Welcome back from the break.
And we are now going to start the second session of the day.
Thank you and now this recording is in progress so the second session of the day where we have four different talks about some new LP search results from the Elysee the central Texas of the Elysee, and I'm going to stop sharing here.
Yes, I am looking to share.
Okay, so do you see my slides, fantastic yes please go ahead.
Okay. Excellent. So good afternoon everyone, to talk about the work that has been ongoing in the RTA project and then he be about the reconstruction and physical opportunities to when we recommend particles actually downstream of the lead magnets.
So, firstly, a quick reminder, this is yellow should be detected and run free it looks like this particular geometry and the intersection point on the left.
In terms of tracking how does it exactly translates well, we have free tracking systems. We got diverted indicator is the closest to the AP, then the utility that is just before the magnet and starts to actually estimate the momentum.
And finally, after the magnetic we've got a sci fi tracker. I did not hear talk about the Nunes or a Gallic shall they have more of a public identification mission that these are the three so detectors we're thinking of them are tracking system.
And depending on the subsystems are used initially to reconcile to track your track and have many types and the three types were interested in or long downstream and T tracks were long trek has some hits in at least two below in the sci fi and possibly
the UK and does retract is only UT and so fine so typically okay short or London at frys etc below. And finally, there are the sea tracks are all these high fights and no point before the magnet.
And well just as reference key shorts in HEB so left arm, roughly, 10 to the minus 10 second when they come from DDKU reconstruct them typically as 33% log log in 66% down down when you ignore other topology so that gives you kind of an idea of how you
fly in bed the decks are in current financial modes, and the current status if we have to summarize everything on the table, is that well your long tracks your bread and butter in HEB so in the two levels of trigger I just wanna childhood so you have
access to long track so you trigger on them and you can live them down tracks are not to the label and Chelsea one and the other they bought a shield, and that is which means that you can perfectly do physics on them, but you will have less available
statistics because you need something else in your event to trigger just one.
And finally, the T tracks that corresponds is very large reached between 2.5 meters and eight meters.
You've got nothing. There is no and that is a piece in the, in the usual way of manipulate there should be there is none that is possible and we never see them in the trigger.
So what can we do. Well firstly we can try to add tracks to analysis. And because as I said and tells the flight distance you suddenly prob region so you have 5.5 meters, added to your reach.
However, because you have on the hits dancer the magnets and you're the gatekeeper red X, if you are outside the details probably inside the magnets is absolutely not trivial to us and there's a lot of efforts to improve that situation so you have a poor
moment of resolution. It is very difficult, very taxing, and also you get these very large ghost rates and the lower efficiencies, especially because the algorithms tend to be tuned for particles coming from a stream.
So for example defendable reconstruction of tea tracks the hybrid seating kind of has a purpose is that your political comes from the PV.
The first step of adding two tracks and that is is actually proving that we could reconstruct signal form already available data.
So we turned to run so.
And these are all plots coming from paper that is being written this day is being reviewed renounce It is our preliminary plots. And the goal of this is this is reconstructed under the trip so lambda and B to drift citation modes with the love dedication
ultra conservative vt tracks and the interest of these moves is that because we have a gypsy actually this bypasses HR to want to jump into issues you're going to trigger very high efficiency with the flip side, so you're just looking at a very nice your
mood and see if you can actually work on some stuff. And because you have these vertices that are actually learned these tips I was masses known etc. You see that the mountain resolution before and after playing the constraint fit which is a dictator
fits up in orange there you go from 25 to 30% moment of resolution on the proven momentum to 10%. So really pretty much a good point for this is all on simulation and and simulation you also have width of the nanda and the longer be distributions that
are rather nice, I mean the way for that under the distribution is of course quite large. But still, for example, when you have a DK including a PI zero this is fine as a kind of things that you have in there.
And so this is all simulation ensures that actually we can expect something that is compatible with corporations and these waves are actually quite interesting in the search for on the particles because well, the narrow your peaks of this lead the more
precise associate integrating the less background, and other result and data.
And now the result of data. So same remark This is preliminary this part of a paper is being reviewed the fit today now finds 10s of thousands of other variants and around 6000 monthly burdens.
In the run to indirect data in six indispensable. So, and the width of the divisions is compatible with that. What we found a Monte Carlo.
So we actually can see in the data and reconstruct k shorts and numbers using t tracks when they decay inside the magnets. And we still have some possible improvement that we've been working on which, such as the use of KD on the preventative balancing,
And the study of the be mode finds roughly 10 to 20,000 Devens something interesting here is that this study actually started only we've learned to be to longer trips I, and these be moody servant and that you can see it as a background of the mood and
so we we said, we said to just show it was possible to use to use numbers as TT, and actually showed that we could not even ignore all that city because this is good enough the geography key background.
So, the global status here is that we are indeed able to use the tracks to reconstruct everything 102 K's email HTTP and that's open some nice facilities fine should be, you know, these particles.
Now the second thing that has been the focus of the methods, is to add the guarantee tracks which helps you want. So flt one is the first step of the trigger it reduces the raid from 30 megahertz one megahertz.
So huge sensical price when you cannot trigger on a type of track. It depends on the mood though, because for example, when you have a mood Weaver deco paint chip so for example you don't pay much, but if you have k shorts pi pi, for example, well your
pie in your case, it takes a lot of energy and if it's downstream you have less chances to actually trigger on the resulting bones.
So, right now, when you look at the current liminal reconstruction and Chelsea one it relies on the old tracks. And these are reconstructed by taking of you know track and adding up hits and then sci fi hits, which means that you have new byproduct that
you can use. However, when you look at energy to attach it to the way we reconstruct stuff.
There is a second strategy to reconstruct a long track security which is new, make video segments and you make sci fi segments, And you match the 232 magnets, and possibly had adversity hits.
And that's if we could improve on that in a chapter one, we would have another way to have long tracks, which also produces as a byproduct this teacher decide Phi Sigma, which is at the track already in which is also the source of our tracks because then
you can match that to UT hits.
And so that's the whole, the whole point is, how are we able to run that in a chance one.
And so when we have a look at it the tracker construction. It relies an algorithm that's called hybrid seeding in Chelsea to give you here the references of the paper on this of this requisition encourage them and talk in connecting the dots that was
it as well. And last year we actually posted the algorithm to GPU, we reduce the efficiency compared to each other too but then how to speed that is compatible, which has a lot of variations in actually this is quite a recent development and there is
a plethora of the meeting on evidence detectors and a talker connecting the dots, which I give you here. And when you have a look at the efficiency we compare all matching little cell phone matching on transformation, with the nominal strategy in red,
and we find the efficiencies are compatible and a bit better on global mental because we have new cuts and the fruit boots in orange is no no, and in the blue is the attitude mode so you see we're a bit slower than we know, however compatible.
And the point of that is that if we can actually reconstruct long tracks using this strategy, certainly we it opens the door to working on the downstream reconstruction NHL to one, and on designing trigger lines as well, and then suddenly you go from
triggering and tracks that only the day before one meters, one meter, two tracks to anything that the case in the first eight meters, naturally, there are other problems with those rates and background rates but at the very least it's possible to try
to trigger on that.
