Juliette Alimena: Okay
Juliette Alimena: and
Juliette Alimena: share my screen. I just have a couple slides of news.
Juliette Alimena: Okay.
Juliette Alimena: yep, I'll I'll get started. So welcome everyone to the Fcc meeting. So I just have a couple of slides of of news. This slide, I think all the content you've already seen, but in case. You haven't been in a meeting lately. I wanted to remind you, because this is important. 1st on the Fcc. Report. The the midterm report is available on the on Cvs to all cern users.
Juliette Alimena: It's at the the link here. I don't know what the plan is for making it public to absolutely everyone. But I believe that's still in the plan.
Juliette Alimena: Then the final feasibility study report.
Juliette Alimena: The 1st draft of that needs to be ready by the end of the year.
Juliette Alimena: And we will have a version 0 draft for internal fcc. Peb. Review by the end of September. So, therefore, your drafts of your analysis. Notes need to be ready by early September. So that's the the main deadline to to keep in mind.
Juliette Alimena: And then, of course, the final report will be an official document.
Juliette Alimena: totally public and submitted to the European strategy Report
Juliette Alimena: and along with the strategy report, there's expo deadlines.
Juliette Alimena: In particular. There's the Efa Higgs factories workshop in Paris in early October, and the the link
Juliette Alimena: to to that agenda is here. So the the equivalent deadlines are in time for for this workshop. So
Juliette Alimena: basically, by by early September you should be really finalizing. Your write ups of what you're working on
Juliette Alimena: if you want it to be included in in these reports.
Juliette Alimena: So for the Fcc. Notes in in general. Again copying the slides from the physics and performance meetings, or the last several the. They have, like a common sense, policy and publication of Fcc. Related events. It includes Monte Carlo and tools and statistics from the Fcc. And has Fcc. In the title.
Juliette Alimena: you know, it should should be reviewed by internally within the fcc collaboration. So it'd be good to have a detailed Scc. Note posted, as well as a draft of the paper in in Cds. And presented in the physics and performance meeting at least once.
Juliette Alimena: and the physics and performance conveners will define reviewers for a speedy decision on this mission. So it's not as lengthy of a approval process as you may might be used to from your Lhc collaborations. But
Juliette Alimena: it is important to keep everyone in involved and aware of your results. And we are a loose collaboration of the Fcc.
Juliette Alimena: So several notes have apparently still been hanging there for for months, and we'd like to get them published. I'm not sure this applies to to any of us, but if so, let me know.
Juliette Alimena: Okay, I think my penultimate slide. There is a talk opportunity. For the hypo camio Conde experiment, and for an event that's happening at Kit in Browser in in October. Actually, I think it overlaps with the
Juliette Alimena: the exit meeting. But the idea is to to talk about Fcc with particular emphasis on the search for proton the case. Another Barron number violating processes. But this, this could be relevant to heavy neutral leptons. So if you're interested in
Juliette Alimena: in this talk, opportunity, the the link is here.
Juliette Alimena: Okay, so
Juliette Alimena: today we'll hear 2 talks, one from Tom about the Dnn in the electron, H and L channel. And so this is an update of on ongoing work. And then the second presentation will be from Richards. Talking in in this group for the 1st time about feasibility studies for dark photon production in Higgs, the case at the Fcc.
Juliette Alimena: Next week
Juliette Alimena: Fcc. Week in San Francisco, so we won't have this meeting next week.
Juliette Alimena: and I encourage you to follow the Fcc. Week in instead. There's a number of interesting talks that could be relevant to to what we all are working on. I suggest you look at the agenda and search for Bsm or Hml, or or similar keywords, and find the talks you're interested in. It's not other ones.
Juliette Alimena: Ichabex House coming up in July. There's many Scc. Talks and posters happening then. Including.
Juliette Alimena: I believe, it's a talk from from Nicolo on Bsm physics and H. And l's at the Fcc.
Juliette Alimena: And then the the Exa workshop in Paris I already mentioned, and there will be an Fcc. Italy, France workshop in in Venice in in November. And remember, these are the links to the Fcc. Full. SIM and Fcc. Analysis meetings, as well as the the Fcc. Seminars, all which could be of particular interest to to all of us.
Juliette Alimena: And that's all. I had questions on the news.
Juliette Alimena: Okay, I'm not seeing any. So then we can move to Tom.
Tom Critchley: Hello! I'll just try and share my slides. It's always a bit dodgy as to whether it works so.
Juliette Alimena: Okay. Good. Luck.
Tom Critchley: Do you see them?
Juliette Alimena: Yes.
Tom Critchley: This is wonderful news.
Tom Critchley: so.
Juliette Alimena: Do you wanna make them full screen.
Tom Critchley: Yeah.
Tom Critchley: oh, if it lets me.
Tom Critchley: well.
Juliette Alimena: It's pretty close to full screen. So if it doesn't work.
Tom Critchley: There you go. That's okay.
Juliette Alimena: Yep, great.
Tom Critchley: So today, I'm just gonna give you an update
Tom Critchley: on the electron digit final state of the H&S at the Fcc and those of you that were at the last presentation may be aware that the focus of this study has been to optimize existing cut and count limits by using machine learning techniques. So so far, we've tried
Tom Critchley: a Bdt, and recently, we've been trying to push this further or match the performance by using a Dnn. So I'm working with Anna and Penthelles on this as my master's project.
Tom Critchley: So as a quick, quick introduction maybe more for me than you guys cause I'm sure you're all aware of it. But while writing my thesis, I've been really trying to get to grips with the with the theory. So, of course, neutrinos are massive objects, but they have very small masses which we've seen by the baseline neutrino oscillation experiments.
Tom Critchley: And one way we like to explain these masses is by using the Cecil mechanism.
Tom Critchley: and to have these pseudo direct H and ls, we use this low scale inverse cesal mechanism?
Tom Critchley: And if we stipulate that they would have a similar power couplings to the electron, we can reasonably search in this sort of Gv range. Which is where we perform this study between 10 and 8 to Gv. With the mixing angle squared between 10 to the minus, 1 10 to minus 10
Tom Critchley: and we're searching in the final state that has exactly one electron and 2 jets. So you can see this left on number conserving fireman diagram in the bottom here for just one of the possible final states.
