So everyone I will be presenting recent searches for our parody violating Susy at
the LHC. Starting with a brief introduction, our parody is a
multiplicative quantum number. To find this equation here, you can see that it
depends on the particles baryon number lepton number and spin. It is plus one for
the ceremonial particles and minus one for their super symmetric partners. Our parody
is not a symmetry of the most general local SSM Lagrangian, and here I've shown
the parody violating portion of the super potential. And in addition to violating
our parody these first three terms violate lepton number, and this last one violates
baryon number. So these terms are often prevented by imposing our parody
conservation and as a result, very odd number and phone number are still
conserved and the proton is stable. And as a bonus Susan is is conserved so the LSP
is neutral and stable and is therefore a dark matter candidate. However, this
banishing of all rpv terms might be a bit heavy handed since some amount of RPC is
fine. For example, a model only needs to conserve baryon number or left on number
to prevent proton decay. And in general, the limits on our PV are less stringent
when only some of the terms are nonzero. And when you allow for IPv, there could be
a few consequences. leptons violating terms can generate light neutrino masses,
which is pretty nice. Additionally, the LSP can carry charge indicator model
particles and the strength of the couplings can lead to various attack
signatures. So down here at the bottom of this cartoon showing the effects of
turning on one of these rpp couplings on the left from the couple of years zero you
have our purity conservation and the LP is stable. For small couplings, the LSP
becomes long lived and it has to displace the Kaizen detector for a bit more
moderate coupling so you have prompt decays And finally for order one couplings
you can simply produce particles. So here is an outline for the rest of this talk. I
will Start off by discussing some searches for the strong production of Scorpion
gluey nose, then the electroweak production of charred Geno's and
neutrinos. I will then show a few Long live searches and then at the end, I will
discuss the process of setting limits on our coupling strengths. Okay, so first we
have a CMS search for BMS visit BSN physics and events with Jetson Sims on
leptons. This search requires either to same sized leptons, or at least three
leptons, and additionally requires at least two jets. And this final stage is
rarely produced in certain model, but it's pretty common in many VSM scenarios. And
the search targets and has interpretations for a wide range of RPC and rpv signals.
And among these are two rpv benchmark models with coil speeds. You can see the
Fineman diagrams above. On the left, Guinan undergoes a fight party decay via
the Qd coupling and on the right and undergoes a three body decay to the We
have the UDP coupling into a TBS file. This search has a very ambitious single
region strategy with over 150 orthogonal signal regions been in various kinematics
variables. And on the left here you can see the yields in just 43 of these signal
regions. And unfortunately, the data agrees pretty well with the background.
And so no significant deviation we've seen from the standard model. So they set
limits on all these various models and above you can see the results for the two
rpv models. And you can see that Gleaner masses can be fitted up to 2.1 TV for the
five party display on the left, and 1.7 TV for the free market decay on the right.
Okay, next we have an atlas search in a very similar final state. The search
requires two or three same side leptons plus jets, but the similar strategy is
much simpler. They defined five overlapping signal regions which they fit
independently. And among these is a dedicated rpv signal region, which
requires exactly two Samsung leptons, at least six jets and an effective mass of
2.6. TV for the effective mass is defined to be the scalar PT sum of all the leptons
jets met in the event. And this region is defined pretty inclusively allowing it to
be sensitive to many rpp scenarios. Fortunately, again knows nothing in excess
was seen. So they said exclusions, and they have an RP v model that's similar to
the CMS one with the Galeano decaying to a TBS and TBD final state. But instead of
having a three body decay, they assume as intermediate stop is on shell. So they do
a 2d mass can between the stopping masses and gluto masses can be excluded up to
1.6. tv in this model.
Next we have an atlas search targeting the production of gluey nose and a variety of
pretty concerning and violating models, all of which have large jet multiplicities
in real met and final state and The search targets the same rpv model as the Atlas
Samsung search, you can see the Fineman diagram again on the right. And this model
can have real met if the topic is the pinnacle to a hydronic town and atrium.
This search performs three separate multiband fits requiring at least eight,
nine or 10 jets with further bidding and the number of B jets and the sum of the
masses of the larger radius jets in the event. Again, no significant excess was
seen in Ford this rpv scenario, they can exclude the masses up to 1.5 TV and these
contours can be compared with those from the Atlas same time search Next we have
another Atlas search this time for bsm phenomenon and events with large Abuja
multiple cities, no leptons and low mat and this is the first Aleksey search in
this final state. And this search has a couple of benchmark IPv models, both
involving stop pair production, but with different available decay paths So, on the
left, you have this simpler model where the stock decays to a bottom insured, you
know, and 100%. And on the right you have this other more complicated model where
you have zero lsps. And so you have a 5050 split in between stop to bottom charge,
you know, and stop to top, you truly know. In either case, the junos neutrinos decay
via the UDT rpv term. This search simultaneously fits eight orthogonal
signal regions, which are been in the number of jets and the number of digits.