So, if you have a look at the baton current work you know you're part of this things we come back to the stable, and well the the paper being written shows that it's possible to run to to analyze the tracks.
And because it is actually so people are already working on writing trigger lights down the showstopper clearly here on the tracks in the chocolate Oh, and what I just showed which isn't a Chelsea one the reconstruction is no possible in terms of speed
and efficiency, to have downstream track anti tracks, and then we need to actually commission it's, it's not a it's not the baseline for now. And to write trigger lines on the speakers, the speaker types.
So that was the reconstruction part however what about the physics case itself. Yeah.
Actually, I wanted to mention is basically cases is a bitter exotic given for LP such as, which is that on a CD is a source of London hormones that are produced in charmed UTM travel indicates which means they are polarized.
And these volumes when you're under the case in the magnets process inside of the field and the magnets, which means that you can actually measure the dipole over anything dipole moments along the barium.
And there's been a proposal to do just the ass that we need to use he tracks for for construction and sensitivity there was a quote in that paper is actually increasing by two orders of magnitude, the Monday dm precision which would be a social proof
of that situation, and also performing your CPD tests with the key factor of it on the bar in.
for by Mike Williams, which talks about the paper which also states that the sensitivity is not limited by the signal rates of backgrounds but instead by Latin acceptance.
And so, including downstream tracks and T tracks in he recently with actually improve that situation.
And what I shoot here is the activity of the moon Daughters of the model when you have a hidden Higgs going to new me. So the two HK and he knew as a function of the HMS and lifetime.
In what you see on the left is long, long, so at low lifetimes you are nearly on the long long.
This is the current life should be threaded tree.
You could extend this strategy with downstream tracks where new you are visited in downtown topology and you have a better handle on larger lifetimes.
And, however you are to deal with the backgrounds, which is not something that I address in this talk.
And then the tea tracks are not yet available at all but suddenly proved yet another region of the parent of space it could be very interesting of 2000 because it comes into the systematic program including Dan NT tracks could actually unlock these two
regions of the parameter space I show here, and prove these large regions that have not gifted proved that he me.
And so as a conclusion.
Okay. I just saw the painting on my on the slides but only on now.
As a conclusion that for software trigger allegedly they actually is certainly something that has been challenging, but it's also offers a lot of flexibility that allows us to look for new opportunities.
And so this is work I'm going to include downstream tracking the first level trigger. So certainly you could increase your level 36 for not only sentimental moods, but also a lot of BS.
So you go from the Harbinger one meter to hold me to have 2.5 meters, which is already pretty nice.
And then there is this article being written to showcase a possibility. Do you see tracks in emulators and actually the work on downstream could also be recycled to try to trigger on two tracks.
and suddenly use this at PD goes to eight meters, and you are you access to completely new region for participates.
And there is a takeaway as like some swear that's connecting the dots conference this week actually about exactly that.
And there are quite a few articles are being written, not only about that but also to evaluate decrease reach on the LMT searches and it should be using these tracks.
Thank you.
Thanks very much, guys, this is great,
really exciting developments for LA cb. Oh yeah, the time thing, there was some sort of delay apparently in the zoom and it was being typed in, but it didn't show up on the screen until it was too late doesn't matter because we're nice thing on time.
Thanks for staying on time so questions for Lewis anybody.
So we got yeah okay Michael Go ahead, Michael. Yeah. Just a quick question. I mean, obviously backgrounds would be quite important to how progressing.
Background studies progressing with this.
Right didn't find the unmute button.
The Surena the first article that is being written is very very does not take into account backgrounds, it's more topological information, and we got the second, we want to write more conclusive.
Well no quizzes article, maybe including backgrounds in the next few months. So, I'd rather not give a timescale but it's certainly something that we are looking into.
because as you see on the, on the very on the quite keen modes, London be if I come back to London to London to love that side. It's a rather clean moody Nice to be here you can clearly see that you got some background there, because then divert axing
into the loo actually along the bay is difficult.
Okay, thank you.
So yeah, that's that clearly will be a problem but I also suspect it's going to be removed dependence.
Considering how actually all under the keys, very clean.
Right anybody else questions for Lewis.
I think this is really nice I love finding little areas that we're not doing so perfect that and then kind of improving them and added them to the analysis this concept of adding to teach backs looks like a really good thing.
So, we say look forward to following along as it develops. So, if there are no further questions for Lewis, remember that if you do have a question that comes up please feel free to put it into matter most.
Lewis if you're over there somebody can probably ask you a question there.
Okay, I'll turn the channel.
Alright, thanks a lot.
Now we are going to switch over to Atlas, we have Christian Christian Are you ready.
Yes. Can you.
Yes, we see you and hear you.
Now we see your slide, and hopefully now we go full screen, you're ready to go. We'll give you just a verbal up there, little kind of heads up when you've got about five minutes left.
Alright, sounds good. Thank you.
Okay, yeah, I'm presenting today, there's such magnitude leptons from Atlas So, of course, it's not going to be very detailed because of the 15 minutes but I have put the paper draft in here and it's already submitted to PL and available here already
passed up as review.
I probably don't have to motivate so much but I will do it anyway little bit.
And then we'll spend some time explaining our signal model because this is quite special. For this analysis.
So, I mean, as you all know we have, like, a few observations, can be explained by the Standard Model, such as an adrenal installations observed metadata.
And one possible solution to this would be to add three right and my entrepreneurs to the standard model a garage Ian, they would then form the so called neutrino minimum standard model.
So you don't necessarily need three. Two would actually be enough to like be part of Western way to agree the with the observed mass hierarchies, and with the opposite of metadata.
you can Prometheus in a different way to give a document or candidate but we are not sensitive to this and this, the search.
When, usually we partner twice the HTML with a coupling consonant and the mass, and of course this has been done before by various experiments. So here, for example, looking at the moon coupling dominance versus actual mass playing.
So we have like quite a few exclusive limits already this was the starting point of our analysis and 2019 were also the previous displace h&r reserved from Atlas was published, or the exposure limits from this one here.
And the search I'm showing you today, basically looks between three and 20 TGV of the HTML and promise rises the signal Monte Carlo samples between one and 200 millimeter of proper lifetime.
And as you can see the proper lifetime it's like inversely proportional to the coupling constant. So this means we get a grid in this plane to proper basically follows you know.
So our signature is basically a purely electronic so we have W, Bo zone decaying in this puppy called prompt left on this alpha we are our first celeb on flavor.
And then we have the long lift heavy metal electron interacting with the standard modern neutrinos.
And then, forming a displaced vertex here with two opposite sign ups on spiders of W. We can also have an offset here within the left hand fingers will be the same.
This decay can be left and number conserving for the left and numbers of neutrinos that we can have the same leptin number violating.
And then basically we allow both cases, we probe for my ohana he knows what would have basically both of these tks involved, but we parameters our model also in a way that we look at.
Direct he was only.
So this means that our signals basically this prompt left on the displaced vertex opposite same leptons.
