774-R-013: Oh, okay.
774-R-013: this is recording. It says recording. But
774-R-013: yeah, I think the webcast is press the button for zoom.
774-R-013: Oh, you suck it.
774-R-013: Okay.
774-R-013: I'm like 2 minus one and 20.
774-R-013: We need to introduce the introduction.
774-R-013: Yeah.
774-R-013: Well, welcome to the 25 edition of the Loomy days, the last one we said we had was in 2,019 at the end of 1, 2
774-R-013: and we've got a I hope hopefully, 2 and a half days of
774-R-013: of interesting and perhaps even, you know.
774-R-013: even angry discussions. I don't really mind, but we should. This is an opportunity we have to all work together. So I'll just summarize something which is in the indico. So the goal is just to review the progress since 2019, and in particular, over the 1st 3 years of run 3. In the determination based. Experiment of the absolute lac luminosity, measurement of relevant beam parameters, tunes, bunch populations, emittance evolutions, orbit drifts.
774-R-013: characterization and mitigation of accelerator and luminometer related systematic uncertainties. So the workshop will cover some 1, 2 results and some preliminary analysis of 1 3 data.
774-R-013: But the emphasis is really on identifying what studies and operational improvements that may prove useful in the upcoming last 2 years, or one and a half years of 1, 3 operations.
774-R-013: or also thinking a little bit ahead to what will perhaps contribute to achieving high accuracy, luminosity, determination. In the early days of run 4.
774-R-013: I want to 1st of all express thanks to the Organizing Committee listed here, and in particular my co-chair, we're told, who, of course, has done an immense amount both for this meeting and for Lh. University over the years.
774-R-013: Just the program overview.
774-R-013: Roughly speaking, this afternoon, we're going to be talking about the luminosity determinations in 1, 2, and 1, 3, the methodologies particular and associated uncertainties.
774-R-013: Tuesday. We're going to work on beam dynamics in the Vdm calibrations and then impact of accelerated instrumental issues on luminosity calibrations, and that will be both in the afternoon on Tuesday and and already and again on Wednesday morning. Then we move on to more experiment. Discussions of luminometer nonlinearities, integration, uncertainties.
774-R-013: and then we finalize, finish up with a
774-R-013: what can we do better in the remainder of run 3, and looking to run for
774-R-013: so in the indico, the times that have been allocated for each talk are the times we? We would like the presentation to sit in fit into. So in addition, time clearly not enough. But life is short, we have to fit as much as we can. This is typically a 10 min discussion time, not after this talk
774-R-013: before the next scheduled contribution. Okay, the program is very full. So please do your best to respect to the constraints, and we'll ask the conveners. And in fact, it's Eric is our convener for this 1st session this afternoon to be kind and brutal, and to make certain that
774-R-013: that we've managed to respect that timing, we, of course, there will undoubtedly be some topics that we will not be able to cover in the 10 min of the discussion. And so we will. I think, all of us, all those will take note of those things which are open topics that need that we need to come back to. Perhaps in some special meetings or status of future discussion.
774-R-013: I
774-R-013: there's a coffee and a tea break morning and afternoon, 1030 and 3, 30, just outside the meeting room here. And it's catered by the the staff of this the building. 7, 7, 4.
774-R-013: But could you please make a point of thanking your experiments, and I'll be up for covering the expenses of the morning and afternoon break, so that enables us to do this meeting without, you know, complications of registration, fees and etc. So thank you very much.
774-R-013: To the experiments and and to and indeed to the Operations group here.
774-R-013: There's a webcast it's on now. There's a live webcast for the event. All presentations will be recorded. All speakers have a have agreed to that. So thank you very much.
774-R-013: And then very kindly, 3 of our colleagues, Mickey, Richard, and Gabby.
774-R-013: have kindly agreed to to try to summarize our next week in the special Llcmw. Meeting at at 4 o'clock. It would as noted here. There's a it's linked
774-R-013: in the timetable of this meeting.
774-R-013: It's a special to try to basically pull together their ideas of the key takeaways and the and the action plans that we should be discussing, probably in future meetings, or or some of them may be obvious, some not.
774-R-013: and that brings me to the end.
774-R-013: And so I will go back to the agenda for the day.
774-R-013: and so in this immediate session, I'm going to turn it over now to Eric. We have a talk from from Atlas, from Brian, and a talk of Cms from from Gabby, and then
774-R-013: a coffee break where we can hopefully get to know those of us who don't, who there are people in here that are perhaps new to each of us. There's an opportunity to to to get acquainted.
774-R-013: Okay, thank you very much indeed.
774-R-013: I turn the over to Eric. We do have time for a quick question for David. If anybody only if it's about coffee or tea. Do thank your experiments, though, because it was not obvious this was going to work out. No, it wasn't. We're very appreciative. Yeah, we could spend millions. But it did help you get coffee. Okay?
774-R-013: Right?
774-R-013: That's the wrong thing. That's the right thing.
774-R-013: So if you want to use this, yes, okay, okay, all right. Great. So I'm going to summarize the way Atlas measures luminosity. But since I'm the 1st speaker, I feel like I am obligated to tell you something, you know, which is basically why we why we're here. Right? So basically, what we want to do is turn thing. Well, basically, this is an event display from Atlas of the HDD. Bar, and we want to turn measurements of events
774-R-013: into results that are, let's say, cross sections right? And we all know that a crucial step in any cross section measurement is to take
774-R-013: well a measurement of a number of events which is actually extremely complicated in the experiments, but not the topic of this workshop, and basically divide by an integral luminosity and precision. Measurements require precision, luminosities.
774-R-013: So just to kind of follow that up these are 2 recent measurements by Atlas, one basically of vector boson production, another one over here of top production, right? Where, if you look closely, the luminosity uncertainties are actually not negligible. They make a significant contribution to the systematic uncertainty, and without the dedicated efforts from the Lhc. The detectors, the luminosity
774-R-013: groups, etc. The luminosity could have limited the precision of these measurements, and I should just note that in fact, there are measurements, especially back in Run one and 2 where the luminosity actually does limit the precision.
774-R-013: So that's why we're here. All right. So let's talk about atlas luminosity measurements. The primary luminosity measurement in atlas is provided by lucid.
774-R-013: Okay, so this is a picture of the lucid detector. You'll see more about this as I go on. It's the only detector and atlas that essentially provides bunch by bunch luminosity. Essentially 100% of the time right and can be vdm calibrated, that is, except for 0 degree calorimeters, but not 100% of the time, because we only use those during heavy ion operation.
774-R-013: We also use calorimeters for luminosity, but that basically comes from the currents, and these only provide bunch integrated luminosities. They're typically only useful at high mu, except there are some cells kind of in a special part of the calorimeter that actually are sensitive even at lower mu.
774-R-013: The problem is those cells and the tile in general is sensitive to activation. So correction for that is essential, and you'll hear about that from Julia.
774-R-013: The inner detector is also crucial. For Atlas we basically do luminosity via track counting. And this is a critical step, if you will, in our sort of ladder that takes raw data measured from lucid and turns it into precision luminosities. One of the problems with using the inner detector is, we're limited by the bandwidth of
774-R-013: the data. How many events we can write. So we can't do it for all bcids right. And so that's a limitation. But you'll see that the tracker is crucial.
774-R-013: So let's come back to lucid. Here's a picture of basically lucid where it sits in the beam pipe, and then this is a closer look. Inside the outer part of the beam pipe you can actually see the detector. It detects, charged particles that are essentially beta greater than 0 point 7. Passing through the window of the photo tube and producing Cherenkov light, there are bismuth sources essentially on the window itself. That means that we can continually calibrate the detector, and
774-R-013: Julia will say more about the details of that.
774-R-013: The symmetric placement of the Pmts in lucid is actually important to reduce sensitivity to, for example, crossing angle that matters because we calibrate at 0 crossing. But the physics is not.
774-R-013: It also has built in redundancy. So essentially, each side of lucid has 4 groups of Pmts.
774-R-013: And essentially each of these 4, like each set of 4, really could be 4 independent detectors in the end. We only have electronics to run 2 of them at a time. So we essentially have 2 completely functioning independent systems that we actually treat as if they're different detectors on both sides. So basically, one color of the Pmt
774-R-013: right on each side represents one right? And then 2 of those we typically use are like Bi one and Bi 2, we also have essentially because they're there a plug ready backup system.
774-R-013: So with lucid. There are a number of algorithms that we can use to essentially turn particles passing through the Pmts into luminosity measurements. So we could do event, or which is basically a hit above threshold in any Pmt. Or on one side. So we could do event A or event C, or we can count hits on all Pmts, so that's a hit. Or or we could basically count hits in single Pmts.
774-R-013: Now at High Mu, the event or algorithm saturate and there's really no choice except to either use the hit or right counting hits, or to use a single Pmt.
774-R-013: Now, in run 2, we used a mixture. So if you, this is a summary from the Atlas, run 2 paper right, depending on the year in 2016 and 17 we used the hit, or
774-R-013: in other 2 years we use single Pmt. And those were for some specific reasons that had to do with the functioning of the detector. There were different reasons. And they've since been addressed. Such in Run 3, we basically are always using well, so far, we've always used the hit org.
774-R-013: Okay. Now, an important part of the lucid performance is that it actually has some sensitivity to bunch spacing trains, and it exhibits nonlinearities at high mu at about the 10% level.
774-R-013: Okay, you'll hear more sort of about the relevant relevant issues. In Vincent's talk on the lucid upgrade.
774-R-013: Okay, so how do we go about basically measuring and calibrating the luminosity. So lucid provides the lumisity, the main luminosity measurement. We calibrate it in Bdm scans and in fact, we have dedicated scans not surprisingly to control length, scale uncertainties and non-factorization.
774-R-013: Then we basically use track counting to calibrate the mu dependence of lucid. The tracks are anchored in physics fields near the Vdm scans, and then we use the tile, the part of the tile that I pointed out, which is sensitive right to essentially validate the what we get from the tracks. And then we use the rest of the calorimeter at high mu to basically evaluate long term stability.
774-R-013: Okay, just about the tracking, because it's, you know, an important part of what we're doing. Julie will say much more. This is basically a set of results using z mu mu tag and probe evaluation of the tracking efficiency. So there are different track selection criteria here. The one that we use in the luminosity measurement happens to be that one
774-R-013: and A, it's very high efficiency. And B, it's very stable. Okay, so this is why we can essentially use tracks to to correct lucid
774-R-013: and much more in Julia's talk.
774-R-013: Okay, let's talk about the calibration strategy from kind of the operational point of view. So basically, in Atlas's calibration scheme, when we have, you know what we call a set of Vdm scans
774-R-013: in addition to setup, and we do a crossing angle scan to measure our sensitivity to the crossing angle. Then we have the real Vdm program. And, as you know, this has special optics, indivs, 0 crossing and tailored injection.
774-R-013: We do dedicated scans to control non-factorization. And while Cms is taking data, we actually take head-on data for doing various anchorings of the calorimeter and the tracks with respect to lucid. And then we have all important length scale calibration.
774-R-013: Then we, we basically do 2 other sets of scans right to understand the mu dependence of all the various luminosity measurements we have. And we do that at essentially, you know the the Vdm optics and number of bunches. And then we do it essentially with physics, optics and the full machine effectively.
774-R-013: Okay, so that's the whole program for typical year. This is, in fact, taken from 2023. Now, what about the Vdm part itself? What does our program look like from the perspective of the beam positions? So this is just a plot of the Dcs data of the beam positions, using to to basically show what we do. And I'll annotate it.
774-R-013: So in 2023, we had 4 on Axis Xy scan pairs. That was the main Vdm measurement. We took 2 off axis scans. So I'll comment on this later. Basically, to measure non-factorization. We had a 2D grid scan. Also for non-factorization.
774-R-013: Okay, in 2024, we did things slightly differently. We divided our program into 2 halves. Each one had a pair of Xy scans, maybe, plus one for the 1st and a 2D scan. So the 1st half of the program looked as follows, there's 3 xy scans.
774-R-013: There's a 2D grid scan. But we did something interesting. In 2024 we had an Xy scan that was actually part of our 2D grid scan. And this was to give us control over the emittance variations and orbit drift.
774-R-013: Then in the second part, we basically did 2 xy scans, and we did a sequence of 3 diagonal scan pairs. And I'll say more about this later.
774-R-013: Okay? Then, for the length scale calibration, it's fairly typical. Right? You basically scan the beams one at a time, right? And do measurements at each point. You essentially determine where the beams are positioned. Using data from the tracker
774-R-013: did the usual, except that in 2024, because of the diagonal scans, the beans move backwards, and why we did an extra pair of scans essentially in the backwards direction in the yeah for the vertical motion.
774-R-013: Okay, so let's talk about the grid scans, because those are something that you know is relatively new. And you know we've done something interesting with. So
774-R-013: in 2022, and 23, we did similar scans. There's some subtle differences, but they're mostly similar. And in fact, these lines you can see essentially the motion of the beams right
774-R-013: in 2024. As I said, what we did something new is, we actually had an Xy scan that occurred as part of the grid scan. In both of these cases we did 2D scans over plus or minus 4 sigma, with an extension at x equals 0, and y is equal to 0. But we think that this protocol is better because of that Xy pair.
774-R-013: Now in 2024, we did something interesting. At Vtold's instigation we took diagonal scans, so 1st we did a grid scan. Then we did this sequence of diagonal scans with UV pairs at different angles. So each essentially we did 3 scans, each at 90 degrees with respect to each other, but at a set of angles 45 degrees and plus or minus
774-R-013: 25 degrees. And this was motivated because with each scan pair they're like an Xy pair, we can actually better control orbit drift.
774-R-013: You can actually analyze them like their xy pairs and compare the resulting cap. Sigma values. But you can also combine them into 2D fits, and we sampled out to 6 sigma rather than the plus or minus 4 sigma. That's for the grid scans.
774-R-013: We are still learning how to use these. So we don't really have results to show this time around. So let's talk about the Vdm calibration. So I have a can. I click, maybe I'll do it. Yeah, let's
774-R-013: is it going to work? No, come on.
774-R-013: maybe you have to click on the frame itself. Yeah, that's let me try.
774-R-013: Nope.
774-R-013: you know that's too bad. I'll do it when I'm done. I made a nice little simulation, but something I've been meaning to do for a decade of what vdm scans look like. So we scan the beams past each other
774-R-013: the overlap jeez, actually, yeah, yeah, let's see, let's do it like this.
774-R-013: No, no, it will.
774-R-013: No, but I'll do it from here. This is what we do right? So you get a nice visual picture of us sweeping the beams past each other, and you see the intense, essentially the luminosity right is shown with the purple on the left hand side. But then we measure, you know the integral over the the transverse.
774-R-013: Yeah, the transverse luminosity on the right. And so essentially, the the pattern on the right is, you know, measuring some rate. Well, we'll discuss that in the next slide as a function of position. And from here we measure the emittance which then allows us to basically
774-R-013: do the full calibration. All right. So back to my talk.
774-R-013: And where was the full screen? Eric? Yes.
774-R-013: okay. Oh, yeah. Well, that's a sorry about that. But
774-R-013: I'll go quickly back to where I was. So while I'm doing this, so basically, we do this procedure right? And what we measure, what we want to measure is effectively the shape of the overlap as a function of beam separation. You can write that, you know, in terms of basically the the Mu.