And you can see the yields in these eight signal regions on the left. And on the x
axis, you can see the jet multiplicity requirements for each of these bins. And
again, unfortunately, the data agrees pretty well with the expected background.
So since no access policy limits are placed on these two models on the left for
the simple model, and on the right for this model with things, you know, lsps and
you can see on the right there's this diagonal across which the stop to talk to
Kay turns on Once it becomes kinematically allowed and then these two models start
masters can be excluded up to 950 gV. Next we have the first and only electroweak
result this is an atlas search for trial upon residences from for Gino and
neutralino production. This search was inspired by the B minus l MSM, where a u
one v minus L a local gauge symmetry is added, but then spontaneously broken
resulting in our parody and local number violation. And in this model, the Reno
charge ginoza neutrinos are possible species. And when they are they decay
promptly to a standard model bows on an electron or a neutrino, you can see the
Fineman diagrams for these on the right. And the branching ratios to the different
leptons flavors are related to the neutrino hierarchy, which is pretty
interesting. So this search targets both see we know c one c one and C one one
production and they require at least one charging to decay via z two, three level
In this provides a trial upon resonance the reconstructs the tribunal mass. But
the analysis places no constraints on the decay of the other we know they attempt to
reconstruct the second Wiener decay as much as possible. And the number of
leptons reconstructed bosons in the final state defines three separate signal
regions. And on the right here you can see the MTL distribution in one of these
signal regions. And you see the signal has nice peaks at the charging the masses.
Unfortunately, again, I know significant access to the scene, so they set limits by
simultaneously fitting the MTL distributions in these three signal
regions. They then scan over the vino decay branching ratios to the different
bosons and leptons Raiders and for each sample point in this left hand branching
ratio space limits are set on the window mass as a function of the branching
fraction to see as an example of one of these contours on the right under the
hypothesis that the the you know decays are left on uniform versal As you can see,
for this assumption, we know masses can be excluded up to 950 gV for 100%, branching
fractions disease.
Moving on to the Long live searches. The first is an atlas search targeting stop
lsps that decay via the term to a muon in a downer, strange cork. And due to the
smallness of this lambda prime coupling, the stop hydrolyzes and has a displaced a
camera detector. So the signature for this search involves neurons with large impact
parameters and displays vertices with transverse displacements between four and
300 millimeters. This is before the silicon microchip tracker of Atlas. And to
help managers to turn the model background this search vetoes any displays vertices
that have positions consistent with the detector, either the active material or
the supports and services. So there's really cool plot in the top right, you can
see the positions of all these displaced vertices that fail this this material veto
and you can see in the middle of the IV The three pixel layers and then on the
outside you can see some support structures. Unfortunately, no events were
seen above the expected background. And so they set limits in the stock mass versus
lifetime plane, and stock masses can be excluded up to 1.7. tv, and these lifetime
exclusions span four orders of magnitude. Okay, next we have a CMS search and
targets many bsm models with longer particles decaying to displace jets. And
among these are a few rpv models. The first is a stop model where the stock
decays to a laptop and a downtime cork via the L Qd coupling. They also have the
familiar Galeano to TBS model, which decays via UDP coupling with the Gleaners
are long lived and stops rock shell. And they even have a dynamical rpv model where
the stop decays to two down quarks. So this a synchronous analysis involves a
digest system that's matched to a displace vertex With transverse displacements
between our up to about 55 centimeters, this is before the outer barrel of the
silicon strip tracker. And this search also has a material detail which you can
see on the left you can see the beam pipe in the middle, the three pixel layers and
then some support structures along the outside. The search expected about one
event and saw exactly one with a displays very text that was about 26 centimeters
out in the transverse plane, which ends up being pretty close to a silicon strip
layer. So this was likely a standard model particle interacting with the detector.