And then we have another variable as our main discriminating variable this reconstructed having upper left on Mars. So even though we don't know much about the neutrino, we can use information we have about the who goes on to solve this equation, and
and to reconstruct the W at the ancient Emma's.
And here on the lower right you see the ancient enemas, and our single region on the left, between zero and 20 GV.
And there you can also see three different agent El Monte Carlo samples with the truth masters of 510 and 15 gV.
And as you can see they are nicely teaching in this reconstructed class. We also have a control region here between 20 and 50 GV, which we mainly use to constrain our back on as soon as we talk about this in a minute.
So then we define our analysis channel as follows using this alpha beta gamma rotation from our signature signature.
And then dependent on the model we want to probe. We do different channel combinations. So for example this standards interpretation, which are shown in the first slide where we just allow one electron with this thing of flavor mixing, we can combine
the new entrepreneurs, or we combine the electron channels to to basically get the get the results there.
But as you have seen already yesterday, and the summary talks.
This is not agreeing this me and only an electron only mixing is not agreeing with the, with the data from the constellations. So, to probe those as well.
We actually assumed to have so called closet direct pair of Eminem's leptons, which means that they are the masters, almost the same so they did not degenerate and therefore, almost act as a single direct particle.
But this way we have to agent outs. And we can prioritize the mixing ratios in a way to basically prove this to benchmark points is normal hierarchy benchmark point here are the inverted hierarchy benchmark frontier.
And in order to do this, we then combine all the channels to probe for the different models.
Then speaking a bit of our data flow.
So, we can of course use standard from leptin triggers, to, to, to trigger our data.
And then an atlas one to the prompt reconstruction only contains standard tracking which specific prompt tracking that we need the support large radius tracking which was already mentioned by lower yesterday and I talk.
And the difference between standard tracking a lot Redis tracking is that we have much wider impact parameters. As you can see, for example the D zero sec factor of.
to have 30 bigger here.
And this was in one too computationally quite expensive. So, um, what we had to do was actually we had to apply some filters, and then have like less data, basically to do the displays for construction on because of the computation and so we end up with
approximately 10% of the data with special filters to get the events which are interesting for us. And then we do the large radius tracking and second robotics finding to continue on and
then we also modified the second overtaxing so what we're interested in are these two leptin opposite scientists best practices. So there's a standard algorithm up in Atlas, which we took, and basically modified.
And interestingly, so what we did is basically allow only leptin tracks for this leptin seeding stuff.
And then of course a few more steps in the middle but in the very end, we have a trek attachment step where we don't allow any trek to be attached. And this way we could release some of the parameters.
But having this track attachment step here with any trick, we were actually able to increase the selection efficiency quite a bit dependent on the channel master lifetime, by keeping the background, at a similar level.
You can see how overtaxing efficiency looks like for this customer sing.
And as you can see where like,
mostly efficient here between the space vertex ready between like 10 and like eight millimeters.
Okay, speaking about background. So we basically classify our background in two sources so backgrounds, we can reduce using specific selection criteria and backgrounds, we consider irreducible and then have to estimate.
So the first one, contain basically the case from material interactions. The case from meta stable particles such as we had run so strange baryons cosmic ones.
And that's to leptin leptin the case where one of the leptons from this SDK is actually part of the random me.
Crossing laptop and then forms at a specified text and backgrounds, we can't we can't reduce, what we call random track crossing backgrounds.
This happens when two tracks randomly cross and formula space vertex, and we use a data driven approach to estimate those.
And the nice feature about them is that if you have infinite statistics, then you should have basically the same number of opposite sign and the same number of Samson vertices, created by this random trek crossing, so this this text we can use for for
estimating.
Okay, here you can see our analysis selection we basically use to get rid of the left part of the backgrounds here.
So don't read this now. Just put it here for to be to be complete.
But
in general, what we want to look at is if this hypothesis of opposite side equals same same is true for our samples.
We do this by looking at our validation region. And so the special thing about over the Asian region is that we explicitly veto the laptop. So this means that was significant be in here but we can look at opposite sign and same sentence best practices
and data.
And if we do this year for example for electron we will displace vertices and we look at the displaced vertex master solution, then you can see that opposite silence same sentence please vertices are going quite well.
This is not the case for all of the channels so there's a bit of a difference but we will have a systematic to take this into account.
Now, we can't just use same sign, this place vertices to estimate or background because we have low statistics so we were searching for a method to increase the statistics.
So what we do here is then look at events where we have the electron and same scientists plasma disease. And then we look at events from the validation region where we have no problem term but is opposite scientists best practices.
And then we shuffle these events around to create our data driven random fact crossing background estimate with increased statistics, Christian just you over five minutes, I think you're okay.
All right, thank you.
Okay and then here you see the edge monster solution again for, like, also two more channels, and this pinkish shaded areas and basically your background so keep talking about systematics.
So we have quite a few system medicinal signal.
I just want to mention, the biggest funders displaced vertex systematic.
Here, we, we basically found that the efficiency of displaced of the displaced vertex reconstruction can vary between data and simulation, and to take us into account we performed a study on k shorts to pound high on that is vertices to estimate these
differences.
And then for the background we have to systematics the displays without tech systematic and the front left and systematic whether this festival tech systematic basically takes into account the disagreement between same set of opposite scientists based
vertices, and the prompt leptons a semantic takes into account the fact that we just have a finite number of competence.
Right then, we can basically go to the statistical analysis. So, this we now, just look at one specific mass lifetime point of course we do this in the end for all of them.
And I've picked one of the complicated models, this class iraq pair of hn else with the inverted hierarchy mixing in the morning, where we combine those channels.
So the combination then looks like this. Here we have all the six channels we're combining and the signal region and control regions as one.
And what we do them so basically you see the background again, and the signal in red.
And the data in black, and what we do them as we do a combined signal region plus control region fit, where we have free floating normalization factors on the background for each of the channels so this way the control region can actually constrain the
background and scale it. And we have a shared signal strength parameter. On the signal.
And then the post fitness program looks like this.
And now we calculate for all of them as lifetime points we calculate the limit on the signal strength, using the CSS method, and to do experiments because with little statistics.
And we do this for almost lifetime points and all models, basically.
And then I can show you our results.
So for the model I've just shown you I mean Okay, as you probably have expected we haven't observed it knows but we were able to set these limits.
Here in the, in the coupling console versus mass plane. And as you can see the observed exclusion limit was very well with expected one.
And then for the first time we have this to qdh so the positive role models in normal and inverted hierarchy, and z on the bottom you see the summary of the observed confidence limits for all four of the models where we assume the eighth notes to be in
my hand particle. And the same.
See here, where the article, and the strongest limits we observed for the the multiplayer mixing the inverted hierarchy to stay tuned, we're already working on the next version of the analysis.
And we're very excited to proceed and see what's going to be the outcome.
Thanks for the questions.
If we.
Alright, thanks very much for that Christian wonderful talk really fantastic result, we got a couple of questions already so Giovanna Go ahead.