Tom Critchley: And then on the right here, there's an image sort of intuiting the the premise of the seasonal mechanism. So in this direct scheme you have very small Mayorana masses which lead to the small standard model neutrino masses and heavy, direct masses which are possibly degenerate in the limit where the major animal mass mu S. Is 0.
Tom Critchley: And so how do we search for these at the fccce. Well.
Tom Critchley: the Fcc. Is going to produce some 10 to the 12 Z. Bosons in its set channel run.
Tom Critchley: and this high luminosity pileup free environment.
Tom Critchley: Will be a really great detector environment to search for
Tom Critchley: to search for our signatures and possibly improve on the limits set by experiments such as lap.
Tom Critchley: and one of the really interesting features about some of the H. And RS. In the parameter space that we look is that if you look on the left here, as we approach the bottom left left hand corner of the parameter space we end up having very long lived particles. Due to the relation that the lifetime is in inversely proportional to the 5th square of the mass and the square
Tom Critchley: of the coupling.
Tom Critchley: And so we can parameterize this with any of the the sort of related parameters to the lifetime. In this analysis we tend to focus on using the D 0 or the d 0 significance.
Tom Critchley: And so for these mass points, there are some techniques we can try and use to sort of tease away the long lived from the prompt decays and consider both, which is a really nice natural feature of the machine learning models we consider.
Tom Critchley: And so in our analysis, we focus on 3 standard model background processes, the 2 centrally generated Z to Bb and CC. And then one locally generated Z to 4 body decay, which we use in place of, for example, the Z to Tao Tau final state, which is what you see
Tom Critchley: on the bottom left diagram there.
Tom Critchley: And just to sort of, say, now, obviously, we're all aware that one of the big problems of studies like this at this stage is the very low luminosity of the production samples compared to what we're trying to model at the Fcc. So
Tom Critchley: and this top table here, you see the production luminosity for the Bb and CC. Is around 1050 bum
Tom Critchley: and then for our centrally generates, for our locally generated samples, for example, to 4 body and the signal events, we have much higher.
Tom Critchley: higher luminosity. But
Tom Critchley: what that means is that for this analysis we focus on looking at 10 femme for which we have adequate statistics, and then only in the final result, we scale to 150 outer bounds.
Tom Critchley: So a summary of the cut and count study the 1st part of this of this project has been to reproduce the cut and count as per Dmitry's thesis which I've linked here.
Tom Critchley: and after all the cuts you see on the left.
Tom Critchley: That we have the invariant mass distribution for 3 benchmark mass points against the the sum of the backgrounds, and you have 3 distinct peaks, as well as some peaks coming from the background, but mostly these 3 peaks, where we can derive some significance which is calculated from the equation on the right.
Tom Critchley: and then projecting this across all the possible points in the parameter space. We get this delimitation around 10 to the minus 6 in the mixing angles.
Tom Critchley: Which is a really nice place to start, and we have on the right here a summary of the cuts. So we cut on the missing energy. The V electron energy, the 3D digit angle and the digit electron delta r.
Tom Critchley: and we normalize 10 funds upon just using that equation there where
Tom Critchley: we're using the selection efficiency at the luminosity
Tom Critchley: and the number in the sample and the cross section.
Tom Critchley: So how do we optimize this? Well, the 2 natural follow-ons from a cut and count study might be to use a Bdt. Or a Dnn.
Tom Critchley: And the really strong advantages here.
Tom Critchley: That, firstly, we don't have to make these sequential cuts on the variables, which might be correlated in some way. But instead, we can just let the Bdt or the Dnn figure out nonlinear and complex relationships between the variables.
Tom Critchley: Categorize the events, and then we just make one cut on the Bdt or the Dnn school.
Tom Critchley: and we keep all the events background on signal, which have, say, a Dnn cut of more than 0 point 8. Something like this.
Tom Critchley: and the other really good advantage is that we don't have to perform this cut and count on some benchmark variables and make global cuts. But instead, we can train a Bdt or a Dnn for each individual mass point.
Tom Critchley: which very naturally lends itself to exploiting exploiting features like the d. 0, and naturally separating the Llps.
Tom Critchley: and so the features we use to train our Bdt and Dnnn
Tom Critchley: here on the bottom right? So we use lots of the leading electron energy leading electron variables, such as the energy, the Phi, the d. 0, the sigma of d. 0, etc. And then for the neutrino and digest system. And then, more recently, I think, things that were added since the last presentation for the Bdt.
Tom Critchley: The sort of tracking related variables. So the the number of tracks, the number of primary tracks, and the Chi squared of the primary vertex.
Tom Critchley: And so the the workflow for the Bdt is such that we, I mean, as with most machine learning models, we have the stage one data preparation. So we load the ntuples that were generated via
Tom Critchley: the stage one of the sec. Analysis framework.
Tom Critchley: We apply some filter to reduce the number of events. So from the cut and count, we see that the lid electron energy is a really nice filter
Tom Critchley: to just reduce the ratio of background relative to the signal and then we perform some split to the training and the test sets, and then we save them, using Tmba as a root file.
Tom Critchley: We pass these to the model training, where the high parameters of the Bdt. Are optimized with the grid search. Then some decision. Trees are made. They're gradient boosted against each other to make predictions, and we save once again the model as a root file.
Tom Critchley: and then the models are applied to this test, set normalized to a chosen luminosity, and we choose a Bdt cup based only on calculating the significance and choosing the region which preserves the highest significance.
Tom Critchley: So the top. Here you see an example of one possible decision tree. I I like looking at these because they're very intuitive to understand. It's quite as you would expect for one single decision. Tree, you say. Look at the missing energy. Is it greater or less than 29? Yes or no, and then it sequentially goes through other variables in order to make
Tom Critchley: our predictions on the probability that an event is signal or background.