774-R-013: the mu that we well, here it is. I don't need to talk right. So we want to measure this overlap, which has information about the width of the beams in terms of the cap. Sig. X, and the cap. Sigma y. What we actually measure is this, mu, viz.
774-R-013: Right? So we measure this thing except that really, we're not interested in having the n 1 and N. 2 here because a, they're not really, you know anything about the shape of the beam, and they can vary with time. So what we actually do is measure this specific rate where we divide by n. 1 and n, 2, right? And then, if there's more equations, right, it's almost the same. That's on the previous slide. Except this is actually how we get sigma. Vis.
774-R-013: okay, so this is what it looks like. Here's a Xy scan pair from run 2. However, one should note, these are different years, but this is the horizontal scan. This is a vertical scan. Again, these are data from actually different years. We use Vcid minus one to measure the bismuth noise and afterglow rates. In fact, with lucid. Currently, we hardly see any afterglow. It's mostly just the noise from the bismuth.
774-R-013: We also use unpaired bunches to measure the beam gas rates, although in full luminosity. PP, those are basically negligbly small. That's what that says. We subtract both backgrounds using probabilities correctly.
774-R-013: And if you look hard, you can actually see points down here which are the subtracted data. Really, the subtraction only has an impact in the last few points in PP operation. Then we fit the scan curves to extract the cap sigma X and y. In Atlas the most common is, we use a Gaussian times, an nth order polynomial
774-R-013: right, but in run 2, we actually had to add an extra Gaussian in the middle because of features in the shape of the profiles. We're typically not doing that in run 3.
774-R-013: Okay, so this is now a set of profiles from the same year, from the same bunch, even in Run 3, it's basically the same. But in run 3. We're mostly using Gaussian times. 6 order polynomials.
774-R-013: Now, over the years, Atlas has primarily relied on 2 factorized functions. Right? A double Gaussian right? Where you basically have 2 different Gaussians with essentially appropriately fractions or a Gaussian times. Polynomial right? So basically take a Gaussian and multiply it by one plus a set of polynomial terms. The odd terms
774-R-013: you can include or not depending on what you're trying to do, but they don't contribute to the Cap Sigma X. In fact, this is the expression for the cap sigma in terms of the polynomial coefficients. There are some details that are important. When you do the double Gaussian. You have to avoid degeneracy when we do the Gaussian times polynomial, we actually fit Cap Sigma, and then extract the little Sigma right for the Gaussian out of it. But these are details.
774-R-013: Okay? Now, there are 2 ways to perform. The factorized Vdm analyses the traditional one. Is you fit the horizontal and vertical scan separately. Right? Then you do you know the typical correction to combine them to get sigma vis you have to correct for offsets of the beams in the 2 directions, and you can include the in-plane orbit drift in the fits. But you have to correct, for out of plane drift
774-R-013: another procedure is to fit simultaneous the horizontal and vertical scan data. With one function it could be factorized, but still a single function.
774-R-013: Then, when you do that, there's no need to correct for offsets, and the orbit drift is included
774-R-013: in the part of the fit. No corrections are needed.
774-R-013: So over the years the Atlas proton-proton calibrations have typically used the 1st method. The heavy Ion calibrations have used the second mostly because of the people doing the calibration.
774-R-013: Okay. Now, some example results from 2023. I'm going to highlight these for you. So these are the Cap Sigma on the left X, and on the right Y results
774-R-013: superimposed from 4 scans as a function of bunch. Right? So that's going vertically right? And you can see that, you know, there's some scatter right? There's actually quite a bit of scatter in 2023. But this is not atypical. You also see right? If you look at the R specific right, the mu divided by n. 1 n. 2. You also get some scatter, but, as usual, you get a much
774-R-013: tighter distribution in the visible Cross section, though there are some outliers. And I will come back to this.
774-R-013: Okay, now, one important thing in the Vdm analysis is a bunch charge product. This is, we analyze in a sort of typical way, right measure the total charge using the Dcct we measure the charge fractions using the Fbct. But use the Pptx for systematics. You have to correct the Fbct for satellites that's typically small in the PP measurements.
774-R-013: the Dcct needs to be corrected for ghost charge. This is also typical right? So you get expressions here for the the charge for given bunch right? In terms of the above. We also correct these fractions for nonlinearities. I'm not going to discuss the formulas here. These are usual.
774-R-013: Okay? So what about uncertainties in the Vdm right? Well, they come in many origins. There's orbit drifts, right? Undesired movements of the beams. Right beam beam effects both deflection and distortion on the opposing bunches. There's possible, you know, emittance evolution effects, especially if the emittance evolves differently for the 2 beams. One has to control the length scale. And
774-R-013: more recently, we understood magnetic nonlinearities. Right? And oh, yeah, non-factorization, right? The fact that
774-R-013: you know, the bunches really aren't necessarily factorizable in their description. Right? We've seen significant non-factorization in Run 3, and this has been a substantial part of our effort in Run 3 is to basically control non-factorization.
774-R-013: So a little bit about some of these beam beam effects, these are pretty well understood. There are some pocket formulas to describe essentially the deflection as a puncture, as a function of separation. Though we don't use these pocket formulas, we use exact results. But you just correct, for what you know is the deflection, and put that into your when you do the fit, you put that into where we say each measurement is made.
774-R-013: the beam beam distortions are more involved. These actually have required quite a lot of work doing detailed simulations. We account for distortions with essentially a Delta X or Delta y dependent correction to the luminosity of the shape that is here. And this is the subject of a whole paper. Just a year ago or so, so we correct the mu visible point by point, and this has now become essentially standard
774-R-013: length scale. You'll hear much more about Richard, about from Richard, but I will say that this is, you know, one set of length scale data from 2017, when we were doing 5 point scans, and it looks pretty good, right? If you look on the right hand side, our control of the length scale is at the level of a few tenths of a percent. However, there are systematic residuals. And we especially saw those systematic residuals in the 900 Gev data. And well, Richard will tell you a lot more about this.
774-R-013: Okay, what about non-factorization? Well, this is, as I said, been the subject of a lot of work. How do we evaluate non factorization in atlas. Well, we do off axis vdm scans.
774-R-013: We have something called the luminous region Analysis. You will hear much more about this from Tim. Then these new well, the grid scans which we've done for a while and diagonal scans. So this is our result on non-factorization from Run 2, right? That's in our paper. We actually had in run 2 non-factorization at the level of a few tenths of a percent. Right? This is the basically the non-factorization factor R, which corrects the visible cross section as so
774-R-013: well, what about run 3. So this is basically taking data in run 3, plotting the cap, Sigma X and Y as a function of time. Right? Nominally, this is the emittance evolution. But, in fact, what we show is that these points here that are highlighted. In fact, I'm going to highlight more. Right? These are our off axis scans, and they are way off from the trends, both
774-R-013: in 22, right and 23 more. So in 22. And this is manifest non-factorization.
774-R-013: Okay.
774-R-013: the luminous region analysis provides a way to basically do this with some real precision. Tim will tell you a lot more about it. But in summary, we basically take tracking data recorded for a small number of bunches, we measure the distribution of vertex positions for actual collisions. We model essentially the single bunch density profile
774-R-013: right? And then convolve that to simulate what we would see in both the Vdm right and in the vertex distribution and perform a fit to both sets of data.
774-R-013: So a summary of what you can get out of this, for example, is a measurement of the luminous width right of the vertex distribution in different directions.
774-R-013: This is a plot of that luminous width
774-R-013: in the X direction. So the width in X, the width in Y versus the beam separation in X. Now, to understand these right, the fact that the width in X varies as a function of separation just tells you that the beams aren't Gaussian.
774-R-013: but this is the variation in the Y width as a function of X separation. And once again, this is manifest non-factorization.
774-R-013: Okay? So we use a grid scans to control non-factorization. So, for example, we can do fits to a Gaussian times. 6th order, polynomial. But where we put in explicit factorization breaking terms.
774-R-013: So we take the data, we do a fit. These are the polls that you get as a function of X and y from this fit. So this is data from 2023. They're basically all around one or less. So it means that the fits work. But there's an important detail you'll have to hear about from Tim's talk. Nonetheless, we can take the grid, scan data and correct
774-R-013: the Xy results that we get bunch by bunch. So we take the results from this. The grid scan apply them bunch by bunch. And this is what happens. So this is a plot I showed you before with the outliers. If we correct them. We don't have this plot corrected, but we have this one which shows the distribution of the Sigma vis values. And when we correct all these guys out here on the tails.
774-R-013: whoops, all those guys basically go away. Which means that the non-factorization was contributing significantly to the bunch to bunch variations. And so we see better bunch to bunch agreement after we correct.
774-R-013: Okay, Tim will show you. This is gives you kind of the sense of the scale for the typical non factorization effects we're seeing in run 3. So this is basically corrected data. This is uncorrected, and the same thing on the right, you'll hear much more about it. This is a few percent effects in basically 2023.
774-R-013: So I'm going to quickly discuss calibration transfer because Julia's going to say much more about it. So I told you that the lucid measurement has basically a nonlinearity. Well, you can see it directly. If you take a long fill where the mu varies over a factor of 3 range, and compare, for example, the track counting to lucid. You can also compare the track
774-R-013: counting to the calorimeters. But if you compare track counting to lucid as a function of the mu, you see this variation?
774-R-013: Right? That's the nonlinearity. Oh, and, by the way, the the track and calorimeter is actually there in very good agreement.
774-R-013: So you see, this linear variation you can correct for it, and then apply the correction, which is what we do. This is the same thing, basically now done a little bit differently. This is basically using 10 runs around the Vdm scan to compare the tracks to lucid. And once again, we can determine essentially the slope of the correction.
774-R-013: Okay, Julie will tell you much more about this.
774-R-013: We can then use the calorimeters to evaluate long-term stability. So these are plots from the different years in run 2, comparing essentially the calorimeters to our lucid measurements again. Julia's going to talk more about this, so I'm just going to say, you know, we have now all the tools to put systematics on both our control over the luminosity scale, taking into account the lucid nonlinearity, correcting for it, and then also checking our stability.
774-R-013: So I'm going to skip this and go to systematic summaries. So this is a summary of our systematic uncertainties from Run 2. So I'm going to annotate this. The Vdm contribution is basically all these here, I'm not going to go through each one. And basically we are getting typically less than a percent or about a percent systematic, just from the Vdm part itself.
774-R-013: And then the total uncertainty is down here. It's slightly higher.
774-R-013: By the way, we have a procedure for working out the set of correlations between the different years, such and taking into account the covariance matrix, such that well, here it is. This is the result for the combination in Run 2,
774-R-013: then these are the results from run 3. So far the preliminary results. I'm not going to go through each of the numbers. But I'll highlight non-factorization. I put the arrows where the non-factorization numbers are in 22 and 23. You know they are significant right? They're a large contribution
774-R-013: calibration transfer, essentially all of the correcting for the mu dependence in lucid and making sure that we have control over that in run 3 right now is also at the level of sort of a percent or so. We expect both of these to improve significantly.
774-R-013: All right, then a few comments on, you know, open problems and things to work on. Factorization is very much a work in progress. We're still figuring out how to do the diagonal scans. We're working on some of the systematics in the grid scan. And I would say, we've only started scratching the surface of the non factorization. Md data which is really interesting. Actually.
774-R-013: Tom.
774-R-013: we're doing some work on the Vdm fit models. We use the Gaussian times polynomial, due to the distortions in the profile that actually are occurring here, not only in the tail.
774-R-013: in fact, we see hints of repeatable, and this meaning in 23, in 24, and in the lead lead data.
774-R-013: Okay, I'm done in one more slide, right? So we see repeatable effects kind of on the shoulder of the profiles where the distortion evolves systematically as a function of scan. Right? It seems to be, yeah, a function of time in the fill. So this is probably a topic for future. Llcmwg.
774-R-013: We're discussing whether, in fact, we can use orthogonal polynomials. In the Gaussian times polynomial. There are some subtleties there but this is a work in progress. The magnetic nonlinearity had not yet been included in our Vdm analysis until recently. And that's it. So basically I will. I'm going backwards
774-R-013: I will leave you with this summary of our system. X
774-R-013: okay, so we have a significant time here for some questions and discussion let's start in the room. Do we have a question or a topic
774-R-013: for discussion?
774-R-013: Yes, let me hand you the microphone.
774-R-013: I think, for the talk. Yeah, very impressive. I have 2 questions, actually, one about the tracking. So did you think about segmenting your luminometer? So not count the total number of terms, but maybe in some regions, for example, in eta and rapidity, or maybe in
774-R-013: well, I mean, we already restrict the tracking to regions in Ada that are well controlled. we. I don't believe but you can maybe say more. I don't believe we've actually, you know, tried to independently do track counting in different parts. And actually, you know. Do a I mean.
774-R-013: do a really systematic setting, as in like, you know, at the level of something that I've shown you here? I guess we don't really see a reason to do it. But maybe Julie will say more.
774-R-013: Yeah, thanks. It's a good point. So we have actually done several studies to optimize the tracking selection for the luminosity measurement. And we end up using the central region where we keep control over the fake tracks.
774-R-013: So there have been systematic studies of different working points, and we end up choosing the one that gives us the best trade-off between a nice flat efficiency and as little fake tracks as possible. So I don't think we've actually, you know, attempted to do independent measurements with tracks, you know, by dividing the detector up.
774-R-013: and sorry I had a second question, maybe, whether your luminous you can be verified with.
774-R-013: We all have sufficient.
774-R-013: I meant to put a slide on, and then I somehow just forgot. We we definitely, you know, it's it's a part of what we do. It, you know. It's
774-R-013: it's a whole talk on its own right. But of course the Zw. Is a crucial element of understanding our luminosity. This, I think, is particularly a point, for it's about the only place we can compare between years and really make a nice cross check that the calibrations we get per year are all consistent with each other. So that's currently how we're kind of planning on using
774-R-013: that data, and it will show up as part of one of the talks later in the session or not. In later in the workshop?
774-R-013: Other questions.
774-R-013: Okay? So so one of the big differences between the Cms and Atlas approach, we'll hear of it is in the use of Cms's use of multiple luminometers and and yours. So one of the things I would like to call the calibration transfer has exactly the same
774-R-013: uncertainty to 2 decimal places every year.
774-R-013: How does where does that come from?
774-R-013: You mean the actual correction? Well, you and the uncertainty? You put 0 point 5 for everyone. I mean, it's that just comes out from the let's see the here. Right? Yeah. I mean, that just comes out of the the analysis, right? And I assume that there's some rounding. Right? Yeah.
774-R-013: go ahead, Richard. So this number is by construction the same for every year in run 2. We did a variety of studies in the different years with different luminosities, and so on, and we concluded that
774-R-013: this was the best number we could search for all years, taking into account all of the data. So it's it's not a coincidence. It's more that we set a blanket number for all the years since the track counting algorithm we use is basically the same in all the years. Right? And it's fully correlated between years in in run 3 right? Of course, that's not the same. Right? Yeah, it's not so. Yeah.
774-R-013: yes, yeah, yeah, right? You know, it's in the end it could happen right? That you know, to push the system, Max, down. We do the same thing around 3, but we're not there yet.
774-R-013: Okay? Question for Mickey.
774-R-013: Yes, maybe we can also see after also Cms presents. But what actually, I think it's very interesting for this non-factorization is that there seems to be strongly bunch by strong differences, bunch by bunch in the factorizability, which is, I think, an interesting observation. I would be very curious if Cms saw the same once they present. Thanks a lot.