Hi, thank you very much for the talk, I just wanted to ask you about this feature in your execution Bloodsport by gv. I still don't quite understand what is this election that shows this bump in the envy, or like Valley.
Yeah, this is this lecture, basically. So this bump is caused by this heavy flavor DKV joke. So what we do here in this place on the right is we look at opposite sentence same sentence this word is again from the validation region, and we have the displacement
vertex mass here versus the this case but it's when we look at the difference between them.
And the difference basically comes from the long lift center model particles, and we use this red cuts to cut them off basically to ensure that our teams and especially our districts are, are the same in the end.
And as you can see for the Mian Mian especially since we haven't been able to do this like more elaborate the market because we have a lot of stuff here.
So, but we're also not super sensitive to your new TVs any way so the most important show for us was the ones where we have electron Leon, what is select he knew and we were we were the most sensitive.
But yeah, this is causing this dip.
And in the previous analysis from Atlas, we don't have this tip, because they are they just put in like a shop for ggV capital P.
Right so okay so this allows you to have sensitivity below five gv but still uses. Okay. Okay. And also I wanted to ask about because you mentioned also this material Vito that I think the previous at least displace like multi drug resistant Atlas do
have it.
But why do you mention only for the E case, because we only saw the impact of the material to actions in our, in our validation standards we only saw this for electronic kind of space purposes, we are not that impacted by this before, when we want to
on board. So this was all finding, therefore we can apply it, because it didn't make a run affected basically by looking to do.
Okay, but it is this because of this the map is for the inner trucker, and you don't have this nuance further away. Is that the case.
We're not necessarily but I mean we have.
So the background looks a bit different looking in electronic tennis best practices so there. It's just more likely to see this material directions that was offending was.
In any case, I mean you don't see. Okay. Okay, thanks. I like your slice. Thank you.
Thanks.
Thanks a lot Giovanna Larry, go ahead.
Awesome. Thanks so much. Yeah, Thanks for the really great talk was fantastic.
of questions like 10.
You were talking about this this control region, where you're vetoing on a prompt left on to kill the signal.
But I'm just wondering, so so that that makes sense for this w production. But, do you have any worries of signal contamination safe from zero new new production of this HTML.
Yeah, if I remember correctly, we looked into this and we didn't saw like much of this so I don't recall no numbers or plots and talking heads but I remember that there was a discussion.
We checked it and we haven't been affected. Yeah, I can confirm every Christian we look order, a couple events, a few events in the validation regenerate otherwise had hundreds.
So it was.
It's a very good point yeah we looked into this.
Okay, okay, I say, Great, thank you. Thanks, Mark.
All right, anybody else. questions for Christian.
Sounds like a resounding great talk so thanks again Christian for a great talk.
And again, the continuous continual reminder for the questions and comments can go on to discussion could go on to the matter most channel please head over there to see who might be around asking questions.
Next we're going to transition to CMS dime you on displace vertex so this is going to be Mohammed Mohammed or euro.
Do you hear me. Yes, hear you and see you. All right, great. Let me share my slides.
Okay, can you see. Yes.
Are you going to do like a full screen. Thank you.
There we are. Perfect. Okay, we'll give you a verbal heads up when you've got a few minutes left. Thanks.
Okay, so my name is unser and I'd be presenting just based on search on behalf of seniors. So before I go into the slides, let me, let me remind you about that we've been seeing again and again to this workshop and this was also shown by James, in one
form in his introductory talk. So, this is regarding the space that we're looking at. We're looking at the region static code analysis, and it sounds are.
double check that it's going forward, back, does he know I still see I know I see the second slide. Okay, okay, I was in the day you were on the first one.
Okay, sorry I'm ignore me Please go ahead. My apologies. No. So, what I wanted to say was that in this nice book where we see the coverage as a function of lag time, we see that most analyses are focused on the range of Lifetime's on the skin of a millimeter
or so, and then we have our detectors which go up to a few meters, and then we have stepping back because after that. So there's this huge gap, if you may in between these two regions and the search I'm going to present today, sort of, tries to address
that, that issue in that we're looking for the space diamonds, coming from common critics, but we're going to do that in a really wide range of displacement.
So, no man's land.
Alright, so, just as we all know that LPs could could manifest by the case to particular set of articles. For example, in this case, this place that nuance and depending on the model, they can they can have a significantly large or small displacement
engine on the model. So what I am presenting today is, is a new generic, and vertically modern independent, CMS search for an obese dedicated to displace that nuance and this which has been has been reviewed by CMS, It has been submitted to GM for publication.
So very quickly. I'm sure you're all aware of this but just just to recap, and to provide some backdrop for the analysis.
As I said, the analysis is relatively more than independent but just to interpret we interpret the results in common use benchmark models. The first one is this inability takes more in that you have a doc sector, it's been that that makes us with the
Doc sector, it's been that that makes us with assembling speed, and with with a couple in Kappa, and then this syndicate to do. lts, which in this case our photons, and those dark photons can can indicate to diamonds in this case.
And this is controlled by, this is this escaped raised by a kinetic mixing epsilon.
The other model that will consider themselves for this analysis is a simplified the SMX model in which we have heavy scalar expose on the decays introduce killer bees, and those killer bees can indicate to do nuance each of them can be candid with us
giving us a displaced signal.
So, I mean, as I said, the analysis interprets there's in terms of these two models by three the petition is of course possible and we provide the routine for interpretation, you can cut it and that.
Okay. So just to give you an example, this is, this is an event of the space that needs to be noticed in that these be constructed in the same as experiment.
It was constructed within the 2018 data decade of the experiments are as you can see, the blocks that you see in red. These are the chambers. And so we're constructing young new ones out of the hits and the segments and the chambers and then they form,
combined with x which is rather displaced. So as I said, it covers the search commerce luxury disbursements. So I'm going to talk about the different categories in a bit but essentially what I wanted to show you was living proof that will actually cover
allergens of displacement and, did you see the combined with x here is actually because outside of silicon practice, which is pretty nice.
Okay, so coming to the search itself, the search was performed using 92% of data with connected to SMS, this was this was during 2016 and 2018 of the data needed aching.
And as I said, the the piece that came to this place diamonds in the search can or they can decay within or beyond the CMS simple tracker.
So, and it just to just to introduce you to how we cover it such a luxury of displacements. Let me remind you that in CMS we can have two types of reconstructing nuance, one of them we call the standalone nuance and these are the new ones that are reconstructed
One of them we call the standalone new ones. And these are the new ones that are reconstructed on the Infineon system. And then we can have cracker DMS what the MSP ons and these ones are the ones that are reconstructed in the subcontractor, as well as
the beyond system. So, based on this we can categorize our search into three categories where we have both them yawns as sta sta or then we can have the DMS DMS category.
And the third one is is the combination of the three, so you can see what these categories don't like in the cartoon schematic on the bottom left, so the diversity is in the middle, where would other fields are coming from the space where taxes as a smallest
movement and with me also reconstructed in the chambers as well as the subcontractor on the left in green, we have the standalone unit there, which not only constructed in his inner chambers and the new is showing the hybrid category.