Tom Critchley: and then on the bottom. Right here you see
Tom Critchley: what it looks like to just have a raw classification in the background and the signal. So in the red we have the background
Tom Critchley: and in the blue we have the signal in an ideal situation. You have all your events for signal at a prediction of one. All your events for background, a a prediction of 0. But in reality you have this sort of distribution that tails off
Tom Critchley: for both the signal and the background, and you would end up making a cut above 0 point 9 and preserving the events that have a favorable background to signal ratio.
Tom Critchley: So for the Bdt result. It's it's quite different. Since the last time I presented we have
Tom Critchley: at points almost 2 orders of magnitude greater the limitation with the h and L couplings.
Tom Critchley: And so if we look here and focus specifically on the 50 Gv mass point at 10 to the minus 6, you can see the raw classification on the top right. And then from here we zoom into this so called signal region. Between 0 point 9 and one. We look at the distribution with the finer binning, and you can see here because the Bdt. Is performing really well, and the peak at one is very much distinctly at one, and not maybe at 0 point 9. As you zoom in
Tom Critchley: we can make a really really strict cut of 0 point 9 9 9.
Tom Critchley: And for this particular mass point that preserves 13.5 signal events and just over one background event.
Tom Critchley: We sort of at this stage of the study. We're rationalizing. The low yields specifically in the background. Just because we're only normalizing this to 10 femtibun. So if we were working at the full statistics of the Fcc.
Tom Critchley: I think these yields would would be acceptable.
Tom Critchley: And so then, for the Dnn. Just to sort of
Tom Critchley: continue on this optimization trend, it's very much the same setup for
Tom Critchley: the dates. Preparation is the stage one. So this time, through experimenting with different filters, we actually apply at this stage a little bit of a harsher filter. So we have less events for the training and testing. So this is on on the lead. Electron, energy is greater than 20 gb.
Tom Critchley: and then, instead of as a root file, we're we're saving the data sets in numpy.
Tom Critchley: and there's some feature flattening that takes place in order to have
Tom Critchley: distributions for the for the variables that are centered between 0 and one rather than
Tom Critchley: rather than being over the full range, because this is easier for the Dnn. To interpret
Tom Critchley: for the model training. Unfortunately, the biggest difference, I would say, so far between the Dnnn. And the Bdt. In terms of the training is that
Tom Critchley: the Dnn. And have
Tom Critchley: I have a lot more hype promises that you can experiment with, which in some ways is a good thing, because it's sort of this endless process being able to optimize. But
Tom Critchley: unfortunately, unlike the Bdt, it's not really possible to do a grid search, because this would
Tom Critchley: take a very long time. So instead, we do a random search for a given amount of trials, and we focus on things like the learning rate
Tom Critchley: or the number of layers in the model.
Tom Critchley: We then train the model for a hundred ebox and target to minimize the validation loss.
Tom Critchley: and then the final process is very similar. In that we look at the raw predictions. We take a Dnn cut that optimizes the significance, and we preserve these events that fall above the cup.
Tom Critchley: So you can see actually from this distribution here that in terms of just its classification ability, the Dnnn is performing exceptionally well, it's it's arguably even better than the Bdt
Tom Critchley: a specific threshold for separating the background and the signal.
Tom Critchley: But if if we look onto the result, unfortunately, what we see is that it's not currently quite as good
Tom Critchley: at predicting the significance as the Bdt. Because when we zoom into the signal region, we have much less of a crisp peak and more of a smearing around
Tom Critchley: 0 point 0 point 9 5 to one.
Tom Critchley: And so in this case we have to make a lusita cut of 0 point 9 8 6
Tom Critchley: And what that ultimately means is our significant suffers because we have to allow for more background events.
Tom Critchley: And so, lastly, then, focusing again on the Bdt. One thing that was very natural to try was to include some d. 0 parameter in the filter itself in order to target. Long lived and prompt a case.
Tom Critchley: And so we see here on the left hand plot,
Tom Critchley: when we target these long lived particles
Tom Critchley: with the with the blue delimitation line, we see that we push slightly more into the parameter space, which at 1st was quite surprising that it wasn't more because we're isolating the number of background events that are entering the training. And so you might think that it's able to find more distinct patterns with the with the signal. But if you look at the bottom right
Tom Critchley: when we're when we're plotting the feature importance for each model trained, we see that already at this point the model is starting to really, effectively utilize the D 0. And so we're not really able to push too far into that parameter space, because we've naturally been able to find this relationship between the lifetime in the initial models, and then again, with the with the sort of sign line
Tom Critchley: for the for the prompt
Tom Critchley: decays.
Tom Critchley: We're not really seeing much to limitation improvement but this is still a really nice check to ensure that the Bdt. Is optimized properly for using these long live signatures.
Tom Critchley: So as a final comparison of the strategy, I've plotted here the the 2 Sigma delimitation for the cut and count the Bdt. And the Dnn.
Tom Critchley: And so far it seems like the Bbts.
Tom Critchley: Let's say, almost 2 orders of magnitude more in the couplings compared to the cut and count, whereas the Dnn. Is only maybe around one order of magnitude.
Tom Critchley: But at this stage it's not really robust. It's not really a robust claim to say that the Bdt is necessarily better, especially as we saw that as a classification
Tom Critchley: and just in terms of the machine learning aspects. It's not necessarily a worse, opt a worse classifier. But instead, we just need to focus on how we can, how we can make this very small signal region be more of a peak for the significance, calculation?
Tom Critchley: And it's still expected in these last few weeks that we can maybe optimize this line to match the Bdc performance by possibly treating it as a multi classification problem.
Tom Critchley: Because currently, what we do is we treat all 3 backgrounds as one sort of super background and compare this to the signal in a binary classification task.
Tom Critchley: There are several attempts we can try as a multi classification problem to see if that gives us better significance in the end. For the Dnn.
Tom Critchley: As well as that. Maybe more work on the high parameter optimization and the feature engineering can be done. So there's still lots of time to improve this result.
Tom Critchley: So as a conclusion, if we look at our study and context. I have this plot on the left here which appends the most recent Cms. Limit from a few months ago.
Tom Critchley: as well as the 150 attribution cut and count from Dimitri's thesis. This work is in red here from the Bdt result, and then the projected Fcc limit from the paper I've added here
Tom Critchley: and also at the bottom here, just the type one seesaw limit now, where we wouldn't expect to be able to push in this theory, anyway.
