of in their in their
tables and plots, but it means the same thing.
okay, so I'm going to start by discussing our brand new electroweak Z J J production
result. the general characteristics of the events here in the electroweak events are
a leptonically decaying Z boson um and two jets with a large rapidity separation
and a large invariant mass. additionally, um in the electroweak production, there's
usually no jets in the gap between these these two forward fowards jets. um whereas
with for instance, strong production or main background, there tend to be jets
radiated every which way because this is what QCD tends to like to do.
so,
here I have a plot that shows the Monte Carlo data ratio for different processes,
um the strong in blue, electroweak and red and then the remaining backgrounds
tiny in orange. and you can see this across the spectrum for M J J. and the
important point takeaway point is a few things here. first off, the strong background is
the largest across the spectrum.
and the second one is that generators for both strong and electroweak production
show huge discrepancies between themselves. um and then, of course, then, none
of them are really modeling the data that well in the strong Z J J case. it's also
important to note that the strong Z J J modeling is especially poor in the signal
enriched region when you see this big divergence between
one of the predictions and the other two. Uh, and this is right where we want to do our
measurement. so we can't just take the Monte Carlo at face value and carry
on. instead, we have to deal with data driven background modeling, and this will
take care of the, the miss-modeling. so in order to do this, the analysis is split into four
regions with two uncorrelated
variables. the first one, the y-axis here is the number of jets in the gap
between the leading and subleading jets. and then the second one is the centrality
of the reconstructed Z boson. so just how, how much it is sort of in
between those two jets. this leaves us with three background enhanced regions
C R A, C R B, and C R C, control regions, and then one signal region that is enhanced, of course
in our electroweak Z J J signal. and we can use these three C R A B C regions to
constrain and understand our strong background, um and then use that
understanding to constrain the modeling in the signal enhanced region.
so of course, I talked about four regions, we're not just counting events um in each
bin, there's still the observables we want to perform the measurement in
that we actually have to consider. so here I'm showing everything for the dijet
invariant mass, so M J J is done in bin number, but this is just the whole M J J
spectrum
we do the analysis in.
on the left, these are the raw distributions before the Monte Carlo is
fit to the data. so you can see objectively there is some some, some quite bad
agreement there, we need to do something.
but, uh, the control regions A B C have minimal signal, lots of background, and we can use
these to constrain the background in the signal region. so in order to do this, we
do a binned maximum likelihood fit. and this is performed simultaneously in all four
regions. now the, the strong Z J J background is constrained with bin by bin weights
separately at low and high centrality, but it's linked between the number of gaps jets
so like C R A and S R have the same bin by bin weights and C R B and C R C have the same
bin by bin weights. 77 00:05:48,thirty-six0 --> 00:05:52,500 um, then there is a linear function of the variable being fit. so in this case, M J J
that allows for a correction for any residual dependence on the number of gap
jets so where that bin by bin linking might not work
a hundred percent, um there's a linear uh correction that uh helps fix that. and that's kept the same
between the low and high centrality regions applied in the signal region and
C R C. so it sort of helps with C R C helps then fix any any residual C R A to signal
region extrapolation um in the signal region. So finally, then you have the bin by bin
electroweak signal strength, this is what actually we want to extract the signal.
um these are kept the same between all of the regions. so you can see then in the post
fit plot that when you actually perform the maximum likelihood fit um it nicely
converges to describe the observed data. this is great. uh.
now, I did talk about of course, that we had these these three different Monte
Carlo generators that all gave vastly different predictions. and we didn't
really know which one of them is correct a priori. um and even after the fact we're not
sure, you know, until we do some proper unfolding which one better models the data
so, un what we actually
do, uh is do this fit with each of the generators. so it's done done three times.
and here I have the pre and postfit plots. also with the next to leading order
madgraph strong Z J J prediction. and, you know, hopefully, you can take away from this
that the extra or the fit also works with the, one of the alternative generators.
okay, so of course at the end of the day, we don't just check these and ignore two
of them, um we end up with three data points for each bin, for each electroweak signal
strength. so in each bin, the actual extracted signal is taken as the midpoint
of the envelope span. you can see my little sketch on the right here um displaying
what I mean. un so it's the midpoint of the envelope spanned by the three strong data
generators and then the spread is associated with a systematic uncertainty
or is an associated systematic uncertainty, sorry.
with these, you know signal strengths, both the signal and the control regions
are folded. uh so for instance, electroweak production
is only unfolded in the signal region because there isn't any in the control
regions. um but the inclusive Z J J production, we unfold this in the signal
region and in each of the four control regions. uh and this is so we can basically uh
use the data to the best of our abilities and show the modeling in more than just
the signal region for future Monte Carlo studies and generator studies.