And in the middle here you can see the exclusion for the stock model. You can see
the stock masses are excluded up to about 1.7 TV. CMS also developed a deep neural
network for tagging jets from long with particle decays, and they train this Tiger
on a split Cz model with our period of conservation. So this targeted the
production of longer gloominess With the GUI knows the K to two courts and the
neutralino. Then to evaluate this tiger, they calculated the expected exclusions
for the split Susy model using the tiger. And then they compare this with a more
conventional analysis, a few minutes of the more conventional analysis that was an
inclusive search and final states with jets. And on this top row, you can see
this comparison on the left for an uncompressed spectrum and on the right for
a compressed spectrum. And you can see once you get a lot of times above about a
millimeter, this Tiger can really help. Then to test the generalizability of this
tiger, they evaluate its performance on GM SP and rpv models. You see the results of
this on this bottom row on the left for short lifetime and on the right for a long
lifetime models. And you can see both of these, these are ROC curves to show the
mistake rate versus the tagging efficiency. And you can see this pretty
similar performance across the models to this this Tiger seems like a generalized
as well. Okay, so I've shown many exclusion contours for various simplified
models. So on this slide I've organized all of them here on the right by the rpp
coupling from the models box in red, were targeted by prompts searches, in the ones
box in blue were targeted along with searches. So these simplified models
assume some LSP. And some will assume the LSP as well. And they also assume some
production mode. And then they turn on just a single rpp coupling at a time for
the bomb searches, they assume that the coupling whatever it is, is large enough
for properties, then they set limits on the production cross section versus the
LSP mass, or they perform a 2d mask and well the longest search is to see what the
coupling is small enough for displaced decay. And then they set limits on the LSP
mass versus its lifetime. So how do these kinds of exclusions translate to limits on
the coupling strings themselves?
So for the longest searches, you can generally convert these lifetime limits
into coupling limits via an equation equations can depend on other parameters,
including the masses of any virtual particles indicate or the mixing of the
particles. But for the problem searches, you really need reinterpretations using
rpv signals with variable variable couplings ranks. Plus you have to add
additional systematics for display signals since these analyses were were designed
for prom signals and analysis targeting are pretty concerning Susie or other bsm
physics may be sensitive to wrap up models, so we should reinterpret these as
well. So Atlas did exactly this a couple of years ago. They reinterpreted prompt
Suzy and exotic searches, setting limits on rpv coupling strengths in multiple
models. Among these are is a stop model with a nonzero UDT coupling. And so you
can see the results for the stop model on the right. And on the bottom you can see
the relevant Fineman diagrams as you turn on the coupling, and says the same all
from the introduction. So you can see just with these prompts searches are pretty
good. coverage across this full range of coupling with a gap right where you'd kind
of expect along with particle search to really help. And speaking of
reinterpretations, both CMS and Atlas have taken steps to help facilitate, help
facilitate them. CMS has published simplified likelihoods for their multi bit
analyses. Analysis started publishing full likelihoods using pi h f. So summarize, I
presented recent rpv Suzy results from Atlas and CMS targeting both short and
long lived LSP decays. This spanned a variety of production modes mass spectrum
and a lot of couplings resulting in a diverse set of final states. I showed
explicit interpretations for the simplified models. But the sensitivity of
these searches to new physics extends beyond the simplified models and even
beyond Susy an existing analyses targeting Susie or otherwise are sensitive rpv
Susie, so we can really benefit from more RPG interpretations.
Thank you and take questions. From the audience so I see that Gordon has a
question so you can unmute whenever you're ready.
I don't think we can hear you.
Cats. Can you hear me now?
Yes, I can.
Okay, so, the question I have in particular, is actually if we got back to
the slides Aren't the rpp machine learning part? I was wondering whether we got the
slide. So it's wondering if you've seen the third neural network, we're able to
learn anything about the lifetimes at all.
So the lifetimes are actually provided as an input for this tiger. So they can do
hypothesis testing across a range of lifetimes with the single tiger. So it's
an input for this.
Oh, I see. So, a lifetime, I guess I imagine that when you're doing your neural
network training, you were not using a lifetime as input. I guess I missed that.
I know I didn't mention it. I have some more information in the backup on this.
But yeah, they use the they use the lifetime as an input to do various
hypothesis testing and then they train the tiger over a wide range of mass spectra
and lifetimes.
It's okay, thank you. Oh, and can looks like Daniel also has a question.
Yeah, I had a question on the same slide actually. So, you know, what, what are the
inputs that go into training this deep neural network?
Yes, I have a slide that's kind of busy back up here, which lists all of them. So,
they have charged a neutral Particle Flow of candidates, secondary vertices, some
global jet features and then the lifetime as an external parameter, and the number
of these Particle Flow candidates and the vertices and secondary vertices can vary.
And so they can zero pad if they need to.
Okay, um, yeah, I mean, the reason I ask is this, this really no model that you
train on has these are hadron objects, right? They can be can pick up some
electric charge, and it has color charge. Well, I think these gms B models don't
have that right. The longest particle is neutral. Yes. So It's sort of surprising
that it works for both. But is there some way to get rid of that as an input? So you
don't have trained on that necessarily?
Um, I'm not sure. Maybe if one of the people developing this happened to be in
the session they can answer. But yeah, also these models have very different on
the number of like UDS versus glue glue on vs. B and C. Cork jets varies a lot too.
And it does pretty well across this very object composition as well.
Great, thanks.
All right. Thank you so much, and I think we need to move on to the next talk.