Tom Critchley: And it might be quite a surprising result to see that even with only around 50% of the branching ratio of the H and l's, we are already cresting upon the Fcc. Expected limit.
Tom Critchley: I think it's fair to say that this is somewhat difficult to interpret without the related uncertainties. If we're working with around 10 femtana statistics and then scaling to the 150 attributes. I think maybe it's
Tom Critchley: It's worth some attempt to categorize what kind of systematic and statistical uncertainties we have here. But certainly what we can say from this plot is that
Tom Critchley: this method, using this Bdt and hopefully in the end, also using a Dnn, we are much better at delimiting the parameter space than just using typical cut and count methods.
Tom Critchley: So what's really important now, for a study like this is one to categorize the uncertainties and 2 to possibly try and find global filters in order to reduce the statistical uncertainties. So that we can make a more robust claim about the discovery potential at the fully luminosity of the Fcc.
Tom Critchley: So thank you very much. I'd be more than happy to take any questions, because I have my thesis events in some 3 weeks. So
Tom Critchley: anything I don't understand properly would be very nice to
Tom Critchley: to get to grips with now. So thank you very much.
Juliette Alimena: Okay, great thanks, a lot
Juliette Alimena: questions. I have a few. But other people can go first.st
Juliette Alimena: Or I can ask if people are still thinking.
Juliette Alimena: Okay, on slide 6.
Juliette Alimena: right. You said you trained a separate Bdt for each signal mass point. But are you varying the the coupling as well? So do you also ha! Have a different training for for different couplings.
Tom Critchley: Yeah, sorry. So that's maybe quite confusing. Wedding for this plot on the left there's a model train for each point. And so all 56 points. Have a train.
Juliette Alimena: Okay, so so mass and coupling point, okay, cool. Just just checking.
Tom Critchley: Yeah, sorry. It's just I worded it confusingly.
Juliette Alimena: No, no worries. But I just wanted to check that my main question about this was
Juliette Alimena: does. So
Juliette Alimena: I I actually, I realize you showed it later on. This plot showing, I think, showing the most important variable for the Bdt for each mass point. Does that
Juliette Alimena: is that sort of changes you expect. Given mass and and coupling and and other things.
Tom Critchley: Definitely. The D. 0 is is really nice to see, and the main reason I wanted to see these plots in the 1st place, so I should maybe explain quickly that the one on the left here is for the Dnn. And the one on the right is for the Bdt.
Tom Critchley: I think the d. 0 and the missing energy are both very expected.
Tom Critchley: I think all we can really do when talking about like the missing energy theater or the lead electron energy. Here at 40 Gv. Times 10 to the minus 5 mixing
Tom Critchley: is maybe speculate. And by looking at the distributions. But
Tom Critchley: I would say that the main thing I think about when I look at these 2 together is just that
Tom Critchley: the fact that the Bdc. Is using more variables than the Dnn
Tom Critchley: is maybe just a sign that it's actually learning the patterns more effectively, whereas
Tom Critchley: on the Dnnn here, you see, almost everything is just just the missing
Tom Critchley: the missing energy, except for this
Tom Critchley: long lived particles. Region.
Tom Critchley: But I would say, mostly it's it's what you would expect, for example, in this
Tom Critchley: low mass, low, low coupling
Tom Critchley: region for the Bdt where we have the electron digit being the most important. This is possibly just because we have very low low mass
Tom Critchley: H and l's to produce this digit electron final state. And so
Tom Critchley: maybe these these jets in the electron are quite collimated. And so this is more differentiable than than for the higher mass points where the higher momentum into final states is gonna give you more more of a range in the electron digest system.
Juliette Alimena: Okay, great.
Juliette Alimena: I think these plots are are cool. So if you, my my recommendation, if you include, include them in your thesis or some other public thing is that you make the font a little bigger because.
Tom Critchley: Yeah, it's quite difficult to read.
Juliette Alimena: Can't see it.
Tom Critchley: Yeah, I can do that quite easily.
Juliette Alimena: Thanks.
Juliette Alimena: I I've got another question or 2. But do other people have questions.
micheleselvaggi: Maybe I see one
micheleselvaggi: on this point of the can I ask you, Juliet, or want to add.
Juliette Alimena: Yeah. Yeah. Go ahead.
micheleselvaggi: So I did.
micheleselvaggi: despite of a low mass being boosted.
micheleselvaggi: do you?
micheleselvaggi: Because most likely in those cases the electron identification will be harder, right, because it would be
micheleselvaggi: inside the jet.
micheleselvaggi: So and most likely
micheleselvaggi: are probably using some flat identification.
micheleselvaggi: If you should see it
micheleselvaggi: independently on whether the electron is in or out is in or out of the chat.
micheleselvaggi: and if he
micheleselvaggi: so it would be.
micheleselvaggi: I mean, it would be interesting to see what's there.
micheleselvaggi: I mean, how how much of an impact the the electron Id would have in this case
micheleselvaggi: have that inside the jet.
Tom Critchley: I might be wrong in thinking this, because this was introduced before I started my thesis. But I think
Tom Critchley: that one of the things we maybe do differently to other central analysis is that we use our own
Tom Critchley: jet reconstruction, such that we exclude the electrons from the jet objects when they're formed.
Tom Critchley: But this might be wrong.
micheleselvaggi: Right. But now this is probably correct. But the thing is whether you're able to distinguish an electron
micheleselvaggi: inside the chat in the 1st place, to veto it.
Pantelis Kontaxakis: You're right, actually, me careless. So yes, this is actually something that we should investigate further. And I think this would be very interesting.
Pantelis Kontaxakis: Yes, thanks a lot for this Jason platform.
Juliette Alimena: Okay, other questions.
Juliette Alimena: maybe another dumb one for for me. So on. Slide 13. This was like your your conclusion. Slide.
Juliette Alimena: I I'm just curious, can, in in case you include this plot anywhere or show it again, would you mind scaling the Cms. Result also to 150 inverse out of Barnes. Just cause I can't do it in my head.
Juliette Alimena: Yeah.