774-R-013: Yeah. So not not only is it bunch by bunch, but that you know the patterns
774-R-013: persists between different sets of scans, but evolves with time in a sort of a very regular way. So we typically find that the non-factorization goes down
774-R-013: the further into a fill. You are. But you see, the same problematic if you will. Bunches right, you know. Persist the whole way.
774-R-013: Are there any questions on Zoom? Can't see zoom okay.
774-R-013: Anything else from the room? Yes.
774-R-013: people should raise a hand if they if they want zoom
774-R-013: you show also on the lucid calibration transfer comparison between the tracker and colorimeter. Yes, and from Cms. We saw that there is a big correction for the afterglow for both of the systems.
774-R-013: So could you elaborate a little bit on this corrections of afterglow for both of them. Well, we don't. We don't really have a significant correction in the tracker, right? I mean, our tracking requirements are such that we don't get tracks from, you know other crossings, if you will, so there's no afterglow in the or do you want to comment on this?
774-R-013: You have to keep in mind that the calorimeter measurement is not a bunch by bunch measurement. It measures for the hadron calorimeter is a current in the photo multipliers using an integrator, and for the liquid Argon it is a current in the liquid Argon gap measured by the power supply. So this is any afterglow is integrated, and the way the calorimeters are calibrated is that by forcing them
774-R-013: to agree in one run, or in a small set of runs with the track counting. So given that at fixed bunch pattern the afterglow is proportional to the luminosity. It would change if the bunch pattern changed to that fixed bunch pattern, which is the case for most of the physics running the afterglow is proportional to the luminosity, so that is absorbed in the cross calibration.
774-R-013: But but there's no afterglow in the track coming right in the that's correct. There's no afterglow, and there's no background, either. Get tracks in the in the of images.
774-R-013: Other questions.
774-R-013: Okay?
774-R-013: If not, thank you, Brian. We'll move to Cms. Gabby.
774-R-013: So we have a mic here. If you don't go too far either way.
774-R-013: If you cannot hear me.
774-R-013: So
774-R-013: okay, so I will walk you through a very brief introduction, as Ryan gave very detailed on, and then I will go 1st into the details of absolute calibration, then talk a bit about our monitoring strategy for luminosity and then go to the final integration systematics. And
774-R-013: okay, so I can skip this slide because we have all learned how to do luminosity measurements. And this is exactly the same strategy for all of us in Cms.
774-R-013: But I will introduce a little bit of our luminometers. The big difference between arpas and cms is that we have 6 independently calibratable aluminometers in cms. We have 2 dedicated luminometers, the pixel luminosity telescope, which counts threefold coincidences in pixel planes
774-R-013: we have the beam condition monitor with a fast 3 dot which counts hits on silicon pads. For that we have 2 different 3 dots, one with a simple threshold risk illumination, and the other one doing the differential peak finder.
774-R-013: And then we have the hardroom forward calorimeter, which is also real time. And we have 2 different counting methods, one basically counting heats, towers in the calorimeter which we call the occupancy method, Hfo. C. And then the other one is counting the sum of transverse energy. Both were for 2 rings of the Hf.
774-R-013: Then we have the pixel tracker, which provides an offline luminosity measurement by having the pixel clusters count
774-R-013: after that we have 2 orbit integrated so-called reference systems which are very stable and linear. This is the new tubes where we call the level one trigger primitives, and then airfield gas ionization chambers, which is part of the Lhc instrumentation. This is basically providing on the end of it.
774-R-013: and these then give us simple measurements which we can compare to each other.
774-R-013: You have already seen how the Vdm procedure works, but I would like highlight here, so, in order to derive the cap, sigma, we do as Atlas does, an analytic fit to the measured rate as a function of separation. Originally we used the double Gaussian functions, however.
774-R-013: for the final round 2 results. We found that symmetric, polynomial, modulated Gaussian, that we use a force over polynomial gives a better description. And actually, for our 2034 data. A. Q. Gaussian seems to give the best description of the standard. So this is a slight change from our
774-R-013: or the Bobby Gaussian fields now to set the stage for the different uncertainties I have compiled here all of the Cms measurements since the last days. In 2019 you have seen a few years ago. We have published the 2,015 to 16 final luminous decalibration
774-R-013: with uncertainties around 1.2 1.6% in total, we have to recent results for run 3 very nice uncertainty of 1.3 1.4%, and then these are more. The heavy I/O related results for the reference. PP. Run at 5 tb. And then the heavy Ios. Now, what I would like to highlight here the ones in
774-R-013: in board are the uncertainties where significant change happened in the methodology since the last many days, and then you see in board the uncertainties that are actually the dominant ones, and a few stands out. One of them is the residual orbit drift.
774-R-013: where we had a lot of improvements in recent years. I will discuss that landscape calibration also at some respect. And the factorization biases. We have already heard from Brian. That's very important.
774-R-013: and we have something unique. We can check the consistency of our Bbm calibration because of the many. Now let's go to the different components of the absolute calibration. The 1st one is how we take care of the low collision background before the window fits.
774-R-013: and since 2,018, we perform a super separation scan that in both directions we separate the beams to 5 sigma. So basically no collisions. And here we can measure the rate either on average or the bunch cross.
774-R-013: These can be cross-checked and are cross-checked, either with measurements that we perform in the upward gap, or looking at the 1st and the last Evm point, which is at 6 sigma separation for heavy ion collisions. There is also one thing that we have done on several occasions where the afterglow is more important, and here we have an option to take the measurement of the rain in the last bunch crossing
774-R-013: before the colliding budge crossing as the estimate of our non collision background. You can see here a plot from one of the heavy Ion measurements. But even in the Vdm scan field you can see, actually the afterglow.
774-R-013: Okay, so next one is the bunch current calibration. And here we do the same thing. I think that Atlas and I will not go into detail. But you will hear more about it, because this
774-R-013: is an important component for the heavy Ion calibration. But for Tp, this is a subdominant effect. So because of the time I will go next. Now for the beam interaction we have implemented in our framework the Llcnwg recommendations, of course, so we follow the prescription also how to estimate the uncertainty
774-R-013: and the most sizable uncertainties comes from the knowledge of the tunes and the non-gaussian pairs that we study for for each case. One thing to note here is that
774-R-013: parameterization of the off-axis scans is available for the bin beam. What we do for our luminous region method is that we run this study and actually get the beam beam effect, and we apply a correction on the bunch reads in our feeds and take this into properly account, and Peter will tell you much more about this in his talk. Tomorrow.
774-R-013: Now I will spend a few slides on the order drift correction
774-R-013: which, of course, affects our cap, sigma measurement. And what turns out is that we can
774-R-013: consider it as 3 different components. So we have a slow kind of linear drift which we estimate from the head-on measurement points of the beam position monitors before and after the steps.
774-R-013: Then there is a contribution from the wind beam deflection which you can actually see on these. These are the measurements in 2024 by the arc and the Doros Bpms, you can see the linear orbit drift, and then you can see the point by point measurements in each scale, and you see these very typical shapes from the wind beam deflection
774-R-013: now, because being in deflection only affects colliding branches. We have a dilution factor in our determination, which we call a scale factor for the
774-R-013: okay. Now, the 3rd component is a residual orbit drift that could come from magnetic nonlinearities. But they can actually come also from jumps and jitters in the beam, because if you do measurements and you compare. This is a Doros and arc comparison in one of our length scale measurements. Every point belongs to one second of VPN data, and you can see that there are correlated movements.
774-R-013: and therefore this means that you can actually have some residual already.
774-R-013: and we decided to correct for that. And let me show you how we do this. So in order to get this residual orbit drift, we perform simultaneous fit in the 2 planes in the scanning plane and the stationary plane that we correct 1st for linear orbit drift.
774-R-013: then we have a length scale between the beam position monitor that we use and the nominal beam position. We have this dilution or scale factor for the beam beam effect for the beam beam deflection.
774-R-013: And we also have a kind of a coupling. For example, if there's a misalignment between the measured and the nominar claims this gamma factor that appears in our fits, and then we have a scan dependent constants.
774-R-013: Now we do this fit either per step or globally, for the whole 10 h of data that we take and calculate the residual orbit drift, basically subtracting the fit result except the constant.
774-R-013: Now, if you are interested on the extraction of the parameters in Alpha and detail, they are in the backup, and I don't have time to explain them. But what I would like to explain to you how we actually do the correction, and how we assign a systematic answer to this procedure.
774-R-013: So I mentioned to you that this fit can be done. Either per scan. It can be done globally, and you can also have assumptions, whether you consider your length scale for the VPN. As a constant for the whole thing or this dilution factor or nothing. And basically, if you take both the art and the.
774-R-013: and consider these different assumptions, and you can make this fit in 8 different ways. And we do this. We do the full procedure. We calculate the visible Cross section for each luminometer.
774-R-013: and then we look, what is the mean of this? And what is the spread among the different assumptions that you can make in this link. And basically, we choose a solution that is close to the mean in this case, in 2017 and 18. This was using Arc VPN data with the common length scale and the common scale factor. And this will be our central
774-R-013: value for the results. And then the spread is applied as an uncertainty related to this procedure, and you can see that, based on your assumption, there is a very strong correlation between the visible Cross section value that you get in 2017 and 2018. So this is an uncertainty that we consider as fully correct.
774-R-013: Now, if you do this you get. This is a 2,012 result for the residual orbit drift for being on and being 2 with different colors, you can see that these residuals are quite systematic.
774-R-013: a consistent shape between them. And while the effect on the central value was very small, it's something like 0 point 0 2%. It improves our scan to scan consistency with the scan rms going from about 0 point 5 to half.
774-R-013: So this is something that we find very useful, and this is something that we now reply every time.
774-R-013: Now, next one is talking about the length, scale calibration. We got a very good introduction. Again, here from Brian, we use 2 different types of scans to check the
774-R-013: position evolution of the Beamsport, the luminous region, and derive the scale factor from that we have the original Cms style scale that we have the 2 beams slightly separated, and then they are removed together, and we also do the Atlas style, which we call variable separation.
774-R-013: blank scale scan where one of the beams is moved and the other one is doing the Mini scan around it to get to the head of position
774-R-013: and
774-R-013: There are advantages and disadvantages of these different
774-R-013: scans. Typically, when we have less time, we perform the Cms tile scan. When we have more, they perform worse, because the Atlas style actually gives you per beam scale, which we use as an input forization.
774-R-013: Now, one thing that is very important, that we have done many simulation studies, and it turns out that the main uncertainty comes from the orbit drift during the scans.
774-R-013: and this is one reason why, from the original 5 step approach, we had 5 steps of the dream spot. In 2024. We actually moved to 9 steps, and also when we perform the variable length, scale scan, we do it also in the other direction. So back and forth as we did with our original Cms. One to have a better handle on the length scale.
774-R-013: Now, one is right here. This is from 2022 for all of our preliminary designs. We use the constant lens calibration. So the shorter one, because it's a bit easier to analyze. And so faster, we have performed a closure test for this in our paper, and as I mentioned, the main uncertainty comes from the orbit, brief and actually a very good proxy to estimate what these uncertainties.
774-R-013: the standard deviation of the step sizes between the steps and the strength steps, and for the variable length scale. For our long. To final paper we made a similar simulation study, we came to similar conclusion, which basically tells you that if you are unlucky you can have very large uncertainties because of the orbit.
774-R-013: And this actually
774-R-013: motivated us to come up with a new method that I will explain in a second what you can see here is in 2022. We had 5 lens, care scans in 3 different spheres, and you see the excellent agreement between the results of these lens care scans.
774-R-013: Now, the new method that I would like to show you is basically to mitigate the effect of orbit drift during the lensky and calibration. Now, when we use our traditional method in order to correct for the orbit drift. What we do is that we calculate the average step size, and we only apply a correction with respect to this average step size.
774-R-013: Now, this means, of course, that you, you basically take out the length scale of the VPN from the connection.
774-R-013: So how? How can you improve on it? What we found is that if you actually not derive the tracker to nominal length, scale in one step, but actually go and do it separately. You extract the tracker to Bpm length, scale, and you extract the nominal to Bpm length, scale.
774-R-013: Then you gain. Now why? This is because both the tracker and the Vpr. Actually sees the orbit. So basically, if you throw one against the other, the orbit briefs will at too large extent. Fall out. Now
774-R-013: for the nominar to the VPN.
774-R-013: I've already presented you the global fit that we do. And if you do this fit, not just using 40 min of data. That is your length scale, but actually taking 10 h of data. Then again, you have a mitigation of the orbit, because it's such a lot of data that basically, it falls out from your feet.
774-R-013: So but we do this two-step length scale calibration. And basically, I can't show you public results yet, but it halves the uncertainty.
774-R-013: Okay, now, just one comment. And this is about where we perform the length, scale, calibration scans
774-R-013: what you can or cannot see here is that if you want to determine the Doros length scale, it actually depends on the filling scheme, because Doros has 3 different options to actually do the calibration, and they choose the one that is experimentally fixed as the data according to the filling scheme.
774-R-013: And, for example, in 2024, we have measured the Doras length scale in the factorization. Md, and then, just a few days later, in our Median field, and there was a 2.5% shift in the result. So this is why Cms always asked for this, and we will continue to ask for doing the length, scale calibration in the same field that we actually do the media.
774-R-013: Okay, now, Xy factorization, which is a very hot topic. And in Cms we have 3 different methods that can estimate this.
774-R-013: The 1st traditional one is something called beam imaging, which uses the vertex data in some sense, similarly to the luminous region that we have heard before. It needs a special scan that one of your beams is stationary and the other one is standing through it.
774-R-013: and then you do a simultaneous fit of the vertex positions. In 4 stands you have 2 beams and 2 directions. Then you model the bond shapes with a sum of Gaussians up to 3 Gaussians in that model, and then you start the factorization correction. Now, we also use the luminous region method with some improvements.
774-R-013: So here again they use the vertex data. It means that both the beam imaging and the luminous region requires specially triggered 0 bias data which limits the available statistics. So we have to gate on a few bcis our data to make this measurement.
774-R-013: and we do a simultaneous fit as a function of the separation of the rate of aluminometer and the 3 dimensional parameters of the luminous region, as well as the bunch length ratio that we get from the longitudinal density monitors. And again, we get a measurement. And for this we can use any samples. So we can actually
774-R-013: role of the time evolution.
774-R-013: And we have a 3rd method which we call the 2D rate feed, which again, needs some special stance where you sample the off axis region of a bunch overlap distributions.
774-R-013: And
774-R-013: basically, this doesn't need vertices, which means that you can use it. For example, in heavy Ion collisions as well where the vertex resolution is close to the website. And we basically fit directly the rate into dimension as a function of the separations. Now, Peter will tell you a lot about the implementation of these methods. But I just would like to highlight a few observations that inform our strategy for the measurements.
774-R-013: One of them is that the correction on factorization can change very significantly as a function of time. You can see here the result from 2023, where, from almost 3%, we got down to somewhere like 0 point 5%. You can see that the luminous region method is more precise.
774-R-013: It has more information in some sense, but everywhere where we can cross check. It gives very compatible results with the 2D rate fit method. They both saw this large change in the factorization.
774-R-013: the dominant uncertainty, and this I have to really emphasize is the method closure for the luminous region. So I would. I would also encourage our colleagues to to look into that.
774-R-013: Now. The other thing that I would like to show is the dependence of the correction on the Bcid or the bench crossing Id. These are 2 results, one from 2022, and the other from 2023, using the 2D. Rate fit method, you can see that the measured correction is actually correlated with the bench families where I call a family based on the collision pattern. In how many
774-R-013: the interaction points the bunches collided.