so I've also consistently shown plots for the dijet invariant mass, um but the analysis
is also performed in the dijet rapidity spread the dilepton transverse momentum
and the delta phi between the higher and lower rapidity jets in that order.
ok. so beyond the measurement, we can also see if the measurement shows any hints of new
physics. to do this, um we use the dimension six effective field theory, uh this is the
SMEFT. and we look at both the interference terms. that's the first bluey red term, I
guess the second term in the equation at the top and then the um
quadratic term as well, which is uh the EFT only quadratic term and that's in the
middle there. now, the analysis tested two CP even and two CP odd operators. and it,
what's interesting to see in the table on the right here is for each operator, there's
two rows, the first one is using the linear um
EFT only and the second one was using the quadratic. and you can see that it's
really not a large effect. so the quadratic terms having a minimal effect on
the result of the whole and it's the linear term that is driving our
sensitivity. this sort of makes sense because um the linear term is linear in the
coupling whereas with a quadratic term, you have this uh the coefficient squared. uh.
now, something I should point out is the reason we actually have sensitivity to
these CP odd operators is by explicitly checking um a parity odd observable, and
in this case, the observable used is the one I just mentioned on the previous slide
the azimuthal angular separation between the two leading jets
calculated by subtracting the lower rapidity jet from the higher rapidity jet, always
in that order. so I have an example here of what that variable looks like unfolded
in signal region for the electroweak signal. and then one other thing you might
have noticed, in the observed
sort of ninety-five percent confidence limit for C tilde H W B doesn't actually include the
value zero. the value zero, of course, is the standard model with no EFT. so we'll talk
a little bit about that on the next slide.
so I first want to point out that we're not talking about an exclusion of the
standard model or discovery, right, this is just a ninety-five percent confidence interval.
um, but it's interesting to examine a little further here we can see you know how we
end up with this best fit value this one point two and not zero. so on the left, we have the
minimization of the negative log likelihood. and on the right, we have the
associated change in the EFT prediction as the coupling changes. so you can see both
the
interference and the quadratic terms. and then most of this contribution is coming
from the interference term. that's the dashed coral line as compared to the
purple that adds in the quadratic term as well. and then you can see basically,
given the data points, how we end up with this best fit value. and as we get farther
and farther away from the Standard Model, it doesn't really fit well, but then you
get down to this minimum value of one point two. and that distribution looks kind of a lot like
the data. and then as you get closer and closer and closer to zero, um, the data no
longer looks quite a lot like the um uh a lot well sorry
the prediction doesn't look a lot look a lot like the data anymore. so
this is a nice way of seeing how we end up with a specific value. okay, so that's
enough of a single boson on results. let's add another that Z boson into the mix and
study electroweak Z Z J J production. so here we either have two bosons decaying
leptonically, or one leptonic and one invisible. again, there are two jets.
still the same characteristic topology
explicitly on different sides of the detector now, with large rapidity
separation and large invariant mass.
the two channels um that I sort of just mentioned on the previous slide, four
lepton and L L nu nu have a slightly different selection, but it's largely the
same electroweak type phase space. uh the big difference in these two channels is really
the backgrounds. so with this L L nu nu channel, you have a very large uh, high non Z Z J J
background kind of getting in the way of the analysis. It's not as clean as
having two leptonic Zs. an inclusive Z Z J J cross section that's inclusive
of the QCD and the electroweak is extracted in the signal region. um but then
to extract the electroweak Z Z J J component a boosted decision tree is used
to discriminate between the electroweak and the QCD components. um now, the BDT isn't just
applied in the signal region we also apply it in the control region. and this is
better uh to allow us to better constrain the QCD background right this thing,
miss-modeling that keeps
popping up everywhere.
and then a separate BDT is trained for the L L nu nu signal region. so it's also a
multivariate discriminant there on the x-axis, but it's a different it's a
different one. we don't assume those are the same by any means. and you can see
that when you fit these simultaneously you get a combined expected
significance of four point three sigma. of course, we got a little lucky and we saw a five point five sigma
observed significance and thus we do have observation of electroweak Z Z J J
production. um the nice neat thing here is that the electroweak cross section here is
point eight two femtobarns. and this is actually one of the smallest cross
sections that ATLAS has measured so far.
okay, in my last minute, I'm going to touch briefly on one last analysis, and
that's electroweak production of a Z boson and a photon. so again, we have our
leptonic Z, but then we have a one photon and we make we do our best to ensure
this is not coming from final state radiation from those leptons because that
wouldn't be sensitive at all to the V B S diagrams we're trying to really probe
here. um the whole
Z plus photon system is required to be central sort of between the two jets. like
we have the Z centrality for the electroweak Z J J. and the two jets are
required to have the large rapidity separation and large invariant mass.