Tom Critchley: Shall.
Juliette Alimena: Thanks. I I just. I'm just curious to compare apples to apples.
Tom Critchley: Yeah.
Pantelis Kontaxakis: Exactly. This is what we're discussing, actually to just have a, you know, a direct comparison for everything. And so don't just avoid and avoid any confusion. Actually, yeah.
Tom Critchley: Yeah.
Tom Critchley: yeah, that could be interesting to see?
Juliette Alimena: Cool
Juliette Alimena: and then just one other question about sort of your your plans. You said you're pending your thesis in about 3 or 3 weeks. And do you plan to to make a an Fcc note and include this, you know, for the the feasibility study
Juliette Alimena: for the report.
Tom Critchley: I'm happy to do anything, so I think this is more dependent on a Anna and Pans Alice's plan with the work, but for sure I'd be happy to keep working on this in some capacity. It's quite interesting.
Pantelis Kontaxakis: Yeah, I think from our side, this is something that we can just pursue further. I'm not sure. And I, if you have any other
Pantelis Kontaxakis: opinion to that.
Pantelis Kontaxakis: But I think this is the plan.
micheleselvaggi: Plus, I think any master's thesis can be easily made into an casino.
Juliette Alimena: Okay, great.
Juliette Alimena: And we'll we'll keep you in our account
Juliette Alimena: of notes. Planned? Awesome.
Juliette Alimena: Okay? Any final questions for for Tom.
micheleselvaggi: Maybe another name one I can. The the the fact that you optimize the Bt also versus coupling.
micheleselvaggi: So I can see that the the
micheleselvaggi: probably the only thing will which will change for a fixed mass is the
micheleselvaggi: is whether the the
micheleselvaggi: how's it called the the channel is long lived or not right, the only thing, or you expect the
micheleselvaggi: so do you really need this? This? Bdt, besides.
micheleselvaggi: the disability optimization versus coupling.
Tom Critchley: I think
Tom Critchley: I think in the end, one of the good things about using machine learning in a space like this is that it doesn't really require any extra effort from our side to just
Tom Critchley: just submit the jobs to Ht. Condor or something and let it do a model for each
Tom Critchley: because there, there maybe are some some differences except for just the lifetime, the
Tom Critchley: that the model will find that aren't necessarily intuitive to us by just looking at the distributions.
micheleselvaggi: But did you have a did you have a look at the distributions and see if anything else besides the lifetime of the
micheleselvaggi: so below. Probably. What? What is the most impactful? Here is the displacement of electrons and trucks. I guess right.
Tom Critchley: Yeah, yeah. It would be interesting actually, to see, because for all of the distributions I've I've plotted on this slide, for example. This is 3 mass points that are fixed coupling. So I'm not actually 100% sure how these distributions change for a fixed mass and different coupling other than
Tom Critchley: like I said about the lifetime, but that would be really interesting to see you.
micheleselvaggi: Okay. Cool.
Juliette Alimena: Okay, great anything else.
Juliette Alimena: I'm not hearing anything. So thanks a lot, Tom, and we move on to the the next talk
Juliette Alimena: from from Richards.
Richards Gonzalez: Share my slides.
Juliette Alimena: Awesome.
Richards Gonzalez: Can you see them properly? Yeah.
Juliette Alimena: Yep.
Richards Gonzalez: Cool. Hi, everyone very happy to start iterating with you guys in these meetings
Richards Gonzalez: So today, we'd just like to very briefly discuss, and
Richards Gonzalez: our interest on looking into dark food and production in Hix the case at Fc.
Richards Gonzalez: so I'd like to just like to start introducing the dot deck to sign the dot sector signature. So dot sectors are not new to the group. Like dot sectors are general like, are studied as general possibility in Collidas. Given that they offer minimal extensions to the ascender model dark matter candidates and areas and different exotic signatures.
Richards Gonzalez: particularly at the Lhc.
Richards Gonzalez: When light dark particles are produced with large boosts these would cause dedicated products to be collimated and form jet lestructors these jet lestructors or some of these jets, like tractors, or the most popular ones, are usually referred to as Lepton jets, which are simply a cluster of collimated light charged particles. This can be electrons or quarks.
Richards Gonzalez: and these left and jet like signatures, arise in in dot sector models that are composed of these unstable, unstable particles with masses in the Mevgv range.
Richards Gonzalez: Where, then, these particles can decay to some amount of particles? A clear example, for example, is this a dark sector extension where we have an additional u 1 dark symmetry, where we have an effective kinematic mix in between a dark photon and a sun, and the centimetered photon allowing for the for the case where these dark photons are produced. Then they can mix with it a centimeter photon and dictate particles
Richards Gonzalez: creating these lips and jet signatures. So I just want to, very briefly.
Richards Gonzalez: let you know what we did or what we've done before. For this leptin jet, like signatures in Atlas, particularly in displaced leptin jet, like signatures in run to data
Richards Gonzalez: where we probed. 3 different modes. Production modes of the hix
Richards Gonzalez: and where we're also, working on around 3 analysts iteration.
Richards Gonzalez: So to very briefly
Richards Gonzalez: tell you about the search that we did. We focused mainly on certitude of the Hicks where the Hicks is decaying to 2 dark photons and possibly
Richards Gonzalez: missing energy. This is, don't be the Higson vector's the one that I referred to before.
Richards Gonzalez: It's the vector portal corresponding to the kinematic mixing between the duct photon and the Sonoma photon.
Richards Gonzalez: We looked into 3 different production modes of the Hicks gloom, glo infusion, associated production with the W and back toverse infusion, and then into a couple of benchmark decay modes that one called Fab. Set where you can see that 2 dark photons to where you can see that the Hicks the case to a couple of dark fermions.
Richards Gonzalez: but then radiate a dark foot in each.
Richards Gonzalez: and in the case of the HHM. We don't have any additional dark fermions present in the signal, and we only have the production of 2 dark photons that then subsequently decay to a couple of fermions.
Richards Gonzalez: This gives us in turn a final state of displace leptin jet, like signatures, with the possibility of additional missing ET.