774-R-013: and the same thing we measured, but now in 2 different, the 1st and the second part of the scan in 2,023.
774-R-013: Here you cannot see such a strong dependence of the correction. But what you can see is that there is some change in time as a function of the Bcid, and it is different for different bcids. And this is the reason why we believe that you need to perform both the more precise numerous region method, but also this 2D related method that can
774-R-013: tell you information per customer.
774-R-013: Now you can see how our scans done a lot. So from 2,022, where we had just the bill imaging one diagonal scan and one offset scan. Last year we had a long program, including 2D scans star scans, more diagonal scans, and so so that we can actually compare whether the result depends on how you sample the off axis.
774-R-013: and then you have your calibration. You want to look for unknown biases. And we do this in different ways. First, st we look at the visible Cross section as a function of the Vcis.
774-R-013: and you can check whether the Rms. Is consistent with the typical statistical uncertainty. We assign the standard error on the mean as an uncertainty. For this, then, we average over all these Cids, and look at the dependence as a function of the scan.
774-R-013: Again. From this we can have some dependence. For example, in 2023. This was 0 point 3%, which we assign as an uncertainty, and the really fantastic thing with 6 independently calibrated luminometers, we can measure the luminosity in the Dvr. Field completely, independently of each other, and see whether they agree.
774-R-013: And you can see here that, for example, in 2,023, the standard of the means was 0 point
774-R-013: a 2 person. So it's it's assigned as an answer.
774-R-013: Now, very quickly about monitoring. One thing you will hear much more about is the correction of the out of time rate, so pedestal, the spillover, the afterglow, which is from material activation. This affects 3 of our detectors, the hf, the pixel cluster counting and Bcm, one F, and this can be quite sizable up to 15%.
774-R-013: What we do is that we take the single bunch response from a special field, and you have one colliding bunch pair only, and then this can be done fit so that you subtract this out of time correction. You can see here one example for the Bcm one F detector for this. And you can see that basically we finish correcting almost perfectly to our
774-R-013: now how we can actually monitor
774-R-013: the stability. Of course you can use a reference. We have 2 of them, the tubes and the Ramsey's radiation monitors. They are very stable with respect to each other, and they are also very polynear with respect to each other.
774-R-013: and then you can look at the efficiency or the linearity of the other detectors. Of course, if you do that, and if you use that, then you would link them together. And this we don't want to do this is why, actually, the corrections that we apply are based on elements can only exist.
774-R-013: And David will explain to you the methodology that we use. We use these days the early scans to provide the efficiency correction. For example, in this case you can see here, by looking at the relative change in the visible cross-section, the efficiency for the Hf and we actually correct our online university
774-R-013: because we have separately calibrated luminometers already fluormimeter scales online in real time we can monitor the luminosity measurement. You can see here for an example from 2,023. It's very nice. Half a percent spread between the delivered luminosity between the 4 luminometers, and this also helps us to spot instrumentation problems very early on and after.
774-R-013: and the last monitoring tool that we have is the Z boson counting. You can see here the results from 2,024, and David will talk much more about that. I think tomorrow. For this you need some reference period, and in this case we use the 2,022 period as reference between the luminosity measurement and Z counting. And this was already public. And you can see here the
774-R-013: luminosity, Z luminosity and the online luminosity. At the start of last year we had not ideal online calibration at the time of Vbm, we have measured and corrected it. And you can see that basically with this 1% step corrections that we did based on emittance can result.
774-R-013: We stayed within 1% of the 0 units of the product from there.
774-R-013: So the final numbers for the precision of the integration.
774-R-013: Now, here we have 2 things. One is that we have luminometers. They have sometimes many channels, and we make an internal channel selection for the best stability and the best linearity for the measurement.
774-R-013: For example, in the case of the pixel cluster coating, we use typically only 10 to 30% of all the modules in the detector. And we check for noise in the video field. We check for internal stability, like what fraction of the pixel counts in the air a given model provides and keep the good ones.
774-R-013: And, for example, for pit, we will have. We have an automatic detection to look for any unexpected results as explained.
774-R-013: And then, as I mentioned to you, we use actually stability or efficiency corrections based on the emitum scans. This we do globally for the Hf. And per channel for Bcn. One F. And pit. But we can also cross. Check these emictorm scans with other measurements. For example, for the Hf. We have laser calibration for the pit. We can do track counting and get the efficiency from that. And then we can apply these corrections
774-R-013: for the linearity. Again, we have an internal selection for the best call linearity of the detector, both for Pcc and also for the dedicated luminometers that basically look at the end results, and they have to make sense. If you see eloquent results from the detective.
774-R-013: and then we apply these corrections and get to the final result.
774-R-013: Now, how this changed in time that you can see here before the introduction of emittance scans. In 2016, for example, we used a stable detector as reference. In this case it was the Ramses detector. You can see the Plt efficiency that you have the jumps. We change the high voltage for the system and also for the
774-R-013: linearity. Now, of course, if you do that, then you link your detectors together, and this is not so nice. So as soon as emittance can became available, we move to the emittance can be efficiency and linearity corrections. Now the 1st results were not perfect because we didn't understand a few effects like, for example, the linearity that you saw
774-R-013: is actually biased. If your potential is nonlinear, which we call major effect from the student who actually thought about it. And we also know from the studies of Joanna that, for example, building interactions introduce nonlinear to the measurement. So we are working a lot on making the emittance scan analysis better so that we can actually get to our 1% precision goal.
774-R-013: And now the final uncertainty on the integration part. We look at the fully, independently coordinated measurements of the good detectors. In time we calculate the integrated luminosity for each of them.
774-R-013: and we actually introduce a so-called average luminometer. What this means that all luminometers that have good quality in a given period is considered an equally, and we calculate the average luminosity from that. And then, on the average, luminosity, the uncertainty is the spread of the different measurements per detector.
774-R-013: and this average velocity is compared for linearity to our references, the Ramses and the and the Tubes. We look both at the spread and the possible shift in the linearity, and apply that as an additional answer.
774-R-013: And this leaves you with the integration errors that you can see here typically between 0 point 5 and 0 point 7% in the recent response. So this basically ends my talk. I have collected a few main issues as messages.
774-R-013: So I think we've made a huge progress on the absolute calibration, both for factorization, for orbit, brief measurements for line scale. And this is where really great
774-R-013: and what we found very useful is to actually make toy simulation tests of the different methods to understand what are the important aspects that the uncertainty actually has.
774-R-013: Now, there are very important inputs for the absolute calibration from the machine, the beam position, and the beam shape, and the more and the better data we could get, we would be the most happy. So this is a message to our colleagues from Lec.
774-R-013: We also see that sometimes, even when you think that you have perfectly calibrated duminometers, and you compare completely, independently calibrated duminometers. You see
774-R-013: large differences. It happened with us in 2,023, that we had 6 luminometers and 3 actually agreed with each other, but the 2 groups didn't properly agree. So I cannot emphasize the importance of having more luminometers, because
774-R-013: and okay, this give us larger errors. But then we go back and we understand them. This means that you actually get a much better understanding of your measurement at the end.
774-R-013: And finally, we have to work on the emittance and analysis understand the biases that are present. We believe that they are key for the high, nasty for linearity, and of course, also efficiency corrections. And you will hear from my colleagues, Francesco and Alex. Much more about what we do in this integration system.
774-R-013: Okay, thank you. Gabby.
774-R-013: Questions, comments.
774-R-013: Can I ask a clarification on Slide 19.
774-R-013: So you say you need to do the length scale in the same fill which is obviously ideal. But do you not just need to have the same filling scheme. Can you not do it in a separate fill? And Doris would pick up the same things? The IP 2 and 8, 1, yeah, yeah, okay, yeah, no. But obviously, if we lose the beam, then we can. We can put this
774-R-013: same one in. Yeah, no, thanks. I understand
774-R-013: some of the identical optics as possible, I think, is the key.
774-R-013: And and Bunch, thank you.
774-R-013: Yes, actually, I have a question on a bit the same when you use the Doros to extrapolate the position of at the IP. Do you actually assume that there is a kick in between coming from beam beam or not.
774-R-013: Not sure. I exactly understand what the question is, but when we do this fit, we of course, take into account the- the
774-R-013: yes kind of basically, I was wondering if you extrapolate the position at the IP. Do you take just the average of the left and the right side? Or do you take into account that at the IP in the center there is actually kink in this, because there might be a beam beam deflection there.
774-R-013: Each of the 2 measurements and the and the beam-beam is taken into account by this formula that.
774-R-013: okay, maybe we're talking about. Okay, let's yeah, maybe. Okay, it's too much in detail. We can discuss afterwards. Just curious if it's taken into context.
774-R-013: Yes, I'm coming.
774-R-013: Oops.
774-R-013: Thank you, Gabi, very impressive talk first.st I'd like to say that your plea for multiple Vdm calibratable monitors is something that I've been bending the ear of my Atlas colleagues with for many years. I can only support this
774-R-013: now down to business. First, st on the question that was asked about the Doris Bpms. I'd like to point out that the length scale of the Dorus does not only depend on the bench pattern, you're correct, and on the bench intensity, as Vladik points out, it's also time dependent within the same fail
774-R-013: at constant intensity. We have seen that as well. So there is a real issue. There now, I'd like to widen a bit. My, I have quite a few questions. I don't think I'll do all of them here, but my main issue I have, and the main thing I don't understand is not. I have an issue with it. I don't understand
774-R-013: why the Bpms. And in particular the Bpm length scale and the Beta correction factor for the beam beam play such a big role in your length scale calibration. I agree, of course, that orbit drift has to be corrected for, and we do the same thing. But in our procedure we take a point before we start scanning with the beams in head-on collision. So we don't worry about beam beam.
774-R-013: same thing at the end. So I'm trying to understand at a global level why you are so sensitive to the earth. Bpm, is it because your length scale uses this constant separation method.
774-R-013: What you correct yourself is just the linear orbit. There is actually order drift, due to various other reasons that I don't think your method takes into account. And if you take this into account and you do a simulation, for example, you do a random work simulation. What happens if from scan to scan. You have an audit.
774-R-013: then you can very clearly see from this simulation that actually the orbit drift that can happen between the steps actually affect the precision of your length scale. Now, it's, of course, true that if you're trying to correct for this, it is like in the magnetic nonlinearity analysis there the length scale of the doors matters an awful lot that I agree
774-R-013: now, something that you called. I think, the residual orbit drift correction. Does that include the what Atlas calls a magnetic nonlinearity. Yes.
774-R-013: so this this is the shape that we live in one year that we correct. You can see that this has actually a kind of a I don't know if you go after the talk to the backup. I actually included this for all the years so we can look at the shapes that we correct for all the years, and this includes what we call
774-R-013: as a Cmw. Co. Convener.
774-R-013: I think it would be very interesting to have in that meeting a more leisurely discussion of your landscape procedure, because I think there's a lot of interesting stuff there, and after I read your slides again, I'll come back to you and bend your ear.
774-R-013: I think we have a question on Zoom from Klaus, who is waylaid by the German airports today couldn't be here.
Klaus Monig: Sorry I would love to come, but no way to leave from Germany today. But I have a question. You have it already on your wish list. I have a question concerning the non-factorization in emittance scans. You want to go through below a percent. But you see, non-factorization effects of up to 3% already in Vdm conditions. So how well do you think you can control non-factorization in the emittance scans.
774-R-013: So it's an excellent question. At the end of David's talk you will have some wish for- for this.
774-R-013: I don't think that we can, we can very precisely correct the loan factorization. This is why it is really important that we do the Hamilton's scan measurements in as similar conditions as possible. So typically we do it now very early on before going, because changing.
774-R-013: maybe it will explain to you. But it's it's a good point. And this is. This is on our radar. But I don't think there is a magic solution.
774-R-013: Are there other questions on Zoom?
774-R-013: Other questions in the room?
774-R-013: Yeah, thanks, Gabi. Is there a plan for experiments to collaborate a bit on the understanding, the Xy factorization? But we do talk to each other.
774-R-013: And are we getting consistent results and scaling. I wanted to make a theory, but I run out of time. Maybe on the summary, we can do this in a week's time. But what I. What I see is that the measurements as published by
774-R-013: at last, and what we see are some of the corrections, do not agree with each other. So there is no correlation with the direct Xy factorization correction, and sometimes they even of different sides. So for one is positive, the other is negative. So if all the measurements are, you know, reliable, then I have to
774-R-013: conclude that these are not correlated. But the Xy factorization is something very local to be happening, which I think is not very surprising, because you have different.
774-R-013: I understand your perplexity. And I share. Okay, I mean, this is what we see what it means. I think one of the main goals of this workshop, in fact, is to have more discussion about exactly this point. So that's why we're here. I think it would be interesting to know if the correlations are between the beams or the experiments.
Klaus Monig: If I can say something from the Atlas side, we have, we have an error of a percent or more than 1% or not factorization at the moment. And please take this error series at the moment. And if you, if you take this, it's hard to see differences between Atlas and Cms right.
774-R-013: I mean, we have a year where the correction was really large. So we can look, for example, into that data. I agree with everything Gabi has said, of course, but on the correlation between non-factorization, correction and Atlas and Cms.
774-R-013: There is one famous example that started it all, and that is 2012, where both experiments saw the visible cross-section from one scan to the next. Go up a cliff, and we spend months banging our head against the wall until we understood it could be non-factorization. This was the start of the non-factorization studies.
774-R-013: and there there was very good agreement. There is another example now that is not published anywhere. But what is published is a comparison between the Atlas non-factorization correction in the July 2012 scans and the Lhcb. Non-factorization corrections in the same scans. This is in the 2014 luminosity Bible, and there the agreement is absolutely stunning.
774-R-013: and the evolution with time. During the fail July 2017, where we had non-factorization correction at the level of 3% or more. So there are circumstances where it matches. But I agree with Gabi. We have talked about the comparison of the run. 2 numbers, the 1, 2 numbers do not match, so there are quite a few mysteries left there.
774-R-013: I think there are many different sources of non popularization, and maybe it depends on whether this is more office related or big history related, or how.
774-R-013: Okay, well, thank you, everyone. I think it is time for coffee, so we'll close this morning session.
774-R-013: thanks to all the speakers, and
774-R-013: we'll restart at 4 PM. 1,600 correct their material.
774-R-013: So, okay, this is about the aspects of luminosity, determination that are more specific or more relevant for the ions. And okay, I will 1st give a list of a personal list of what I think are the most specific aspects, and then discuss a bit of them also in light of the material that is publicly available. So the ghost and satellite charge.
774-R-013: the scan shape, the treatment, the modeling of scar shapes and the treatment of the tails, the non factorization and the stability and consistency between duminometer. Then I will briefly summarize the current precision that we have
774-R-013: with the vis from run 2 and some very preliminary results from Run 3 and then also discuss the fixed target. Will made a termination. That, of course, concerns the Hcb smoke.