So, what I would like to highlight here is that these three. these three different categories they have completely different apologies, they're completely different backgrounds, so it's like to eat three separate analysis and then combining them into
And as you'll see throughout the for the states that we, we do optimize the selection appointment separately, different background estimation procedures for each one, and so on. So what I saw on the bottom right, this is, this shows you what the what
the distribution of the categories is, as a function of transfers displacement. So, this is the this shows the fraction of diamonds, which poured into each category, as, as a function of two transfers displacement in a simulated simulated benchmark disseminates
sample.
And you can see that at displacements per chart, you know, let's say, 20 centimeters or so, this is dominated by the TMS TMS category as you can understand.
We have the largest budget efficiency from the record, and at large displacements, this is completely covered by SDS the year where we not have efficiency from the record, and in the, in the region in the, in the sensitivity which is provided by this
hybrid stadiums category.
Okay, as you can expect to get out such search the normal triggers, don't work very well so we have dedicated triggers that is for the search.
So the dedicated triggers that we using this start with two new ones which are reconstructed on the internal system because we want to capture all the three categories there, and we do not use any tracker information in the triggers themselves, and the
two new ones have certain, certain requirements on them which are listed here for 2016 and 2018. What 2016 trigger. What we also had a built in in the trigger was a requirement on the three dimensional angle between the two meals which one Elsa, and this
this is to basically suppress cosmetics because, as you can understand the cosmetics, have the cosmic scan appears to be on spread the really large opening angle.
So this requirement was there to to suppress cosmetics, and there was a built in requirement on the debut on mass of greater than 10 GV.
In 2018 optimizations elsewhere, as well as the resolve to do this offline have removed this requirements from the figure themselves and these are now optimized offline.
And for example, just as an example of the cell phone, this is optimized differently in the different categories, because the policies are different so this alpha is optimized differently in different categories, we're still keeping the W on contention
need requirement and others we categories but there's also the removal of this requirement from the trigger means that we can use some of the some of the events below 10 gb as our as our control room, as a control issue.
What additionally was done in 2018, was that another complimentary ticket was a trigger was added with a state different seating of that also improve the efficiency, and the triggers was studied using prospects.
So again, you're probably all familiar with such requirements but just to just for completeness, in the bottom right you can see the variables that are most important for the analysis.
And the first one is really unique to this search. So what we do is we take the, as I said, we start with sta yawns in the triggers who didn't document and as we're getting started with SDN new ones SDN guns course and then we try to associate them with
DNS new ones. So, what happens is that if we are able to associate PMS beyond with an SDN you on that SDN Jaan is removed from the collection and the TMS Mian is put in, put in its place.
So by doing that what we essentially do is we remove the backgrounds from the FDA this categories. And this also increases or enhances the resolution of the transport for the plastic as well.
For in terms of displacements, what we required is the Alex wire transfers to kill and normalized with uncertainty, which we call xy significance. And as you can expect this as this is expected to be large in signal, then the transfer effect parameter
again normalized its uncertainty for this to significance and justice and expect to be large signal.
Then what we consider is the angle between the XY and Daniel vector and this is what we call bullying at the end of the fight. And as you can expect for signal this is this is supposed to be small because we're for this analysis we're looking at just
a beast again to do he wants, so this is supposed to be smaller.
For and for backgrounds will discuss the shapes of WD different for different background sources. Then, what do we have his guts on vd better than 10 gb, and requirements on the track quality Daniel would exploit it.
And since we're testing different mass hypotheses, we have mass windows that correspond to different, and the masses. And then for STP ones we have conditions on timing, as well as the direction in which the new one was registered and 14 sp ones we have
conditions on isolation.
So, background as was already already mentioned in some of the talks before that, in this region, the equivalent ng the standard models artist. Yes Really quick yeah but five minutes just like, okay.
So, in the, in this animal. We don't really have.
We don't really have a intrinsic background in this region. So the background in the search comes from this reconstruction of the ones who owns and what can be Miss reconstructed is like if you if you have already animate, and that can be that can be
the.
I mean, that can be Miss reconstructed because of instrumentation false or so on. And this can appear to be a natural display standing on. And since the the director does not have a preferred direction, in respect to the victor.
This is symmetric in the defiance you can see the, one of the controllers and lots of top rank and other class of backgrounds that we have is coming from, no mass resonances for example chips I McCaskey indicates of the headlines, and in some of the sources
be quantum TCP like background, this is really a symmetric in delta phi, because it beats that small device you can see on the on the finger on the bottom right.
So, the background evaluation, and all the categories was by using large identify events as a proxy for credit, like backgrounds and same same events as a proxy for to see like events and then it was possible factors to transfer them to the segmentation.
So the sta sta diamond category. This, this provide sensitivity to LGBT gets beyond the record volume as you've seen.
So, for the search specifically, we developed it and bigger requirements for display standalone nuance, and that was used in the studies and cosmetics.
for this category. What I also should mention is that cosmic beyond one background for the st st a diamond category, so we do the requirements as we talked about, but we also apply certain other requirements, for example, we reject a configuration of
back to back neurons, or we require a certain number of segments to control the cosmic background.
Then the 20th easily transfer factors are made in regions by the job done by converting the SDR to the MSP on Association, and that they're also validated in certain regions, and you can see a validation in the top right of this slide.
The water buds showed the result as a spectrum of Daniel mass. So, in yellow you have the QCD predicted in green which you don't see in this in this new speakers, is, is the 21, which is predicted.
And then those are shown that is back points and, but also overlaid are the signals that are constrained by the synapses. As you can see we don't see any excess in this category for the TMS TMS Daniel category has a much better resolution resolution resolution
and also easier solution allows us to grow up displacements which are much smaller than than a few centimeters. As I said, you know, an isolation is a great handle to suppress the background in this category, also doing these the sensitivity what we're
doing in this category is split it into three subcategories based on the based on the minimum of the dz or significance of the two new ones. Again the training and into seedy transfer factors are calculated and dedicated regions and for this case, we're
chi square. And when isolation regions to study that and again no significant access was observed in this category as well. the CMS Mian category. This is it resolutions are in the other two categories, and it has the requirements which are inherited
from the other two categories as well as some requirements which are, which are which are there because it has the need to polish if it's on. So we apply some guts, which are not in the other categories for example, The the Alex why dependent number of
and angle between the LXY Victor and the beauty of the beauty of the team SP on which is in that. And again, as the other categories as factors I recreated in dedicated designed meant regions, and then are validated in in different motivations and again
we see that there's no excess of the Standard Model background.
So coming to the results, we, we, we derive 95% growth and several other limits of what the models that I discussed. So what I want to highlight here is if you look at the code on the bottom left, you can see the nice complementarity between the three
categories. The green one is the SDS here, which we needed this elements at high lifetimes. The blue one is the SDS TMS which contributes intermediate lifetimes and the red one is the DNS DNS which indicates that in a very small lifetimes.
And as you can also see that we are able to really cover a large, large base base with many orders of magnitude of displacements, and you can also see in the paper for example, the cover a lot of change of the masses and interchange of was a message for
this next one, and then two dimensional limits and quicker concurrent users or D right.