Richards Gonzalez: Here, where we can set the kinematic mixing parameter, the dark photon.
Richards Gonzalez: small enough, such that we can ensure the Dark 14 is long lived.
Richards Gonzalez: and then, if the dark footing is light enough with masses from 10 mev. To 10 Gv. We can ensure the decay of the dark footing is going to be collimated.
Richards Gonzalez: The actual decay of the duck photon. It depends on the mass of the duck photon, and this is also related to the C 1,000 or photon, such that we can prove
Richards Gonzalez: by choosing different mass and sea tower scenarios, we can prove different displacement and
Richards Gonzalez: collimation scenarios as well.
Richards Gonzalez: So.
Richards Gonzalez: regarding the display, slept and jet signature, and this is particularly the way that we define it in Atlas. So we have this custom reconstructed objects that we call dark Fulton jets. So if I say, Dpj.
Richards Gonzalez: in the future. You know what I mean.
Richards Gonzalez: where we are basically sensitive to the case of the dark photons that are after the pixel detector.
Richards Gonzalez: So beyond the the outside, beyond the idea acceptance.
Richards Gonzalez: We have 2 types of dark photons. One's called municip Dpj.
Richards Gonzalez: and the other one's called color Dpj. In the immunic case. This is where the doctor indicates to Meon and immune.
Richards Gonzalez: Again, we target the case that are outside the id acceptance. And this is basically a signature of a pair of close by
Richards Gonzalez: muon spectrometer only tracks with no matching tracks in the Ad.
Richards Gonzalez: And for the color Gpa case, we target decay in the adrenalic calorimeter. That means that we are looking into low electromagnetic fraction jets with no matching.
Richards Gonzalez: It tracks in the immune spectrometer such that the 2 categories are exclusive.
Richards Gonzalez: So that's our signal definition. So in this case, for the kind of Dpj just to note.
Richards Gonzalez: this category of color. Dpj reconstructed object.
Richards Gonzalez: happens when we have both the decay to electron positron and to quarks. But this is only because the displacement of the dark photon is enough such that the electronic that the energy deposited on the electromagnetic calamity is going to be low.
Richards Gonzalez: and
Richards Gonzalez: such we look at the reconstruction on the atronic calamity.
Richards Gonzalez: So our rental results are basically, we explored a dark photo masses from 17 MEV. To 15 GV.
Richards Gonzalez: And lifetimes that translate on a sea towel from 2 to 1,000 this seat, then.
Richards Gonzalez: times Gamma and Beta. It gives us a proper decay length, such that we can make sure that the dark forces are indeed decaying.
Richards Gonzalez: And the fiducial volume of the detector.
Richards Gonzalez: The plots that you can see on the right. Basically are
Richards Gonzalez: final branching ratio limits, and this is an upper limit on the branching ratio of the Hicks. To this dark photon and final state.
Richards Gonzalez: So on the left. You have a photo mass of 1.1 Gv. And on the right of 10 GV.
Richards Gonzalez: The red curve dashed corresponds to the Bbf combination. So it's the combination of all the channels that we define on Bbf.
Richards Gonzalez: And then we performed the combination of the Bvf production mode with the previous lease, explored gloom, fission, and WH. To produce the
Richards Gonzalez: Brazilian curve that you can see on the top plots.
Richards Gonzalez: this is in general such that we can have an idea where you guys can get an idea of where the range of masses that we proved and the size of the displacements that we were targeting
Richards Gonzalez: this results. I interpreted it in accepting kicks to cases, scenarios to lonely particles, and in general start sector models, interpretations. Where we have, therefore, we said on the HHM. Benchmark. The case that I mentioned before.
Richards Gonzalez: The caveat in this case is that the full combination that we performed in Atlas for gloom, fusion. WH. And Bbf is only Fab
Richards Gonzalez: and this is not ideal, since since Fab is not commonly used compared to other minimum models as that I studied.
Richards Gonzalez: But many other people.
Richards Gonzalez: To finish with this slide. I just want to mention that this apple limits on the branching ratio of the Higgs to this exotic decay
Richards Gonzalez: translate them to a 2D exclusion limit as a function of the master detached photon and the kinetic mixing parameter epsilon
Richards Gonzalez: so that's the
Richards Gonzalez: atlas stays, and at a glance. But we are interested in looking if we can do something similar at Fcc.
Richards Gonzalez: So what we what we want to do is have a 1st look into the foot in production and hix the case at the Fcc.
Richards Gonzalez: This goes compliments really well with other ongoing Fcclp. Searches that are going in the group within the group.
Richards Gonzalez: It's similar to
Richards Gonzalez: display signatures coming from Aops like the displaced Lepton pairs, scenarios
Richards Gonzalez: and there's and it also constitutes an additional exotic hix scenario A on top of the longit scalar search that is currently ongoing as well.
Richards Gonzalez: So for this we are preliminary targeting Fcc. Associated production with the set bosun
Richards Gonzalez: plus the Hmp HD benchmark
Richards Gonzalez: so such that our signal looks like this where from each dot photon decay, we get a lectern, a Dpj like signature.
Richards Gonzalez: In this case we
Richards Gonzalez: have been associated to production, for now we've simulated the set decay into a couple of lectons. But we're open to considering also the decay
Richards Gonzalez: to Quark's.
Richards Gonzalez: Given that, we know that we have really good Mass Boston,
Richards Gonzalez: And and
Richards Gonzalez: like recognition, capability. And then we have the hix the case with a couple of dark photons. This is done at center of mass energy of 240 Gv.
Richards Gonzalez: And from this process our experimental signature would be basically a reconstructed set bosun from
Richards Gonzalez: Lepton pair or a quark pair.
Richards Gonzalez: and displaced dark photon jet from each of the long, live, dark photons, such that it looks roughly like this in here. I tried to
Richards Gonzalez: emphasize that for the color Gpj case, we are targeting a reconstruction on the Adronic calorimeter, while for the Muon Gpj case, we are basically looking at
Richards Gonzalez: neon Chambers information.
Richards Gonzalez: So
Richards Gonzalez: for and our signal Monte Carlo and future plants, we, we've simulated signals using the Macgraph buffer module.