774-R-013: Okay, so here's what makes here are the main difference between heavy ion luminosity calibration with respect to proton proton 1st is that the heavy ion meantime, typically is limited. It's like one month or so. So. Of course, all experiments are hesitant to devote 2 or 3 days to Van der Mir Scan session, which is what is typically done for. PP,
774-R-013: so the Vdm scan program typically short, there's not much time for cross check or fancy tests. And also for the same reason, there's no time to set up a dedicated optics, so the Vdm scans are taken in more or less the same conditions as physics. One can play a bit with the filling scheme, of course, but the optics is the same. This, for example, means that the Beta Star
774-R-013: will be the same as physics, so it will be small, so the luminous region will be small, and this will put a limit to all the. This will put a challenge to all those studies that are based on the vertex, be it the non-factorization, but also the landscape calibration. On the other hand, the fact that video scans are taken in the same condition as physics as a plus aside, which is the fact that one expects
774-R-013: smaller uncertainties from the calibration transfer, because, for example, the new visible new is the same. Typically in physics and at the low condition of the Vdm scan, and also for the long term stability. Since the data taking is short, is one month one expects to be less sensitive to all kinds of deletes.
774-R-013: The bunch intensities are smaller, much smaller. So the luminosities are much smaller. This means that typically the uncertain, the Bimbi effects are very small and so, and those are the associated uncertainties we can expect, although this is not entirely true. From some type of technologies we could expect less saturations. But this is specifically true for methods based on event. Counting.
774-R-013: on the other hand, low luminosity means low rate in several cases. So bunch by bunch studies are typically statistics limited. There are cases, for example, in Alice when one could only do a bunch integrated analysis without the limitation it carries, and when you go to the tails of the scan, if you have some detector noise, this will become, of course relatively more important, so on.
774-R-013: to be particularly attentive to what happens in the tails of the scan, and in general the scan shapes tend to be a bit funnier than in beauty. Sorry.
774-R-013: and this might be due to the the large charge of the
774-R-013: of course, of the lead nuclei, which also, in the longitudinal phase, space leads to large ghosts and satellite charge. These are corrections that are big up to 10 percentage and typically time dependent. And these are corrected for using the variations Mdm. And the beam gas imaging data from an Hcb. But this comes with some
774-R-013: issues that I will discuss finally, the velocities are low, but if one uses electromagnetic processes, the cross section can be very large on the order of hundreds of bars. So this all paves the way to the usage of 0 degrees calorie meter
774-R-013: as lubinometers. And we will see some examples in the talk.
774-R-013: Okay, now, 1st topic I want to discuss is the gold standard correction. This is an
774-R-013: I will use the Alice round 2 results as a case study in the Vdm. Field of 2018. Alice experienced what I think is to date the largest loss plus satellite chart correction. It was 13% total, and this, of course, affects bunch intensity, but also the measurement of the rates, because we see that at least in Alice this satellite can trigger the lubinometers.
774-R-013: And what complicates everything is that this satellite fraction can be strongly bunch dependent. Here you see the distribution over a half orbit of the satellite fraction measured by the Ldm. And basically the fluctuation of this square bunch by bunch is about 50%
774-R-013: of the mean value. So this triggers the question on, how should one correct for satellite charge? This is something that Ali has to struggle a lot with. And I will quickly summarize the findings of this study.
774-R-013: So basically,
774-R-013: we use fast beam current transformers to determine the relative bunch populations. And of course, then we use the Dcct for the overall bunch current beam current normalization. So this brings the question, how sensitive is the Fbct. To the satellite chart. So how much of the satellites get integrated into the Fbct. Signal? Because the answer to this question basically should tell us how we should correct
774-R-013: for satellite charge in the extreme assumption that electricity is fully sensitive to the satellite charge. This gets integrated into the signal, and then one would have to perform a bunch by bunch satellite correction. So correct population of each bunch with the corresponding satellite fraction
774-R-013: on the other. Extreme option. If Fbct. Doesn't see satellite at all. It only sees the main bunch. Then we would have to treat the satellite charge as a correction to the overall Dcct. Charge same as we do for the ghost charge.
774-R-013: Basically, all these studies was triggered by this plot. You see, this is the
774-R-013: a cross-section of the from the Alice Fdc bunch by bunch. So each data point is, A is a bunch pair, and you see the cross section, and there's a big spread. You see, the Chi squared over the F is huge, and then, after some study, it turned out that we tried to plot this versus several quantities, and we didn't see any correlation until we plotted it against the
774-R-013: fraction of satellite charge of the specific badge.
774-R-013: So you see that here there is clearly a
774-R-013: there is clearly an effect, a correlation with the satellite charge, and that seems to be what's leading this large spread in bunch by bunch core section. So this, Alice. So far we have always been treating the satellite charge as the ghost charge. So we were correcting the full. The Dcct. For the total fraction of satellite charge without attempting to do a bunch by bunch correction. So we did that as a test to see whether that would improve
774-R-013: things. But actually it made things worse.
774-R-013: So the spread is large, and it becomes even worse if you try to correct bunch by bunch on the plus side. If you look at the average cross section here, this stays very much the same in the 2 cases. And this is because we were lucky in that field, 95% of the bunch pairs were colliding in ice. So basically, in such situation.
774-R-013: how you distribute the luminosity across bunches matters much less what the precision is driven by the Dcct normalization. So that's why we could still
774-R-013: get a good result. But while investigating this, we came across this very nice study done by the Ldm group, and already presented with the 2019 gloomy days. But I'll summarize it here also in light of what we saw in Alice, because I think it's interesting by the way, they use our specific field, the 7, 4, 8, 3 as a case study, because it again, it was one with very large
774-R-013: ghost and satellite correction. So what you see here is they studied the ratio between Fbct.
774-R-013: And the sum of Bsrl bunch per bunch
774-R-013: with proper normalization, and it's plotted here as a function of the satellite fraction of each branch. So of course, if let's see if one if Sbct was fully sensitive to satellites, then this would be a flat line which could go to 0. The difference could go to the relative difference could go to 0 with proper calibration. If it was not sensitive at all, then this would be a straight line.
774-R-013: because basically, the the satellite fraction is the difference between the
774-R-013: Fbct. And the Bsr. So what you see here you find one of the 2 cases you find the more complex dependence, and the conclusion of that study was that the sum of satellites per bunch is a poor predictor for the Fbct bunch. Intensity. By the way, if you look at our Sigma visa spread as a function of the satellite charge.
774-R-013: It has some striking similarity with the spread of this Sbct. Over the acceleration, but our
774-R-013: colleagues from the Bin group went even further. They tried to model this. So they came up with a fit model, where they basically assume that each satellite contributes to the total Fbct intensity, but with a weight that they called lambda, which can be positive, but can also be negative.
774-R-013: And basically they fit this from the data using all the branches, and they get very good agreement between their model and the data. And and this, let's say.
774-R-013: measured Fbct. Over Bsrl ratio, and, as you see the extracted lambda, lambda coefficients. They are positive when you are near the main bunch, but they become negative when you are farther away, and their interpretation was that the near satellites contribute to the Fbct. Integrated chart, so they get integrated in, although with a lambda less than one meaning, they don't contribute as much as the main bunch. There is a scale factor.
774-R-013: and the they interpreted the
774-R-013: negative lambdas further away, as the far satellites or near goals contributing to the baseline, so leading to another subtraction of the baseline and a decrease of the Fbct. Signal. So this might explain the positive correlation actually, that we see now is of Sigma vs. Versus the satellite fracture. So the conclusion is that the Fbct sensitivity to satellites is not trivial. It's not one of the 2 obvious of the 2 extreme cases
774-R-013: which I mentioned is somewhere in between, which leaves us without a clear recipe for the satellite charge correction. So we should accept that if
774-R-013: unless, of course, we go to
774-R-013: very let's say, complex corrections such as maybe based on this model. For example.
774-R-013: we have to accept that if there is a large satellite charge, variation bunch by bunch, there will be a large bunch by bunch spread of Sigma V's. But this can be cured, as I mentioned, by making sure that the fraction of colliding over total bunches for the experiment who is doing their Vdm. Scan is large in that way. Then this, okay, you will still get a bad bunch by bunch consistency, but you will know where it comes from.
774-R-013: You will know that it does not affect your final observable that much.
774-R-013: Okay. Moving to another topic. It's how it's the dealing, basically with low signal over background. And the treatment of the non collision. Right here we have a very fresh example from the Cms. Analysis. We just came out on Archive. They, as already mentioned, partially by Gabby. They have several sources of background.
774-R-013: like the beam induced background, the out of time background from the electronics and the activation and intrinsic detector noise. And of course, in net lead. This is non-negligible already at head on, and it can become maybe the dominant rate contribution in some cases in the tails. So the important thing here is here is to have several handles to estimate this background. So we've seen some example. The non-colliding bunch pair.
774-R-013: when the filling scheme is sparse enough. You can use the slot right before a colliding bunch, and also these dedicated super separation scans, which is a cool idea that Cms came up with. And okay, once all these effects are taken into account, I find it striking that
774-R-013: the manager. In the end they are left with a cube that can be described by a simple option. But that's that's what what happens. But still, the fact
774-R-013: of this background subtraction on the visible Cross section is very large, much larger than what we are used to in PP, probably it's 2.5% for their main meter, but it can go up to 8% for the Hf. Something in between for the Vcm, so it's really something that one is to look into.
774-R-013: Now, a similar example for my list
774-R-013: here. Basically, we realized quite soon that in the in the tales we have an interplay between the law statistics
774-R-013: and the
774-R-013: and the contribution of the noise. So basically, we came out of that with a global likelihood fit which has its core, a description of the luminous rate, but also parameterization of the various backgrounds. Like, you see.
774-R-013: there's parameters that describe the beam induced background, the detector noise, and also the contribution from satellite collision. This is something that in ours we are very sensitive to, or our luminometers do see satellites.
774-R-013: and they see them in a way that is dependent on the separation for a number of effects. So one would have to do. We have the good timing resolution with the Ztc, so we can really identify satellites.
774-R-013: But again, we would have to do it as a function of the separation and also bunch per bunch. And this is not possible due to the statistical limitation. So basically, what we have to do is to measure a bunch integrated fraction of satellite which gives us the starting point for this satellite collision probability and then adjust it bunch by bunch by means of a local likelihood maximization which
774-R-013: basically uses also as an input the discrepancy between the feet and the measure rate. Alternatively, one can use the Ldm Ldm information to adjust this satellite collision probability bunch per bunch. And unfortunately, we find quite a big discrepancy between these 2 methods which leads to one of the dominant uncertainty for the analysis.
774-R-013: Okay. And this is also regardless of the background.
774-R-013: In general, scans can be funny. So even after all, the subtraction of background on as well as we could, we found that the usual shapes, like the simple, the double, or the modified Gaussian, for example, multiplied by a polynomial, did not fit well the average length scan data. So in order to make the fit converge, we had to add these symmetric tail parameters added as a separation dependent modulation. You see, there is this Delta J.
774-R-013: Added here in the numerator of the of the Gaussian exponent, and these parameters. They are symmetric, and they start beyond a certain separation. So you see, depending on the consider colliding bunch pair, we had to start adding this parameter from the 6th step, or from the 9, th so that was giving us 4 to 7 extra feet parameter. When that was done, then
774-R-013: the fit, the finally the feed quality was good.
774-R-013: And here I have a very recent plot from Atlas. This is the first.st This is already from run 3, where they compare the scan Q for the lucid and for the Zdc. Here the main message is that Gaussian function multiplied by a 4th order. Polynomial seems to do the job. Also we can clearly see how the Zdc. Which is sensitive to electromagnetic processes.
774-R-013: give some newbies, which is almost 2 orders of magnitude. So
774-R-013: you also see from the precision of these data points how beneficial it is to use a DC in that lab, because then you get
774-R-013: suddenly more statistics. And also we see the effect of the we can come. In this comparison. We can see the effect of the wind gas, which is subtracted for usage and not subtracted for Zpc, so of course, this clearly show how this can be an important contribution in the tale that has to be done, too.
774-R-013: Okay.
774-R-013: last point. Second last point I want to make is about the non-factorization. So basically, as I already mentioned here, the luminous region is small, like order of a few tens of microns compared to what we get in Bp. Which is a very large luminous region, so of course, we are hitting the limit of the vertex in resolution, and also in some cases
774-R-013: the statistics will be limited because the rate will be smaller. So what you see here, this is an Alice implementation of the Atlas
774-R-013: trademark, luminous region evolution method. This is applied to piled, and you see
774-R-013: the agreement between data and food is poor for some of the quantities. And partially, this is because in this example, for example, we could not do this bunch by bunch, we could only fit
774-R-013: the bunch average quantities. So basically because of that, whenever we see this kind of failure of the model to reproduce the data, we always apply an uncertainty of 100% of the correction, and that can can become larger for 1% and 2. And here is a similar example from Cms. This is also pled. This is their beam beam imaging method. This is the pools that they get from this
774-R-013: fit to the 2D distribution of vertices. And you see here the group can be quite large, and this reflects in quite a large uncertainty. And Atlas, also, using this method, got similar uncertainty for the order of 1%.
774-R-013: One way is already here. Gabi already spoiled the point point I wanted to make in her talk. Basically, the one way to overcome this is to somehow get rid of this luminous regional analysis and use the rays. So in order to do this, one is to become very granular in 2D. Face space. So of course, we have seen a lot of examples of diagonal offset scans.
774-R-013: It's done by Cms and also atlas. And then from this one extract parameter from the non-factorizable models and can use them to simulate the bias from the factorization assumption. And here you see how nicely they did it in Cms. Here you see the different fit models. The correction that they give these, of course, is the basis of their uncertainty, and they are also able to take into account the time dependence of the math. So this is a nice alternative
774-R-013: to the vertexing for for, and we also have a recent result on this via already discussed there to discuss. This is how it looks like when applied to.
774-R-013: and these are the pools, and of course they have an uncertainty which is on the order of what they got around to with the fact. This is pre preliminary, as they mentioned, so of course, I'm sure there is room for for improving here.
774-R-013: Okay. Finally, about the stability and consistency of the aluminum meter. I mentioned this expectation that things should go
774-R-013: should be better should be. That should be easier in PP, and partially, we see that because this uncertainty is always less than 1%. These are all examples from around 2.
774-R-013: You know the address from Run 3, but they got a similar result in 2. And these are okay. This comes from the various reasons I already mentioned. However, it's clear that there is room for improvement, for example, point 7%. Uncertainty is good, but not amazing. We have seen in PP calibration transfer, uncertainty which were even smaller than that, although they were referring to a much longer time span. So
774-R-013: there's room for improvement, and they're probably again the treatment of background could be important, and also for all those database, for example, on photo multipliers, we know that this can age pretty fast and lose their gain pretty fast
774-R-013: even in, because, even if the rate is low, the current is relatively high, because you have all these very high multiplicity, events and similar results have been achieved for piled, although slightly worse in.
774-R-013: and this is a summary of the luminosity precision for lead lead. So here we have Alice Cms. And that last round 2. We also have the preliminary 4 and 3, so we can see
774-R-013: that the the uncertainty ranges from 1.6 atlas to to 3% Cms, but only for one scan, because for the 2018 there on the Atlas level, Alice is somewhere in between 2.5%. So this is this is good, I think, but
774-R-013: bit worse than what one typically gets in proton proton. And we can see for M. 2 that in all the cases we see it's it's striking that in the end the dominant uncertainty. If we forget the satellites for Alice, it's always there's no factorization. And it's always
774-R-013: on the 1% level for Atlas Cms and and that is, and okay, these are the very preliminary results of Atlas for 4 and 3. The uncertainty is larger, but of course I guess that a lot of stuff is still being worked on, but it's nice to see that they already were able to wrap things up and get to a number.
774-R-013: Finally.