So this is my last slide, I want to give a quick comparison with those that are already around.
So, we did the research that I just presented this gives the best constraints in most of the considered masses and bad times, for example for the wx model.
As you can see in the two dots that I show at the bottom.
It gives the best constraints in a large region of this back and fill space, and other CMS analysis has better sensitivity in documentary GG in these lifetimes.
You can see the values of where each analysis is is better in terms of sensitivity in the slides are in paper for example. And then for the next model we have the best constraint call consider the masses.
So, not go to the conclusion a, as I just said but one thing that I do want to mention is that sensitivity of research is really limited by the trigger, and this you can see on the plot on the right.
And so for the next iteration of that either they were doing certain trigger improvements and trying to improve the sensitivity of the search by that.
So, thanks.
Fantastic. Fantastic really nice talk hands are great result of of Two Cities longer lifetimes getting the more coverage their questions Matt, go ahead.
I'm really nice results. Then the question I have, has to do with isolation, as you said, the trigger is the limiting factor for for the sensitivity model so you consider, there are other models in which your typical displaced vertex is going to be in
the middle of other crap.
middle of other crap. And so the question is, at least for the, the higher D zeros for the TMS TMS category, could you could you potentially relax, that going forward. Relax isolation going forward and start to probe these other models is absolutely so
Relax isolation going forward and start to probe these other models, yes absolutely so so this was probably not very clear in my talk because there was not a lot of time so isolation so let me let me try to clarify that.
So we have these three categories, which are Joe st st st DMS and give us team so the team is the US is the one that, but that's really relevant at small lifetimes.
So for the TMS TMS because that's reconstructed in the paper, we, we did apply isolation requirements for the other two, four and four for example for the STS Do you get agree we do not apply an isolation requirement, and it's exactly because of the reason
that he said. So for example, we could get, we could get be barred from from NLP and we want to prove that. And so that that's going to be highly displace.
And so if we apply an escalation we're going to get out into the second from here. So we do not apply an isolation on this SD SD again. And in addition to that, the isolation that we do apply on TMS DMS that's highly dated for for the search.
For example, just to give an example, it's not exactly the same point but the standardized solution that I used in most of the searches. That just looks at one particle and then set on the on the beauty that's around that and just consider that as considered
as considered that in isolation, but in our case, for example we have new ones or we have form your own category. In that case, the other neurons which are, which are published yesterday she was being considered that that's that doesn't go into the isolation
so we are dedicated to the done that. And then we do the parameters that go into the calculation desolation.
So it's definitely this can be doing more as you said depending on the model that we're considering it's relatively relatively modern and then in the search extremely easy to do that.
But absolutely, thanks for bringing that up.
Thanks.
Okay, great.
For the questions for answer.
Alright, sounds like a nice place to end there thanks again I'm sorry for the great talk, and again, continual reminder go to matter more most more discussion there, people might have questions if you do have a question over there and ping answer.
Yeah. All right, next up we have Neha, Neha with Atlas non pointing photons are you here.
Are you here.
I see you connected.
don't see any response yet we're a couple of minutes ahead of schedule so let's offline send a quick email to Neha, so everybody just kind of like hang out for a couple of minutes and we'll see if we can get our slides up and running.
Hi everyone. Can you hear me now.
Yes, we can hear you now. Sorry. Yeah, my computer froze so I had to restart it.
Yes. Yeah.
Great. We are here and ready to go so yeah we have.
They had to talk about displays photos. So please go ahead and we'll give you a heads up verbal heads up when you've got a few minutes left on sleep, everyone.
Today we'll be talking about search with the space put on produced in the exotic case of the standard modern Higgs boson using the ATLAS detector.
So.
So what exactly is the signal model I'm talking about.
It's shown in the apartment item here below where we have a standard model kits produced in association with a zW or the TT bar, and we basically use the leptons from the associated production to trigger our entire event.
And the interesting part here is the Higgs digging into too. Long live particle pairs. Here, it's the next to like the super symmetric particle, which is generally a neutrino, and then it's long lived so it travels a certain distance in our detector and
the keys to a photon, and stable LSD. So, the signature that you would. The final state signature that you would see in our detector is at least one displays futon, and in association with some met that arises from the stable MSP is that we have here,
also from any neutrinos and the associated production. And here the week coupling between the two supersymmetric particles, leads to the lifetime for the analysts be.
So, this result is extremely new, so it was just public I think roughly a month ago, and we are currently in preparation to submitted to the Brd journal by this Friday.
So, pretty exciting. So, let me tell you why this is interesting, and what exactly was appealing to me for my PhD.
So, firstly no evidence have been found for supersymmetry using traditional procedures. And given that many particles and standard model itself have nonzero lifetime.
It's a priority, not a given that bsm might be trumped, so there could be be some signatures that have finite lifetimes. And this particular signature is interesting because the current limits on Higgs to undetected particles, the branching ratio is around
21%, which means the signal that I'm talking about if, let's say it exists in nature and happens at like branching ratio, at around 10%, it's relatively low hanging fruit that we should be able to see using the run to data from HD.
And as I said, this is an unexplored face piece that have been few displaced photon searches done in the past, by both Atlas and CMS, but note that the target a completely different signal model, wherein they look at GMSB models were typically photons
have PT in the range of hundreds of GB and associated with very large met as well. But here we are looking at very soft photons, typically, with bt between 10 to 20 gV and the metals around hundred GB.
So the face pieces that we are proving a completely new that comes with its own set of unique challenges.
And what I also like about this analysis is that it uses Higgs boson as appropriate be some physics, and that's shown in the cartoon here. This is a cartoon from one of the symmetry magazines, I think from a few months ago, where Susie could be neatly
hiding between Higgs boson.
And this particular signal search involves a unique and challenging final state where we need to deconstruct displays photons, using the actors.
of the photon and, and it's directional light, which we use a smoking gun to look at the signal.
So, talking about the uniqueness of the final state, the first thing would be to talk about photon pointing. So what exactly it's pointing pointing is basically the direction of flight of the incoming photon when it hits on kilometers.
So the schedule for Atlas eagle is given on the left here and you can see that it's longitudinally segmented you have three different leaders, and let's imagine like a photon hits are equal and these are the energy deposits that you see in yellow in different
flavors of our kilometer. So typically if you're drawing simplistically for joining the centroid of the energy deposits and the first two layers and extrapolated back to the big by.
Let's say the photon was prompt and it was produced in the primary vertex coalition, then it would point back to the primary vertex on the beam pipe.
But in case the photon is produced from a disclaims object, as shown in the courtroom on the top right, you can see that when you join the red dots, which are the center of the energy deposit and extrapolated back.
You point back to a place on the bean pie which is away from the primary root x, and the separation between these two on the beam pipe is what we refer to as put on pointing.
So, here, basically, the direction of light is different, based on the Muslim the lifetime of the period particle and the angle at which the incoming photon is produced at the decay word next.
So, How good is the resolution.