Richards Gonzalez: We have a couple of signals for different Doctor Thomas, both
Richards Gonzalez: for a hundred and 1,000 events per sample.
Richards Gonzalez: What we're doing is we are generating the led files directly from that graph, and then handing this to PT. Plus Delphis, using the idea, Delphis card in order to have
Richards Gonzalez: a full generator lower and sample
Richards Gonzalez: so for the actual samples that we have. Now we have a a couple we have
Richards Gonzalez: a 1st sample of dark photo mass point one Gv. With a displacement of 1515 in this case. For this mass the branching ratio of the dark photon to well the dark photon decays all the time to electron positron
Richards Gonzalez: such that this sample allows us to focus on color Dpj signatures.
Richards Gonzalez: And then, once we are, the dark footing has a mass larger than 2 times the mass of the muon. The decay to Muons opens up
Richards Gonzalez: and based on our mass and seat out choice we can also be sensitive to new Dvj signatures.
Richards Gonzalez: In this case, our backgrounds.
Richards Gonzalez: We have several candidates. We'll have, like generals, inclusive select production, diversion production
Richards Gonzalez: and different samples that we are checking in the winter. 22, 3 campaign.
Richards Gonzalez: And here, if our future plans are a
Richards Gonzalez: in parallel, do some generator level studies such that we can look at Lh level kinematics and at the same time look at the Fcc analysis framework to study recovery level information.
Richards Gonzalez: This is quite important to us because we want to explore
Richards Gonzalez: low level detective response, particularly color cluster information and muon information, including the timing
Richards Gonzalez: and this is related to considerations that we have to have in mind regarding the displays that displace dark force and jet signatures.
Richards Gonzalez: sins
Richards Gonzalez: our reconstruction of the Calor Dpj, for example, is highly dependent on the level of simulation that we have from the calorimeters.
Richards Gonzalez: Here we think that, for example, the municip in jet final State is a safe option, since it's easier to reconstruct
Richards Gonzalez: we can either do it as collimated bones in narrow cone, or even consider the option of
Richards Gonzalez: Part of reconstructing resolved immunes with a simple vertex in.
Richards Gonzalez: and then tentatively, we could also explore Atlas like newer network taggers to distinguish this displaced color Dpjs from prompt Lepton jets.
Richards Gonzalez: Given that, and
Richards Gonzalez: we can work with that calorimeter simulation that we have now.
Richards Gonzalez: But this is the general idea. So that's the prospect for the search.
Richards Gonzalez: And this is what we're working right now. So that's it for me, at least, for now.
Richards Gonzalez: thanks.
Juliette Alimena: Okay, great thanks a lot for for this introduction to your at least your plans. But I think you've got things already. Well, underway with Seg simulating the signal
Juliette Alimena: questions.
Juliette Alimena: Farah.
Sarah Louise Williams: Hi, there! Thanks a lot. For that. It was a really nice talk, and this is really more a comment than a question, but
Sarah Louise Williams: I expect that you will be able to find the required backgrounds in the winter. 23 campaign, but I think we're probably we might end up hitting up against
Sarah Louise Williams: things we've seen in the other Llp. Samples about whether there's actually enough statistics. If you want to really look at the unconventional signatures.
Sarah Louise Williams: and yeah, if if there's anything that I can help with on that, I'm happy to chat further offline after.
Richards Gonzalez: Th. Thanks, sir, I think that's actually quite relevant from the experience that we got in Atlanta. Indeed! It's very hard to rely on Monte Carlo. Simulations for background prediction for this kind of signatures. We indeed did some data driven background estimation for our results in Atlas. So if
Richards Gonzalez: that's something that we'll keep in mind, and that's something that we could definitely chat about. So I really appreciate your comment.
Juliette Alimena: Yeah, indeed, Sarah's dealing a lot with the Monte Carlo, especially for the
Juliette Alimena: the Bsm. In general at Fcc.
Juliette Alimena: So, indeed, take advantage.
Richards Gonzalez: Yeah, yeah.
Juliette Alimena: Yeah.
Richards Gonzalez: Just just just just to make sure. I mean, maybe we don't have to.
Richards Gonzalez: It's just a quick question, let's say, but
Richards Gonzalez: would the option be in the case that we hit that wall? And we see that we don't have enough multicultural statistics to make a reliable prediction. The chance would be maybe to try to make a dedicated simulation, or
Richards Gonzalez: just to get a feel. Let's say.
Juliette Alimena: Yeah, I'd say, that's an option.
Sarah Louise Williams: Yeah, I think that there are probably a few things we could do. Sorry, Julia. I didn't mean to actually.
Juliette Alimena: No, no, no, please!
Sarah Louise Williams: I I guess the good thing is you're gonna look at your generator level stuff first, st so you can probably make at least some kind of back of the invite calculation
Sarah Louise Williams: of which selections are going to be useful from a signal perspective, and maybe look at the backgrounds there, and there might be ways to use this. You know, very early, but evolving filtering framework
Sarah Louise Williams: just to maybe just at least check if we get if we are getting background events in those
Sarah Louise Williams: areas of face base. Even if we have to filter and we don't necessarily get a reliable estimate.
Richards Gonzalez: Okay, perfect. I think that sounds great.
Richards Gonzalez: thanks.
micheleselvaggi: Good. All this being said that you have to be aware that most of the the the Delphis sample will not have
micheleselvaggi: course. The low level detector response information that you're looking for right.
Richards Gonzalez: Yeah, timing. But
Richards Gonzalez: yeah, exactly. I think that's why we that's why I've been trying to do, look at the analysis framework in parallel
Richards Gonzalez: given that that was one of the main things that we've
Richards Gonzalez: thought@firstst
Richards Gonzalez: given that, we need that kind of information for the kind of Dpj signatures. But
Richards Gonzalez: I think
Richards Gonzalez: what
Richards Gonzalez: something that I tried to express here as well is that even beyond a
Richards Gonzalez: the information that might be available at recoil level for the color Dpj signatures. We are fairly confident that we can
Richards Gonzalez: at least study the mudj signatures properly. Given that this,
Richards Gonzalez: It's considerably easier to to implement and to define the objects. And
Richards Gonzalez: I am
Richards Gonzalez: like that information. I believe that it's in it available. So
Richards Gonzalez: so we'll see? But at least we have a at least we have a a backup plan that's a a a reliable signature that we know that we could look at.
micheleselvaggi: Yeah, I mean, I guess the 1st the 1st step would be to understand how
micheleselvaggi: what sort of said, how many?
micheleselvaggi: At least displaced jet candy that you get from from Zdas, you know, from Taos and this kind of things already.
micheleselvaggi: The problem, the the real physics based one, and then
micheleselvaggi: then fakes are probably something you will have to study in full team, anyway.
micheleselvaggi: Yep.