774-R-013: I just want to mention that, of course, the ideas at the Nhc. Is not only that led collisions, it's also the fixed target program at the Nhc. Here they have ambition, ambitious plan for plans for their smoke update. So here, of course, this is a totally different scenario, the luminosity. It's a fixed target luminosity, and so far they've been evaluating it indirectly, using the
774-R-013: no theoretical conception for some reference processes, but here they want to go farther and really measure it from the thickness of the target, which is, of course, target. So one has to be really precise in
774-R-013: measuring the time dependent of the gas flukes that it's injected in the in the beam pipe. And now they estimate an accuracy of below 5%. But the goal by improving all this modeling and the fitting procedure, the goal is to reach less than 2%.
774-R-013: Okay, so that's my summary. Okay? So several aspects of luminosity, determination, deserve special attention. I mentioned the satellite chart here I have this, repeat this recommendation to always have large fraction of colliding bunches in your Vdm scan. We see that there is an interplay between background sources and scan shapes that, of course, leaves a lot of room for improvement.
774-R-013: and also fantasies to see fantasy how to take all of this into account. The no factorization. We see how the vertex in base correction hit their limits, but results from scans based purely on the rate are promising and the current positions 1.6 to 3%. And of course this is
774-R-013: well a bit towards the Mpp. And the target for and 3, of course, is to close the gap as much as possible, and we've seen how there is
774-R-013: interesting prospects also for the luminosity of fixed target in the next week. Thank you.
774-R-013: Thank you very much.
774-R-013: Right?
774-R-013: Thanks a lot for this.
774-R-013: Okay.
774-R-013: yes, thanks a lot for this very nice presentation. Just one question in, say, slide 6, 7 for the satellite story, because it's striking how similar these distributions from fast Bct. Versus Bsrl are to your findings. Did you ever try to normalize the integral of the Bsrl to the Dcbct and
774-R-013: use that to do your analysis to see if this would reduce the punch to punch spread.
774-R-013: So you mean, basically forget about the efficiency?
774-R-013: Yes, yeah, as a test. But use directly the the Bsrl to measure intensity. Well, it can only measure in relative. But if you normalize to the Dcbct.
774-R-013: But again, if we don't know
774-R-013: how much of okay? Because that would see all the satellite. Yes, this is something that no, this is something that we didn't try, because in the end we were happy with the main uncertainty. Here in the end is from the collision, not from the right, but yes, it's an interesting suggestion. Why should try it? Okay, thanks a lot
774-R-013: more questions.
774-R-013: Yes.
774-R-013: thank you. Still, on this slide, you made it clear that the Bsrl measurement of the satellites is a poor predictor for the Fbct. Bunch intensity. But that's the fault. Quote unquote the limitation of the Fbct. Do you have any indication of inconsenses or problems with satellite fractions from the Ldm. Or are you absolutely happy with them?
774-R-013: Well.
774-R-013: for satellites? It probably doesn't matter. But maybe Baduel wants to comment. Yeah. Well, the comment to the previous question was, the fast Bct, we know there are problems with the baseline. That's what you are getting here. So when there are many. There are the main branches and the satellites. The baseline subtraction doesn't work fine.
774-R-013: But for the Ldm. Yeah, you will have to tell us for us. It works fine. Yeah, they shouldn't be. The Ldm. Should be better on the fast visit for this, for this field. The Ldm data was gold. I mean it was the the difference between
774-R-013: difference between baseline subtracted and non baseline subtracted was very small, and all the other consistency consistency between system A and B. They were all all very good for the ghost charge. I remember this was funny, because there were quite some differences between Mdm. And the Hcb. For the single beam, but they were in opposite direction. So in the end, when you do the bunch product again, this was very, was very small.
774-R-013: So, okay, maybe it was a lucky coincidence. So overall, we didn't support any issues with the idea, at least for this field. Thank you. And then a comment on applying the luminous region analysis to non-factorization corrections which you made clear is not an ideal solution, but sometimes those are the only data we have.
774-R-013: As you pointed out, the vertex position. Resolution is, of course, a much bigger issue than in PP. Vdm, scans, because the beams are smaller. And here I'd like to point out that there is an important
774-R-013: that sensitivity to the resolution
774-R-013: in the luminous region. Method for non-factorization depends very much on which correction method you use if you use. That's the 2 Dvdm doesn't have this problem. This is only for beam spot. If you use for the correction the ratio of the on axis slice treated as a 1 dvdm. To the whole surface. It's fine. The resolution mostly drops out.
774-R-013: while if you try to get directly a Sigma, visible cross-section from the head-on overlap integral. Then you are very sensitive to the resolution. We already see this in PP. Where the resolution is less of an issue, and it must be a very big effect here. So for groups who would like to do lrae analysis on lead lead, one really has to look at this resolution issue quantitatively
774-R-013: any more questions.
774-R-013: If not, then thanks again and
774-R-013: we will have, the next presentation from Guillermo and the Alice
774-R-013: down to data. If I manage to oops.
Jesus Guillermo Contreras Nuno: Hi! Can you hear me?
774-R-013: Just video share or.
Jesus Guillermo Contreras Nuno: I prefer to share, if it's possible.
774-R-013: Okay, I might need help.
774-R-013: with that. If someone knows how to.
774-R-013: Just one second until we solve the technical, can you try it.
774-R-013: Not yet. You are still sharing the screen
774-R-013: we are still sharing. In that case there's nothing you can do there.
774-R-013: So I think I've gone to remote sharing. That's so. Why can it not work.
774-R-013: Eric? No. Is Eric have to go with me cool.
774-R-013: Now I can share.
774-R-013: Give it this, give it a whirl.
Jesus Guillermo Contreras Nuno: And yes, yes, it works now.
774-R-013: Perfect.
Jesus Guillermo Contreras Nuno: Now you see my screens, I guess.
774-R-013: Yes, we can see your slides, and we can hear you. So I think you have 15 min.
774-R-013: Okay.
Jesus Guillermo Contreras Nuno: So let's start 1st of all, an apology that I cannot be there. But the teaching has started. So I have to be here.
Jesus Guillermo Contreras Nuno: Thanks for inviting us to to give the results from Alice.
Jesus Guillermo Contreras Nuno: I will briefly summarize the luminosity measurements that we performed during
Jesus Guillermo Contreras Nuno: Round 2, and the final results we obtained the
Jesus Guillermo Contreras Nuno: okay? So first, st let me mention the detectors that we use for luminosity. We have 3 luminometers, which is 0 v. 0 0 degree calimeters, and for the non-factorization and length scale calibration, we use the inner tracking system.
Jesus Guillermo Contreras Nuno: So let's go to these detectives. This is a picture of Alice. The Cdcs are here and here far away from the interaction region, and here, in the middle, you have a zoom in, and there you have in green the its, and at the borders of the its you have the T. 0 and the V 0.
Jesus Guillermo Contreras Nuno: The T. 0 is youth, bold.
Jesus Guillermo Contreras Nuno: sorry in PP. And in Proton led scans.
Jesus Guillermo Contreras Nuno: It consists of 2 arrays of 12 cheretov counters.
Jesus Guillermo Contreras Nuno: and it is placing. It has 2 arms, one covers from 4.6 to 4.9 in cellular rapidity, and the other from minus 3.3 to minus 3 in cellular rapidity in the other side, and the reference Cross section was defined at the level 0 trigger.
Jesus Guillermo Contreras Nuno: and it is defined by having a signal in each of the rays, such that the interaction vertex, evaluated by the distance of arrival times in the 2 arrays is within 30 cm of the nominal interaction point. As the detector has a pretty good time resolution of 20 picoseconds. There is a negligible signal loss. Using these
Jesus Guillermo Contreras Nuno: history.
Jesus Guillermo Contreras Nuno: then we have the V 0 trigger, the V 0 detector, which is used in all the scans in all 3 systems. It's again 2 arrays, each one made of 32 scintillator tiles. You see one of the tiles here
Jesus Guillermo Contreras Nuno: again the 2 arms, one covering from 2.8 to 5.1 itself rapidity, and in the other arm, minus 3.7 to minus 1.7 rapidity. So it's a lot larger coverage than T. 0
Jesus Guillermo Contreras Nuno: it has at the trigger level 2 time windows, one to to get the beam gas and the other to get the beam beam interactions
Jesus Guillermo Contreras Nuno: and the reference cross section for proton proton and proton lead was similar to the T. 0 in the sense that it requires a signal in each of the rays at the level 0 trigger lab.
Jesus Guillermo Contreras Nuno: yeah. LCO. Triola.
Jesus Guillermo Contreras Nuno: the referring cross-section for lead light scans was different also at the level 0 trigger, but it requires that the sum of the signals amplitude. So the amplitudes in this case, not just counting from all v 0 scilators is above a threshold that was chosen to correspond to the 50%. Most central hydronic collisions.
Jesus Guillermo Contreras Nuno: Finally, as luminometer, we have the 0 degree calorimeter. We have proton and neutron for luminosity we use only neutron calorimeters, and these are used exclusively in led light scan.
Jesus Guillermo Contreras Nuno: Again, there are 2 calorimeters of a tungsten alloy. It's made of 4 sectors which are read out with scintillative fibers, and they are about 100 meters away from the from the nominal interaction point. They cover the rapidity range for rapidities larger than 8.8,
Jesus Guillermo Contreras Nuno: and in this case the reference cross section is defined by requiring a signal in at least one of the 2 neutron chlorometers where the signal has an energy position that is larger than one TV, and this threshold is about 3 standard deviations below a 1 neutron signal. So it's pretty pretty good to get all neutron events
Jesus Guillermo Contreras Nuno: now moving on to to these inner tracking system. This is used in all scans for the length, scale, calibration, and the non-factorization correction. Using vertices.
Jesus Guillermo Contreras Nuno: It is composed of 6 cylindrical layers, which is made up of 3 different technologies. Pixel drift and strip detectors.
Jesus Guillermo Contreras Nuno: It is a quite
Jesus Guillermo Contreras Nuno: close to the beam, 3.9 cm, the distance away in radio for for the V 1st layer to 43 cm, and it covers the rapidly range from
Jesus Guillermo Contreras Nuno: plus 0 point 9 to minus 0 point 9
Jesus Guillermo Contreras Nuno: this is a tracking detector that reconstruct the primary vertex of the collision during the scan.
Jesus Guillermo Contreras Nuno: and you have an example here for the length, scale, calibration. Here you have the Y coordinate of determined of the vertex. Here you have in the different colors, the different steps of the length, scale, calibration taken in 2017 proton-proton collision, and there were 6 steps, and you see them clearly separated here.
Jesus Guillermo Contreras Nuno: So these are the the luminometers and the auxiliary detector for for some studies, and we have the following Van der Mae scan during 1 2
Jesus Guillermo Contreras Nuno: proton-proton collisions at 5 TV and 13 TV, then proton lead and lead proton collisions at 8.1 6 TV, and then the lead lead collisions at 5.0 2 TV.
Jesus Guillermo Contreras Nuno: Did you have a summary of the condition during the scans? Because there may be slightly different from what you guys use in Atlas and Cms and even Lhcb.
Jesus Guillermo Contreras Nuno: so what you see here is the the different system with the different years.
Jesus Guillermo Contreras Nuno: The field where the data was taken, the beam intensities. This was already briefly mentioned by Martino, but the intensities are a few 10 to the 10 for proton per bunch.
Jesus Guillermo Contreras Nuno: while for lead is around a few 10 to the 7, 10 to the 8th lead, ions per bunch, both in proton lead and in lead collisions
Jesus Guillermo Contreras Nuno: the budget during the during the scans is around 2020 ish for proton proton collisions, proton proton scans around, 200 for proton lead and around 600 for lead lead.
Jesus Guillermo Contreras Nuno: and the Beta Star changes during all these scans in proton proton was 10 meters and 1219, and it but for proton lead it was already smaller. 2 meters and for lead lead it was really small.
Jesus Guillermo Contreras Nuno: The half vertical crossing angles also varies a lot. If you have the different numbers, and the maximum b separation corresponded in in proton proton, about 6 rms. Of the of the sigma of the V
Jesus Guillermo Contreras Nuno: also for lead, lead, but for proton, lead and lead proton it was only 4.5
Jesus Guillermo Contreras Nuno: here you have. In each page you can click. These are the all the published references for
Jesus Guillermo Contreras Nuno: for the for the scans. Most of them are public notes only for the led light scan. We publish a paper.
Jesus Guillermo Contreras Nuno: So the typical scan sequence analysis is the following, here an example for the V 0 rate integrated over all bunches across time, you have 2 consecutive Xy scans, then the length, scale calibration and offset scan
Jesus Guillermo Contreras Nuno: the steps during the Xy scans is 30 seconds per step, and the whole procedure take a bit less than 4 h.
Jesus Guillermo Contreras Nuno: If there are no problems.
Jesus Guillermo Contreras Nuno: then I wanted to show you an example of the uncertainty tables that we produce. This is for proton proton at 30 tb, all other tables are in the backup of this presentation, and you see, a relatively long list of of items that we cover a bunch intensity current normalization, non-factorization, etcetera.
Jesus Guillermo Contreras Nuno: You see here the 2 luminometers that we use in proton proton light.
Jesus Guillermo Contreras Nuno: and what we observe in general is that there are several smallish contributions that add up a little bit, and then a few larger ones, which dominate in this particular case. The one that dominate is called here stability and consistency. And this is just the transfer of the results from the van der meri scan to the physics front to the full year.
Jesus Guillermo Contreras Nuno: In this case. This there was the dominant uncertainty.
Jesus Guillermo Contreras Nuno: I don't have much time. I would like to present some studies where we had problems and some where things look nice, and these are taken from different systems, so that you have an overall view. And this last one I will not mention, because it was discussed just a moment ago by Martina.
Jesus Guillermo Contreras Nuno: So 1st let me start with the background. Subtraction in v. 0. And this is the main difference in the uncertainty between T. 0 and V. 0 luminometers in PP. Collisions.
Jesus Guillermo Contreras Nuno: So what you see here is the time difference in the time measured independent in the A and C array against the time zone.
Jesus Guillermo Contreras Nuno: And you see here this is the the beam, beam, collision, and these are satellites, and then not satellite beam gas collisions, and then you see some other contributions.
Jesus Guillermo Contreras Nuno: So what we do is we put some windows here in this area, and we change the sign of the window.
Jesus Guillermo Contreras Nuno: and and by changing these these windows here we we get an uncertainty of the background substraction, which varies from 0 point 6 to 1.1 across the the proton proton scan.
Jesus Guillermo Contreras Nuno: And you see here the effect of of this background. What you see here is the ratio of different rates, and interesting for this particular slide. Is this one the black where you see the rate that, we get the raw rate and then corrected for beam background events
Jesus Guillermo Contreras Nuno: by background events, and you see that the corrections is pretty large at large separations. And then this affects the results of the fix. Of course.
Jesus Guillermo Contreras Nuno: another another study is that we? We can do the measurement of the of the visible cross-section bunch by punch, and then compare not only Punch by punch, but also across scans in these cases for proton lead and lead proton in red, v. 0, luminometer in blue, the T 0 luminometer. And this is across the product of bunch intensities, and these are the visible cross sections.
Jesus Guillermo Contreras Nuno: And if you have a moment to look at the, at the numbers, you will realize that the the variation in the red numbers are small than the variation, smaller than the variations in the in the blue numbers. Both of them are small in general, but the scan scan by scan consistency is a slightly larger contribution.