Pointing resolution in the Atlas electromagnetic kilometer. It's shown in the bottom right plot here, where for example we can look at the point in resolution on the y axis and the photon PT on the x axis.
So the best case scenario for very high energetic for guns, we have a distribution of around 15 millimeters in the battle region, but in the region of interest for this analysis which is sitting in the bottom left year.
It's typically around 25 to 40 millimeters.
And the other variable that we use to distinguish our signal and background is put on timing, the electromagnetic calorie meter records the time of arrival of photon in each and every cell of the calorie meter.
So, in order to officially define the time of arrival, we look at a particular cell in the calorie meter which we refer to as the highest energy. So, in the second year.
This is basically where most of the photons energy is deposited in a single cell for the photons of interest to us which have PD of 10 to 30 gb almost 70% of the photons energy is deposited in this particular so so we use the time of arrival from the
So we use the time of arrival from the cell as a proxy for the entire cluster, but to avoid correlations with the neighboring cells, and the photon timing is defined as the delay in arrival time compared to the prompt photon.
And, as can be seen in the previous cartoon, the delay arises from the additional leg that the NSP travels before indicates into the photon for our signal.
So how exactly do we calibrate and measure the timing performance of our kilometer we do that using electrons from WP new decades and also the to eat.
Electrons are used as validation.
So, no tech for most instances electron. So it was a very good proxy for photons and this was definitely true in regression analyses, where we were looking at photons with bt of hundreds of gv, but the case is a little different for low PT photons, for
example, Then the middle thought here.
Before we applied any other correction we just took the calibrations from electrons and applied it to photons. So the electrons are in the blue curve here, and the red is the photons from radiative Zd case.
So, basically, there is some difference in performance of the timing for electrons and protons in the low PT or low energy range, which is of interest to us.
And at high energy is the basically agree with them statistics. So we wanted to make sure that we got this difference right because I think this was of the order of 200 because second difference in me.
So, once we identified that this was an issue, we looked at the debating can be done in cluster energy for both of the samples and we applied one additional production to account for any residual differences.
So once that was applied, we can see in the right most broad that the electrons, and the photons agree quite well in the loop at range.
So, the timing does solution itself.
Time dissolution decreases with energy as you would expect, and it plateaus around the been split of 200, because seconds for high energy photons. So typically, the region of interest to us is somewhere here, and we have a performance as good as 300 pixels
seconds. Exchange.
So these are the two variables that we would use to distinguish article and background, but how exactly do we select our events, it's listed here. As I mentioned before we using single laptop triggers and offline we require at least one laptop to be trigger
matched and PD greater than 27 GV. And it has pretty standard identification and isolation requirements. And then we require at least one battle photon with BD greater than 10 gb, and the battle requirement is important here because both the timing and
pointing performance in battle is much better compared to that in the gap teaching.
And one important thing that's put on is required to satisfy a loser identification requirement, which relies only on a minimal shower shaped variable, primarily in the second layer.
So this is important for this analysis because depending on the angle at which the signal photon hits the calorie meter the shower ship would look completely different from a prompt photon.
And this distinction could basically deconstruct our signal photons, as faithful been candidates and it will not pass the identification. So I'll just comment on those identification, a little later.
And once we select our events, we divide the analysis into multiple regions.
The to the signal regions are identified separately for two cases. One is where we target the signal points with the mask reading between the analysts be NSP to be greater than 10 gb.
This is what we refer to as high masquerading analysis, and the signal region is identified with met greater than 50 gb and the ESL, which I defined earlier which is the highest energy deposited so in the second layer of our calorie meter, greater than
10 ge.
tangy, the opposite analysis that proceeds in parallel to this is what targets the Loma splitting regime, where the mass difference is equal to 10 G. Here we increase the med code for our signal region to at gv to ensure the higher signal to background
ratio for the signal points. And we also reduce the diesel cut from 10 to seven gv for the low mass meeting analysis to increase our signal acceptance, because the photons, resulting from Loma splitting analysis generally are softer.
So we reduce the cell cut corresponding. Correspondingly, and for each of these analysis.
Quick, quick know you have about five minutes.
Yeah. So, these two analysis proceed in parallel, and the control lesion is.
So, there are two different regions that we define for the analysis one is the control region with the mechanism to TGV and another is a validation region with intermediate map.
So, this analysis completely uses data driven techniques PR background estimation, and our background is extensively validated in this intermediate validation region and also another region which is same as our signal region definition, but the negative
timing nation. This region is perfect because there is no signal contamination on the negative timing side, so we can basically use this as a proxy to make sure that our bedroom validation works and the background agrees with data in this region, all
of the validation plots are given in backup. If you're interested, and all of the selections and buildings that I mentioned here are optimized. But the heart of the analysis is how we basically performed to our time achieve the idea here is to perform
The idea here is to perform simultaneous speak to the timing sheet in the 10 different categories that we identify based on the photon pointing and the number of photons which are listed on the right to you.
So we basically categorize our events into one photon, and greetings on to put on channels, and in each of these be identified by pointing categories.
And then we picked the time distribution in each of these categories.
So just to give an analysis overview, how exactly do we determine our make our background estimation. So the goal of this analysis is to come up with the Standard Model background prediction, and then compare it against data and see how consistent, they
are with each other. So for this we basically start with the control region, and we identified two different timing shapes timing shape templates, one which has defined at stake for dance, and another one is really good on.
So the idea here is to form a complete basis of timing sheets, using two complementary put on timing distributions. And once we define two complementary put on timing distributions we can put any shape that we desire by basically doing a linear combination
of these two.
So, the way we define these templates would be given in the next slide, but basically the idea is we have a real photon timing template and a faithful on time and complete and we leave the mixing traction as a parameter and upset.
That's how we basically a cylinder background, and the validation is performed in the to intermediate region and the signal region itself, which is defined as our high mid region that signal typically populates in large pointing and timing bends, whereas
the background, which is predominantly made of jets are electrons speaking photons are prompt photons. These generally populate the low point in in timing distribution.
And then we fit the n dimensional PDF with the timing distributions in each of the student activities that we have.
And also we combine it with control region photons which pass a title identification requirement. So this ensures that the population of this timing template that we obtained is populated more by the real photons than any people dance, the complimentary
template for this is the fake enhanced template, where we required the photons in the control region to pass the loose identification but fail the data right instigation.
Once we required that these two templates completely define our basis for timing fits. And once we construct these templates, we, as I've shown before the hood on timing depends extremely on the eastern variable, because it correlated, and we need to
ensure that the templates that we have defined match in fanatics to our segmentation so this is done by a simple repeating in this variable.
And then we just put the venting, the way to templates, we see that they have a residual mean of around 50 because seconds so we just shipped the templates to make sure that there is no bias.
And finally the purity, which is the mixing faction of these two countries is a parameter and output.
So just a quick note on how our signal was his background looks before I show you a couple of resulting plots. So, the pointing distribution is shown on the left side for black and red flags here which are the real and the fake and constantly and different
different signal points are overlaid on the spot. You can see immediately that the pointing does not give you a very good discrimination between civilian background.
If our signal region time distribution looks like the red one.