Juliette Alimena: Yeah, onion.
Yanyan Gao: So I think the the full detector related the information. I think this might be a physics object level of study. So in principle, we don't need the dedicated processes, because one of the main thing is to understand what is the what is the rejection factor for a prompt yet. So in this case we can. We can have other samples, for example, even if some possibly single particle
Yanyan Gao: or just some inclusive quark cock production, so that we can just
Yanyan Gao: use that as a as an object level, and then we can make some, if that's possible, to find such samples. I think that would be good.
Yanyan Gao: So.
micheleselvaggi: It's definitely possible. It depends, then, how what kind of
micheleselvaggi: rejection
micheleselvaggi: efficiency you you expect, I mean, or you need.
micheleselvaggi: I think it's busy. It's definitely feasible to produce order.
micheleselvaggi: you know. 100 k. To a million full same Zatoc events. That's for sure.
Yanyan Gao: Yeah, exactly. So I think in principle, we don't we? Okay, yeah, perfect. i i i think we can also use use some of our information of the Atlas at least current objects, and get an understanding of of that. I think the level of rejection we're looking at, probably on
Yanyan Gao: 3 or 4 orders of magnitude at this stage. But if it's, you know, inclusive Z. To J in the core sample, we should be okay at that level.
Yanyan Gao: then a physics level of.
Yanyan Gao: of, let's, say, working point of efficiency versus rejection can then be used to to for the realistic backgrounds to extrapolate some
Yanyan Gao: guesstimate of the numbers, and that could be an option. If, for example, the ZHZ. Quad samples are limited by statistics.
Yanyan Gao: In that case.
Juliette Alimena: Other comments or questions.
Juliette Alimena: Maybe just
Juliette Alimena: 2 silly ones for for me. So indeed! If you need to find that that you want to do some simple displays vertex. I I can point you to to Magda and the other people at at Opsula. They've been working a a lot on displaced vertices, so they they could probably help.
Juliette Alimena: So if you need their contact, let me know.
Richards Gonzalez: Thanks. Thanks. I appreciate it.
Richards Gonzalez: That's the long lip scalar. Search right? Yeah.
Juliette Alimena: Yeah, these are the kings. One, yeah.
Juliette Alimena: So just ping me if you if you can't find their other emails.
Richards Gonzalez: Yeah. Thanks.
Juliette Alimena: And then, since you're you're ramping up now. Maybe it will be too too soon to to say that you'll have a final result for September, but maybe you can still be be included in the in, in, the.
Juliette Alimena: in the feasibility study, I mean the in the report with like a preliminary write up with, like, you know, hints of things that can be working that that can work without, you know, necessarily having a final result, but some some beginning. Whatever you have by then, maybe that would still maybe that can still be a goal to be it to be included by September.
Richards Gonzalez: Yeah, I think we are happy to just to still, trying to answer that.
Richards Gonzalez: but we are also happy to go go beyond the the report. Let's say.
Juliette Alimena: Absolutely. I I imagine that that would be the your plan.
Juliette Alimena: Sorry.
Richards Gonzalez: Exactly.
Juliette Alimena: So I just didn't want you to to to think. September. There's no way we can't do anything, but I'm thinking you might be able to do a little something, but.
Richards Gonzalez: Yeah, no, thanks. I I appreciate that.
Juliette Alimena: So each.
Juliette Alimena: okay, other comments or questions.
Juliette Alimena: Okay, I'm not hearing any. So thanks, Richards, and th thanks, Tom, and everyone for for connecting
Juliette Alimena: any other business before we close.
Juliette Alimena: Hmm! No meeting next week and I don't ha! I think I have anyone in in the plan for following week. So let me know if you want to give a presentation.
Sarah Louise Williams: Julia. Sorry just to ask you question about this. Maybe what we could do in a couple of weeks time. If there's energy for people to do. It is actually
Sarah Louise Williams: I guess, have a recap within our group about our possible to do lists in respect of what's presented at Scc. Week.
Juliette Alimena: Okay.
Sarah Louise Williams: Cause I don't know. Like, Are are you going.
Juliette Alimena: I'm not, unfortunately.
Sarah Louise Williams: Because I guess if we can find someone who is there who's been following these discussions.
micheleselvaggi: And the heat.
micheleselvaggi: And so.
Sarah Louise Williams: I don't know. Maybe Rebecca will go, or something.
micheleselvaggi: And below.
Sarah Louise Williams: Think that could be quite nice.
micheleselvaggi: Right? Because.
Sarah Louise Williams: Some of the some of the meeting is going on at like slightly antisocial times in this time zone. But discussing what we think we need to be thinking about ahead of the summer in lieu of that, could be quite good.
Juliette Alimena: Okay, yeah. Good idea. I think Louise is giving a talk on Bsm. At the Fcc. Next week, and she's in principle connected with with all of us, so maybe she can simply give that talk again. And that's maybe the starting point.
Sarah Louise Williams: Yeah, yeah, I mean, it's just a again, it can be a relatively open agenda item. But it might be that either follow ups or things that might be good for us to discuss.
Juliette Alimena: Okay, great, that's.
Sarah Louise Williams: Thank you.
Juliette Alimena: Thank you.
Juliette Alimena: Anything else.
Juliette Alimena: Okay, great
Juliette Alimena: thanks, everyone. And we'll see you next time. Have fun at Fcc Week. If you're going.
micheleselvaggi: Right, thanks.
Juliette Alimena: Hi! Thank you.