additionally, here, um, there's a no b-jet requirement in the events, we don't allow
that to happen.
so one thing to point out before going to the result is that this is a partial
run two result. so it's only using thirty-six inverse femtobarns of data.
and also that it's really important to look specifically at all of these different electroweak productions, because we want to ensure we have the full picture
of all of the quartic couplings. so with Z plus photon final state, we're
uniquely sensitive to the W W Z photon quartic coupling. whereas for instance, if
you're looking at W Z, you'd have contributions from um W gamma as your input
vector bosons, or W Z it as your input vector bosons. so if you saw some anomaly
you wouldn't know necessarily which diagram it was
coming from.
um now, in addition to this b-jet veto I I mentioned on the previous slide, the
events then that failed that, that have at least one b-jet are used to constrain the
ttbar plus photon background and make sure that we're not susceptible to any
miss-modelings there. so and like with the Z Z J J um
analysis, a BDT is used to discriminate between the electroweak and the large QCD
background, you see the BDT score distribution on the bottom left here, the
full distribution is fit simultaneously with the b-jet distribution in the ttbar
plus photon control region. and the extracted observed and expected
significance are both four point one sigma. so unfortunately, no luckily, lucky
statistical fluctuations here. but we still have a hundred inverse femtobarns of data to add
and and observe this process.
okay, so there's three additional results that I haven't talked about due to time
which I'm sure I'm out of. uh, we have.
um yeah, so the, sorry,
same sign W W J J, um this is we have observed this with six point five sigma.
um, the W Z J J with a five point three sigma observed significance and a semi-leptonic V V J J uh with
two point seven observed significance. all of these are thirty-six inverse femtobarn uh, run two uh analyses
and there are details in the backup if you would like to hear more. um so just in with
that, I'll conclude we have new differential cross-section measurement of
electroweak Z J J production with strong limits on new physics through an effective
field theory interpretation. we have observation of electroweak Z Z J J, and lots of
other partial run two uh dataset analyses. and many results with a full run two data set
are still to come and there's a link uh that's not a link at all, there's a list
of the meeting ID and password of for the poster session zoom chat if you would like
to discuss anything. thanks.
Thank you very much Heather. are there any questions? yes, there is a question.
from Josh
please go ahead. you're unmuted when you can.
thanks. uh yeah, so I had a question on slide five.
uh, so, in particular for for the two predictions here for the for the QCD
Z J J production, which are merged, merged multi leg N L O. I mean, I
wonder if you could comment on on ongoing efforts to understand, you know, the
uncertainties on those two predictions. and whether there's some hope to one day
replace this sort of two or three point model comparison uncertainty with one
which is driven by let's say, missing higher orders in QCD match matching
merging uncertainties or shower resummation uncertainties, which could
perhaps be a bit better defined from a correlation standpoint.
yeah, for sure. so this is this is part of the reason there there's been so much effort to
put out not just the electroweak signal extraction, but also the inclusive
differential cross sections for the different um different generators um in not just
the signal region, but also the different control regions in the hopes that this
information will be fed back to the community. and we can use this to look at
new predictions and then sort of run three iterations might be um using whole new
Monte Carlo predictions that fit the data much better in the end.
hope that answers your question. thanks.
so we can take another question from Kenneth. and then we will have to move
on. Kenneth you're unmuted as you can speak.
on slide seven, maybe you said I just didn't understand but the the bin by bin
weights that you apply to the V J J. these are derived independently of the fit and
basically applied before you do the maximum likelyhood fit, is that right?
no, they're part of the fit.
I mean, so is there is there a parameter that's free and the fit for each bin? uh no.
so not not for each bin. so uh the fit is done with three times the number of bins
plus two parameters. uh and there's obviously four times the number of bins um of actual
data to fit.
so is there I mean, are these weights allow for
essentially just the normalization to change? or do they somehow allow uh 261 00:19:thirty-six,600 --> 00:19:40,440 a slope could be to be introduced to the shape of the M J J?
yeah, so they definitely do because they're done bin by bin right, the weight
in each bin that comes out of the fit can be different,
are they constrained in some way. sorry, so they're linked between the the number of
gap debts of of greater than or equal to one and zero. so it's the same sort of in each
column.
so C R A and S R, the strong Z J J weights are identical, the same in that low
centrality region the same in the low in the high centrality region. um but they are
allowing for a bin by bin difference in each of the columns basically of that
little figure
ok thanks they'll be a more wide description uh in the paper. these are preliminary
results but in the paper when it ends up on arxiv, I encourage you to read it.
there is one more question from Stefano but we are a bit uh over time
now. so maybe I mean, Heather you will be available at the end on your own zoom room
so probably Stefano you can ask a question there. sorry.