Jesus Guillermo Contreras Nuno: But all, all in all things, are pretty well under control.
Jesus Guillermo Contreras Nuno: Then this is special. I want to discuss a little bit the length, scale calibration. What you have here is the separation as measured by Alice, and the separation as proposed by the lac. This is for the vertical scan, and this is for the horizontal displacement.
Jesus Guillermo Contreras Nuno: and these we have 3 different step sizes. This is data from Leadlet, and this is already by the the item that was mentioned by Martino, that the the beam spot is a lot smaller, and then we are getting to the resolution of our detectors.
Jesus Guillermo Contreras Nuno: So
Jesus Guillermo Contreras Nuno: doing, these 3 different scans with 3 different step sizes. We can control a lot better. The the systematics. We have a lot more handles.
Jesus Guillermo Contreras Nuno: The correction is large in for this case was 3.6%,
Jesus Guillermo Contreras Nuno: and the uncertainty was around 1%, and it has different contribution, the the size of the data sample. We repeat the analysis with many different event selections, the comparison of the different colors here, so the different step sizes and the deviations of every single fit. With respect to the linear trend.
Jesus Guillermo Contreras Nuno: then this has been already discussed in the previous presentation and and discussion session. The non-factorization correction these cases for proton-proton collisions at 13 tb.
Jesus Guillermo Contreras Nuno: And what we do is we fit the rates and the luminous region parameter during the scans with a 3 dimensional, non-factorizable double Gaussian model, and then compute the bias on the head-on luminosity. With respect to the factorizable model.
Jesus Guillermo Contreras Nuno: as Martin already mentioned, we take the full correction as a systematic uncertainty. And this field correction varied widely across, run 2 scans from a fraction of a percent to 1.1%
Jesus Guillermo Contreras Nuno: then a few words about the stability and consistency. And this is probably a little bit different from there are some something a little bit different in collisions with respect to to the other experiments. And this is basically because we have very, very, very small luminosity with respect to to you guys.
Jesus Guillermo Contreras Nuno: So during proton prototy physics runs. Alice collected data on the typical conditions of the visible rate of 100 kilohertz that translates into an average number of visible interactions per punch crossing of 0 point 0 0 5 or 0 point 0 1.
Jesus Guillermo Contreras Nuno: And in some special cases it went up to 0 point 0 5.
Jesus Guillermo Contreras Nuno: And this, I think, is quite different from what you have, and what we do is then we plot this ratio of the different luminometers we use and we weigh these run by run, by the integrated luminosity of the room.
Jesus Guillermo Contreras Nuno: and the mean quadratic difference from unity of the ratio is taken as the systematic uncertainty.
Jesus Guillermo Contreras Nuno: So here you have the similar plot for lead proton.
Jesus Guillermo Contreras Nuno: For the conditions of physics. Zones were very similar to those during the scans. With these new visible, ranging from 0 point 0 0 7 to about 0 point 1 for the V. 0.
Jesus Guillermo Contreras Nuno: Finally, for lead lead collisions, the same thing. The condition for physics. Drones were similar to those during the scans. The new visible was of dollar, one per mil for Vc. ROM. And 50 times larger for a
Jesus Guillermo Contreras Nuno: for the trigger with the Cdc.
Jesus Guillermo Contreras Nuno: This. Bring me to the summary.
Jesus Guillermo Contreras Nuno: again. The details of all the tables are in the backup. We have measured a series of systems, all the
Jesus Guillermo Contreras Nuno: collision systems and energies during all the years in round 2. Here you have the the total uncertainties in the visible cross sections and the van Emer scan for the 2 luminometers for each case, and the stability and consistency separated for for each one of the system, and the total
Jesus Guillermo Contreras Nuno: and and the the total summary is that the total uncertainty in alleys ranges from 1.8% to 3.4, with the bulk of PP and all pled data around 2% ish and lead lead around 2.5%.
Jesus Guillermo Contreras Nuno: And that's all from my side. Thank you very much.
774-R-013: Thank you very much.
774-R-013: So questions.
774-R-013: We thought it has one just one second.
774-R-013: Actually, I have 3 1st on page on page 10.
Jesus Guillermo Contreras Nuno: Yes.
774-R-013: Presumably the 2 scans at the back there at the right
774-R-013: off axis scans. I was wondering why you left some time between the on and the off axis scans, because if the non-factorization evolves versus time, you probably want to have those as close to each other as possible.
Jesus Guillermo Contreras Nuno: Oh, this I don't know. This was decided before I started doing this, and then has not been moved. Maybe Martino has an idea why it was selected like that originally.
774-R-013: Just a second.
774-R-013: So sorry. Your question is about the distance between the on axis and the offset scans, or the distance between the 2 offset scans. Oh, that's purely operational, because, okay, the offset scan for us is just an additional input to this luminous region feed. So the idea was that by doing the Vdms and the Lac. We have the bulk of our program done, and if the beam is lost we don't have to refill.
774-R-013: So it was just purely operational choice, let's say.
774-R-013: well, this might actually affect your feet. But
774-R-013: right? I mean, I had the same concerns. We already have trouble in Atlas, getting, as Tim will show, the on axis and the off axis scans intertwined to fully agree so with such a large time span. This may not be optimal. My second question is on page 15.
774-R-013: First, st I haven't quite understood what is the difference between the plots on the left and the right.
Jesus Guillermo Contreras Nuno: One is the movement in the horizontal direction and the other in the vertical.
774-R-013: Oh, okay. Now, why do you have half a percent of systematic from the data sample size and from the event selection, there should be no ambiguity in selecting lead-led events. Right.
Jesus Guillermo Contreras Nuno: They? We don't have the full detector working in in Alice, only the its 3 during the scans.
Jesus Guillermo Contreras Nuno: the the ideas, and and this is a detector that suffers when it has very few tracks or a lot of tracks.
Jesus Guillermo Contreras Nuno: So the the tracking algorithm, it has a lot of fakes, or it has problems finding the tracks. So if you have to select different to to have optimal track selection.
Jesus Guillermo Contreras Nuno: you have to. You have dependencies on occupancy.
Jesus Guillermo Contreras Nuno: and and then we do different selections for that.
Jesus Guillermo Contreras Nuno: Then you have also different selections. If if you start asking how many points you want in each of the layers, I mean, of these 6 layers. How many contributions you you should have? You have? The Chi square of the tracking is a track by track, and for the full vertex as an influence.
Jesus Guillermo Contreras Nuno: So you change also this criteria.
774-R-013: Yeah.
Jesus Guillermo Contreras Nuno: But the the main. The main issue comes from from the the maximum number of tracks that you can consider for the
Jesus Guillermo Contreras Nuno: for the vertex, because then the contribution of fate tracks start to get coming to mind topic.
774-R-013: Is this some kind of hidden centrality, dependence.
Jesus Guillermo Contreras Nuno: Yes, yes, for head-on collisions. You have a lot more tracks.
774-R-013: But Gabby is asking whether the systematic implies a dependence on the centrality of the event.
Jesus Guillermo Contreras Nuno: And
Jesus Guillermo Contreras Nuno: if I understand the question, then yes, the centrality of the event will pro produce more more tracks.
Jesus Guillermo Contreras Nuno: or or what? Maybe you can rephrase the question. I'm missing something.
774-R-013: I was just wondering, because this uncertainty seems rather large for an event selection, that whether actually what you are measuring is somehow more related to the, to the centrality that you choose. I mean, we did similar studies.
Jesus Guillermo Contreras Nuno: Yes.
774-R-013: And we got no centrality dependence. But I mean we have different detectors.
Jesus Guillermo Contreras Nuno: Yes, if we would have also the Tpc. But the Tpc is very low, then we would not have this issue.
774-R-013: Basically, I mean what this uncertainty is trying to probe is the fact that if you select too few tracks you have.
774-R-013: or you have bad resolution. If you select too many tracks we have, you have a lot of fakes. So you have to somehow decide a range where you like your multiplicity that you feel you are further away from the 2, of course, but of course, since you make a choice, then you have to, which is somehow arbitrary. You have to estimate an uncertainty. So we tried to vary the ranges. It's just that. And while I have the mind, what we call data, sample size is simply the statistical uncertainty.
774-R-013: Thank you. I think there is one more question from Vital
774-R-013: on page 17.
774-R-013: I am in left plot. I'm intrigued by the fact that in PP. The peak of your distribution is about a percent below one, and that leads me to ask whether for the Vdm scans the ratio is indeed one, or whether this reflects a change in the in the actual, absolute luminosity scale, I mean the discrepancy sorry in the absolute luminosity, scales from the 2 detector in PP,
774-R-013: I'm talking about the.
Jesus Guillermo Contreras Nuno: A definition.
Jesus Guillermo Contreras Nuno: Yes, yes.
774-R-013: They that this is centered at one. But it isn't obviously.
Jesus Guillermo Contreras Nuno: So the the Van Dermer scan would give you one.
774-R-013: So. Do you understand? Why do you understand why? The most probable answer is actually a percent off.
Jesus Guillermo Contreras Nuno: Not really sure about that, Martina. You did this part of the analysis. Do you remember 2,016.
774-R-013: Well, yes, I confirmed that in the Vdm scan, of course, what we can compare is only the specific luminosities, and these were agreeing perfectly during the Vdm scan. But then, as soon as we go to the standard filling scheme with trains, then we get, we start to see this difference in the ratio. So we conclude that one of the 2 behaves differently during physics trials than during the Vdm.
774-R-013: Thank you.
774-R-013: Vital, do you have no okay? Any.
774-R-013: Yes, just one second.
774-R-013: So, George, just for curiosity, because also, when Cms we see length scale.
774-R-013: I don't know whether this is also in Atlas, and if so, do we understand? Why?
774-R-013: The answer is, yes. Oh, yeah. Okay.
774-R-013: And what is the reason?
774-R-013: Just one sec.
774-R-013: You know, we have 2 microphones.
774-R-013: I've said that long enough. Well, to be honest. Strictly speaking, I don't know what the reason is, but to the extent that this difference deviation from one is much larger than the systematic uncertainty. It means that the modeling of the you know of the corrector and or the optics in the machine
774-R-013: is such that the calibration of the knobs is not perfect. There's nothing offensive about that. I mind you, that the intersecting storage rings in the seventies. The length scale was a very big issue for Vdm calibrations.
774-R-013: Let's see, why did you go?
774-R-013: Okay? I think Mickey might have an answer.
774-R-013: I have a guess. I'm not sure if I have an answer, but I have a guess. Of course, in PP. The Beta star is in the range of 20 meters.
774-R-013: so say in relative, an imperfection of maybe one micron or half a micron has significantly less effect than in lead lead. Where your beta star is 50 cm. Then I would expect. That is a significant part of the problem. Also, any imperfections from the optics from the triplet will
774-R-013: get much more significant if the beams are heavily squeezed as they typically are in lead lead during the scans where they are not in proton-proton.
774-R-013: Thank you.
774-R-013: So if no urgent questions, then we go to our 3rd speaker, Daniela, could you stop sharing? Please? Thank you again, and we go to Lhcb. And hear about their luminosity calibration methods.
774-R-013: Sorry one second.
774-R-013: let me just go to, okay, perfect.
774-R-013: Okay, yeah. Okay. Hi, I'm Danila. And I'm gonna present to you some some of the methods and techniques that employees for luminosity measurement. So luminosity.
Jesus Guillermo Contreras Nuno: Sorry. Sorry you are not sharing the mini screen. Could you please.
774-R-013: No, you! Why, it's not going on. Zoom sorry my fault.
774-R-013: Let me try.
Jesus Guillermo Contreras Nuno: Thanks a lot.
Jesus Guillermo Contreras Nuno: Now it works. Thanks.
774-R-013: Oh, okay, I'm surprised. Very good. Okay.
774-R-013: okay. So the luminosity is very important parameter both for the online and offline operations. So for the online. Of course it is relevant for driving the luminosity leveling. That is a key parameter for less operation, as you can see in this nice plot, where you can see that the luminosity Lacv is constantly leveled at a lower luminosity than Cns and atlas, and it is also required to guarantee detector safety of your online operations. As we say.
774-R-013: So instead, the offline luminosity is fundamental for physics, analysis that involves the measurement of absolute perception measurements.
774-R-013: as, for instance, the measurement of a cross section for the Dublin tech production. Another one had the biggest systematic uncertainty driven by the luminosity mentioned.
774-R-013: So let's go a bit in past so just a quick overview of the luminometers that were employed and implemented in a 1 and 2. There were many luminometers defined across all the detector in the different sub detectors. But there was no dedicated system.
774-R-013: and, for instance, the online luminosity monitoring was performed by measuring the transverse energy in the calorie method provided by the 11 0 0 trigger, the other trigger in the Lsp instead. For the offline analysis, there were many counters across the detector, so the number of neurons, the number of bits in the pressure detector
774-R-013: and the many quantities defined on the vertex locator detector. That is the closest detector to the interaction point in Acb, and indeed, the best criminal vectors were defined on the detector, such as the number of vertices because of their low beam, gas background, sensitivity, and the number of betacks registered within the data.
774-R-013: So regarding the luminosity measurement in round one. This was based, as I said, on the veil of emphasis for the Van Dermer and wind gas imaging calibration just for clarity, ie. Of course, the earth sketch of the veil, where you can see the luminous region, and how the tracks can be reconstructed when crossing the several layers of the veil
774-R-013: and the little tracks were used for propagation to physics conditions. The interaction cutting was done via log 0 meters. So, counting the number of diffraction and empty lines in the mean being crossing and subtracting the beam, gas and gas and gas beam interactions.
774-R-013: And one nice thing of this analysis is that you have to correct for the non-uniform reconstruction of tracks and vertices for the different position of the beans. 14 z. But you can see here the correction factor based on lacb simulations for the different proxy, luminosity, proxy. So tracks and vertices for different center of mass energy.
774-R-013: So the precision that was achieved was 1.16% combining the calibration from a band and beam gas imaging technique, and where the main systematics were driven by the overlapping the beam of drifts and beam-beam interaction
774-R-013: in Round 2 the analysis is still ongoing, but the strategy is based on the same round one analysis. So the exploitation available counter. So you can see here the stability of these 2 counters by their ratio across the whole rancho data, taking period with the Eloton Square of just 0 point 0 8%
774-R-013: across from the measurement. So so long, the absolute cross-section publications with the Cb quoted, 2% answer, stating the luminosity measurement. But this is expected to fall significantly once the full analysis is complete.
774-R-013: So let me now introduce the smog system that has been also introduced before by Martino, if I remember correctly. So this is a dedicated system in Lcb. That allows for injecting gas within the bin piper. And this is very useful for performing beam gas imaging that we'll talk about in a few moments
774-R-013: and the fixed target physics program. You can see here how this works. In the case of smog that was implemented in round one and round 2. The gas was injected throughout the whole bean pipe, while in for round 3 this has been upgraded to smog. 2, where a much higher density gas is injected just upstream of the Velope.
774-R-013: So, as we have seen before, at the
774-R-013: the luminosity, we can measure the luminosity also in this fixed target experiment of led, and in this case the luminosity can be directly measured by measuring the gas clocks in the vessel of the
774-R-013: or smog, but this was not possible in round one and rancho, because the gas pressure gauges that were used were not precise enough to perform an accurate measurement. So in rancho, for instance, the luminosity was measured by measuring the proton electron analysis in
774-R-013: proton helium conditions. And you can see here the results of this analysis where you can see the candidates of electron for this process
774-R-013: compared with the simulated distribution, both for the momentum and transverse momentum distribution.