On the other hand, if we look at the timing distribution on the right side, you can immediately see that the signal has much broader tail compared to both of the templates that we have.
So, timing would give you a smoking gun distinction between our signal in background which is the distribution we are trying to fit. And we slice and dice the categories based on the left plot here.
And just a quick note, the loose identification that I mentioned earlier, for the highest pointing categories that we have the identification admission fee is around, 80%, and this is why we use the loser identification, just as an example, if we had
used, medium or tighter identification which is more standard for photon objects and Atlas. This efficiency would be around 60% or lower. So that's why we restrict ourselves to the moves that identification here.
And just a quick note on the statistical model. So, the basically our timing PDF is moderated by this box that I showed you where NB is our background normalization which is a p parameter and outfit.
And this is basically the real enhanced template that is normalized with the mixing faction, and the fake enhanced template which is normalized by one minus the mixing faction.
So this part in entirety describes our background template. And then we combine it with our signal template which comes completely from Monte Carlo, put the normalization and the signal shape come from article.
The goal here is to fit our branching ratio pics to the NSP pair, that is a parameter of interest in the set.
Note that this is a very simplistic box here, all of the systematic uncertainties are of course included as research parameters so there are many one plus delta sigma terms that you can imagine, added to this box and extensive validation of the statistical
interpretation is performed in the validation regions and successfully So, so the data at least with the background and all of our validation regions that we have studied.
With that in mind, how does our data compared to background in our signal reason I'm showing you two of the categories that one of the categories that we have for both the high masquerading on the left and on the right.
So the question to ask you is how good data, these with background so you need to compare the black boys and the blue curves. And this is the highest pointing then so if there was a signal, like a shown in the red dashed line here at a brand new shop
around 20%, if it would have popped up as an example.
So, one spoiler, is that there's no exit. There's no significant exists that we have seen, either of the analysis, and given that the data and background the three points well with each other.
Now we can proceed to please exclusion limits on the signal models.
So how good do our limits look like we basically can exclude the branch and ratio pics to analysts be paid at around 1% for our best case signal point which is sitting here.
The mass of analysts bs on the x axis and the mass of the SP is on the y axis you put a lifetime of two nanoseconds. So basically the best performing scenario is the bottom right corner here which is, which also corresponds to the place where we have
the highest took on acceptance because this is the highest PT Hogan's life. And as we move away from this plot in either direction so put on acceptance drops, which also develops and worse sensitivity.
And given that the branching ratio pigs to undetected limit is around 20%, you can see this 10% control here, we can exclude, almost all of this space space, based on the analysis that I presented to you.
Similarly for 10 our second point, it's the same product shown on the right here for a different lifetime, and you can immediately see that the higher lifetime it gets the limits get worse, compared to the Lord lifetime because the probability of at least
one analysts be digging before the coloring goes down, and it eats into your signal acceptance, so isolated in this would be the last night I would show on, I can, I think we can concentrate on the top left one here, to here the branching ratio of x two
to analysts be limits are shown on the y axis against the lifetime of analysts be on the x axis, and for a mass of analysts be sitting at 60 G and different controls corresponding to different Master, LLC.
And one thing to note here is the sweet spot for our sensitivity lives around two nanoseconds and it gets worse in either direction at Holly lifetimes just.
They said just before the probability of at least one analysts be digging before color image of goes down.
Are you still there.
Anyone else here and they have
no we don't sound.
Okay, sounds like we lost her might have been another frozen connection.
Let's give it a couple of seconds to see if she comes back.
Yeah, it looks like she got ejected there we're getting, we're into the coffee break here. Let's just give her two seconds maybe she'll Connect. We're going to have a couple of questions, or maybe just one quick question.
She doesn't connect that we can take our coffee break and maybe have questions, at the very beginning before the next session.
Alright, let's do this.
She's probably going to be reconnecting so let's take our break right now and then we will ping, they have let her know that we can have a quick one or two questions at the very beginning of the next session.
And that is going to start at 445. So let's do that. Let's meet back here at 445 we can maybe have one quick question for now yeah and then Oh there she is.
Let's see if she's, she's here.
Hi, just confirming if you can still hear me. Now we can hear you this.
I'm extremely sorry for the disruption we lost like electricity few hours ago so I was connected with my phone so yeah abolishing is OK, no problem. I think you were pretty much the the idea.
Okay, no problem. I think you were pretty much to the idea. This is my first presentation I'm giving from India and, yeah, it's been a disaster so far.
Thanks for sticking with us, it's great.
Yeah, we're pretty much at the end of the time if you want to just wrap up or maybe have one time for one question.
Now, maybe you can just conclude now. So, this is, this analysis has been extremely exciting because it presents very unique challenges dealing with like non pointing and delete photons, and particularly the actors electromagnetic curry meter is equipped
to deal with this beautifully, it presents like a resolution in timing of 200 pixels seconds and pointing of 20 billion meters, which is great. Having said that, there are multiple things that we could improve on this analysis looking forward, and a couple
of things that I would personally like to do is one of them is to make this analysis much more modern independent. So currently one of the problems is that we using electronic triggers and triggering have a space where the photons are extremely soft,
and with low met. So, one thing that could benefit this analysis is to use equity are triggered on the time of arrival of the photons. If we have this please put on dedicated displays put on triggers, and then we could combine it with some met and make
this analysis, a little more model independent that we can also target this this space space, and also the one that thought that was targeted in on one hand drawn to without doing separate analysis.
One unique place that actors put into on compared to CMS is to improve the displays put on identification and the pointing integration and machine learning could be very useful to hear, because the signal shower shape looks completely different based
on the angle at which our signal heads and the traditional reconstruction algorithms that identify the photons could basically throughout our signal events, thinking that then of Bigfoot on candidate.
So, that would definitely be a place that we could improve. And also, CMS does something extremely clever, that they use the kind of information from the ego do to provide a complimentary method to exploit the displays jet space.
So something that actors can also do in round three and beyond. So I see a lot of excitement, at least with the displays protons in the near future, and I hope you do too as well.
Thank you very much for sticking with me for this entire time. Apologies again.
No no no problem at all. Thanks for thanks for sticking with us since seen it through the end. We have time for maybe one quick question for now.
Okay, we have a couple of quick points so Joel, go ahead.
Hi, can you hear me. Yeah, I can hear you.
Yeah. Have you considered a triggering we have the victor bosom fusion.
I understand that the background sir, or bit more under control, you should.
Yeah, I think.
Yeah, one thing that we only did here is the associated production, but definitely like VBF and also glue on long fusion could be another place that we could considerably improve in our cross sections as well, but I'm not sure like how good the forward.
Triggers are project triggers are in this case so we have not really looked at that.
Thank you.
All right. Fantastic. In the interest of time, let's take the further questions and let's put them over to matter most. Now you'll probably find your way over no matter most at some point and if there's any follow up questions is a good place to put them.
And for now let's take our coffee break, and we will come back at 445 so about seven minutes right quick espresso and then come back here for the discussion of the DDXXS, quote unquote, So, see you back in a few minutes.