774-R-013: This achieved a 6%. But now, with the new, the news system. So we have a much more precise gas flow gas flow control. And this will allow us to perform a direct measurement aiming at an offline, and 2%.
774-R-013: Also, the analysis of the luminosity in the round 2 based on the big high calibration is ongoing. You will hear more about in Naya's talk, and the idea behind it is to not measure the, to not calibrate the visible sigma or some counters, but instead of measuring the overlap integrated between the 2 beams by performing the beam glass imaging. So you
774-R-013: use the fact that the beams can interact with the gas that is injected to the smog, and then you can reconstruct the all the shape of the beam and their trajectories. So, for instance, here there is an example from run one measurement where you can see the beam shape of the Xz and YZ. Plane, and from their shape you can analytically reconstruct the overlap of the beam profile or the overlap integral.
774-R-013: And also in this case, as said, the run through measurement is not finalized yet, but we can expect in around 1%, and the internal review is ongoing.
774-R-013: So let me focus on a different topic. Now, we introduced before the concept of log 0 meter, so one can count number interaction, prevent by just counting the number of the fraction of the empty density.
774-R-013: and this gives you a good estimator because of the person, distribution, or interaction per events. This is a commonly used method, and it's very good, as it is insensitive to reconstruction biases in a very busy lens, and it is being.
774-R-013: It has been therefore used for one eventual measurement, both online and offline, but this has this advantage, that it does not work very well at high mu, as the probability of having no interaction period is quite low. So you have to integrate a lot of statistics to achieve a meaningful measurement.
774-R-013: You can use another method. That is just the average one where you compute the average value of your luminous proxy. That may be tracks, or whatever. This, of course, is much more simple with respect to the level 0, but it relies on long term stability of calibration constants and requires linearity inflow.
774-R-013: So, in addition to this method, so in Lseb or more of lab. It came with a new method for measuring the interaction. Rate. Data is not being published yet, but you can find some references here, and it is based on the probability generating function to extend both 0 and the average meter. So the idea behind it is to develop the
774-R-013: just test the luminometer response to one interaction as a function as a power series where there is a 3 parameter that must be was model must be lower than one. And given this formula, you can formalize the response of your in terms of a probability generating function after Milkerson distributed the interaction, and this, and you can get this
774-R-013: for one, a tier.
774-R-013: And just using that formula, you can define a new estimator. How it's done is just based on computing the average value of Z to the power. Na, where na is detector measurement, then you can define a new quantity by just taking the logarithm on this
774-R-013: average value that is imported here. And since on the previous formula, you see that this is directly proportional to the average value of your Poisson distribution. So this constitutes a new meter for the measurement. And you can also prove that the average and the dot 0 meters are just special cases over the probability generating function meter.
774-R-013: So why would you ever want to use this? The idea behind it is that both in log 0 and the average method. You may have biases in very highly populated events, and in one case, in the log 0 case, you just sample the very 1st bin of the solution, while in the other case you weight all the bins of your distribution milometer distribution. In the same way
774-R-013: in with this meter, by choosing this parameter in the range from 0 to one you can tune how much weight you want to give to any of your dominometer distribution. So here, for instance, we have an example of how this works. So you have a continuous transition from the long 0 meter. That is, the line at the bottom
774-R-013: to the average method by just defining this new quantity, this new estimator, based on the probability generating function and setting the Z value to this power of 2, the different hand. So now you have a different new parameter that can allow you to optimize your estimator, given your luminometer spectrum, and this method is being considered for run 3 offline measurement.
774-R-013: So, coming to the run, 3, there has been a huge upgrade of the Ledcb with respect to the run, 1, 2 data taking, indeed, as I said before, the luminosity of the online luminosity was provided by the process energy selected by the level 7 trigger. But now we have completely redesigned the data taking, and we have no more
774-R-013: level 0 trigger. And for this reason we have defined a lot of new online immunometers for the Landry that are based, for instance, on the currents in the rich photon device, the currents in neons, and the number of peaks in the safi and the velo, and many more, and we also have a new dedicated detector plume that has a very nice feature that is almost completely independent from the Acp Diq. State.
774-R-013: So it answer whenever there are several things, no matter the system and it provides both oops
774-R-013: both online and offline luminosity.
774-R-013: So I'll give you a very quick introduction to Luma. By the way, you will hear more about from Eduardo Eduardo store. So it is the main led.
774-R-013: and it is based on the same technology of the lucid detector in Atlas. And it is another scope composed of 48 photo multipliers energy carports pointing to the nominal interaction point in LCD, so maybe it's not very easy to see here. But this is a photo of the plume detector, and the photo multipliers are arranged in couples, and they are pointing to the interaction region that is outside of this slide
774-R-013: in this case, so it provides both average and the 2.4 sequence, and the visible is defined either with the average meter. So the sum of ABC counts for each single channel, or with the long 0 meter so counted the number against over ABC. Threshold per channel.
774-R-013: and you can see here a nice figure showing the the performance of the visible. So the trend of the visible meal in the 2024 scan. You can see how very nice shape you can obtain in this way, not to the comparison between the offline and the online measurement.
774-R-013: One of the biggest upgrading has been also the, as I said before, the detector that is closest to the mean spot that is just in this point, in this image, and the main difference between the run 3 and the one is that now it is a pixel detector and not a silicon sweep detector.
774-R-013: It is composed of 52 modules, so for a total of 41 million pixels, each having pitch size of 55 microns, and it is composed of 2 mobile phone values that retracts when stable wings are not stable in order to ensure the safety, the safety of the sensors, and when stable beams are declared, they are blown together, and
774-R-013: the innermost pixel of Tobago is just 5 away from the from the bean spot.
774-R-013: A nice novelty in the detector is its redoubt that is based on real time clustering on its active pixels. And you can see here a sketch of these few more words that this algorithm works that is implemented in the redoubt Fpga of the velo. So basically, you gather all together the active pixels from the veil, and it can sustain patterns
774-R-013: of active and inactive pixels found. You can reconstruct the class of pixels and computing the central
774-R-013: classic distribution. So the the product of this fumer is just the list of it's on the velo sensor for each passing at 50, at the 33rd 30 megas is
774-R-013: so. Why we care about this is that we have in this way the representative heats available at the readout level for each crossing ideally in real time. And you can use this information to provide the luminosity measurement. So the in it's a powerful proxy to measure the luminosity. Indeed, it has been exploited in
774-R-013: as a middle. We have talked about before, and then this is a very robust middle against the aging and validation damage of the detector.
774-R-013: and also the changes in a and because the number of you don't care about the average number of pixel that contributes to the classroom, but just the number of cluster on the sensor.
774-R-013: But the only potential problem. This method is nonlinearity, due to heat matching of a different practical insights that you know cannot resolve because of the finite size of the so given this premises, we have defined some luminosity counters that, and this allows for the 1st without available line.
774-R-013: high redundancy, and yet visibility and the shape of the accommodation regions of the video. So for the moment, we have just defined 8 counters for each available station, so defining for inner and 4 outer counters for each station. That sum up to a total of 208 diagnostic counters for the whole video.
774-R-013: I give you just a quick overview how this is implemented. This is a female sketch, or this is done in Fema, and the counters are divided by bunch plus in time. So they integrate in time using a running mean, and they are computed either with the average and about once every seconds.
774-R-013: And we have also the bunch crossing measurement done with below 0 meters. And in this case we integrate for a bit more time in order to accommodate enough statistics for every bunch crossing
774-R-013: some preliminary studies regarding linearity of this matrix that needs to be evaluated because of the possibility of heat merging. And you can see the very nice linearity both in Monte Carlo, and in real data.
774-R-013: Here you can see some calibration. These counters here on the left plot report to the calibration for one of the counters in A,
774-R-013: and this is very nice, as you can see the different acceptance of the
774-R-013: there are sensors as a function of the sensor position
774-R-013: inside, and you can also see the resulting calibration in the luminosity of each country, where you can see that the acceptance factor to provide a very nice agreement in luminosity between the different countries, different countries that are combined, all together with a team admin approach in order to have just one luminosity estimator for your line operations.
774-R-013: So here, of course, just few preliminary results. So they are very preliminary. But they are being gathered in in a paper
774-R-013: where I want to just show you that this needle is powerful, but you have to take into account the dependence on the switch opposition.
774-R-013: Indeed, it is quite sensitive to movements of the beam, namely, along the Z axis. So you can see here from simulation how this depends. Quite a lot of the acceptance of the changes. Quite a lot as a function of the mean position of the beam, and you can put a systematic view to the movement.
774-R-013: for instance, in July, and this corresponded just to at 0 point 2%.
774-R-013: And this could affect also in the spread of the production online measurement that without correction is about 0 point 5% and shrinks to 0 point 3%. Once corrected, I just want to mention that these plots are very, very preliminary, and you may take them. So this is a nice tool that can be used for online monitoring. In addition to
774-R-013: you can also use the fact that the position by by using this information to track the position of the people in real time. This is useful as a complementary information to those devices and existing.
774-R-013: and it can be useful for protecting the alignment accounting for the missed quarters.
774-R-013: So emitter has been implemented that relies on a definition linear estimator for each direction. XYZ. Using the normalized counters in this formula, here, where you have a few parameters.
774-R-013: So you have a vector of ways that are computed in Monte Carlo with the physical component analysis technique that I report here. Let's sketch this. So the idea is that you have. You have distribution of variables in a multi-dimensional space. And if you in Monte Carlo change the position of being just around one axis, you can diagonalize the space in order to get best combination of these
774-R-013: discount. And then you have some parameters, Alpha and Beta, that just take into account.
774-R-013: So here we've got a few preliminary results. For instance, I just mentioned to you that the Xy simulators compared to
774-R-013: left, right and up. This has been test in dedicated landscape with Position monitor by the
774-R-013: and you can see very nice agreement with the resolution for microphones every 3 seconds.
774-R-013: and just by circulating the statistical certainty of this measurement condition, one can put 4 microphones of precision every few milliseconds. So this can be very interesting for attractive position.
774-R-013: So with this, I'm not done. And just as a summary of what I presented you the current centers of rawan and measurements that are based on available of the Bing gas imaging technique where we expect an expected expected which is around 1%.
774-R-013: We also defined a new interaction counting meter based on the probability generating function, the and this is being commissioned for the offline, and maybe a way to go for the offline measurement, and I presented you also the new detector and the new meter based on below. It's both for measuring the immunosity and stuff.
774-R-013: And that's all.
774-R-013: Thank you very much.
774-R-013: So time for questions.
774-R-013: Okay, yeah.
774-R-013: Thanks. A lot. Very impressive. One question to this velo heat method you think in particular, in, say, physics condition, where you estimated it could give data like every millisecond. Does this also mean that it could give full bunch by bunch data. Every order of seconds
774-R-013: with a bit of improvement is that we can play with the distribution as much as we can if the humor allows us.
774-R-013: and we can just increase the number of counters across the bed or detector. And in this way you increase the information that you can integrate for each function, then you can actually measure much better statistical the position. So
774-R-013: maybe mostly out of curiosity. But it's an interesting information. For for instance, beam-beam studies because you have bunch by bunch orbit differences.
774-R-013: I actually have one. I actually have one question. So you mentioned for the value that you have to to estimate the acceptance from Monte Carlo. Simulation
774-R-013: is this something that you have can check in data? So when you, when you, depending on the Z position.
774-R-013: Yes, in round one. It was a Monte Carlo in run 2 main data. Actually, we use the colorimeter which is far away from the interaction point. So it doesn't depend on the zoom movements and collaborate with respect to that perfect thank you. On page 16 again.
774-R-013: I'm a bit slow, but my question may be
774-R-013: link to the fact that I don't quite understand the sketch on the right. You say that the head counting is robust against radiation damage
774-R-013: or high voltage changes, and I would have expected precisely the reverse. That head counting is very sensitive to pixels dropping out so could you clarify for me what's being stated here? Yeah, if you count the number of pixels, you're quite a lot sensitive, but if you count to the number of classes, so the. It's not pixels in the
774-R-013: in the cluster, if if you count clusters rather than pixel. Yes, that that, of course. I agree. Now, what is the relationship with the sketch on the right. Okay? And then also on the beam spot position with the Velo.
774-R-013: Quite aside from the detailed implementation there, do I understand qualitatively that what you are doing here is you are measuring the position of the beam spot from the spatial distribution of hits in the veto, which, of course, depends on where it is in the various dimensions. Is that the basic principle and that changes depending on where the events come from?
774-R-013: Yeah. But we integrate across. For instance, we are integrating over 3 cycles. So these images. So we are sensitive to the, to the centroid of the shape of the
774-R-013: I vaguely remember, and Mickey can maybe comment here that there is a way with certain beam position monitors which have only 4 electrodes
774-R-013: to determine not only the position, or, let's say, the displacement, but also the shape or the aspect ratio of the beam, and if that can be done with 4 electrodes, maybe it can be done with the many pixels you have.
774-R-013: so that you could have more information. Not just the position, but you could get at least an aspect. Ratio, maybe not a size, although the size would depend, may come in as well. But at least you know, dimensionless quantities.
774-R-013: Yes, this is this is something that was attempted. Maybe, actually, Manuel would be better to comment. This is for, say, specially wired Bpms, you can get the beam size. Estimate that way. Maybe maybe Manuel can tell you more in detail.
774-R-013: I don't know many days, but I think it was tried, and this didn't work. Think it may work, but it. They says they were done. I don't know if my I think it was Diego. I don't know if they are connected.
774-R-013: Diego was following this, but I don't think he's connected. Maybe tomorrow we can. We can answer that. But I think he didn't didn't work.
774-R-013: Yes.
774-R-013: so I'm curious about this neon currents as luminometers. Sorry I can't remember which slide it was. But okay, 1st question, is it the germs? And second is whether you use them as they are, or you have to somehow calibrate them, correct them for fluctuations of the gain due to temperature or humidity or gas mixture.
774-R-013: I'm just curious about that. I don't know much about this system.
774-R-013: So okay, no, they're not gems. 1st in Lhb, we have wires chamber and the calibration, and we also have currents for other detectors, for instance, the reach and the tracker, the cipher tracker. So all of them, they're calibrated against the main luminometer, and then we try to keep an eye on the aging, so the gain effect and everything is monitored. But the calibration is done against bloom is not an absolute one.
774-R-013: Elizabeth. Maybe you can comment how many counters we have offline?
774-R-013: Come on.
774-R-013: I think it's a bit in your talk, Edward. I guess. Yeah, there is a list of all the counters we implemented this year, but we have counter at different levels. So recurrence clusters in the firmware for developer. For the sci-fi, then we have all the offline quantity like tracks, clusters it everything. So we will have competition for the highest number of fluminometers.
774-R-013: Very good.
774-R-013: Any more questions. We'll start to spit our Hf into every channel. Okay, actually, we might do that.
774-R-013: Okay.
774-R-013: thank you very much. I think there are no more questions. So we come to a close, but also my weather app says that tomorrow afternoon it should be reasonably sunny, and perhaps we could take a photo of the group outside
774-R-013: during the during the afternoon tea break so you can put on your best suits in the afternoon.
774-R-013: Okay, thank you very much. Everybody see you in the morning. Thanks. All
774-R-013: varies depending on this.
774-R-013: But in Pcc. We don't have per module calibration, because you can't have that, but we can have per layer, and this was done before, I think, in in early round 2.