1 00:00:02,250 --> 00:00:04,890 I'm sharing now let me know if you 2 00:00:07,470 --> 00:00:08,190 Yes 3 00:00:09,719 --> 00:00:19,979 Okay. Yes. So yeah a bit of CPM metrology but mainly focusing on VCB and metal 4 00:00:19,979 --> 00:00:28,439 measurement of PCB with bs so adding a bit of strangeness into this game. So as we 5 00:00:28,469 --> 00:00:33,989 very well know CGN mechanism very well established. So I'm not going to the data 6 00:00:33,989 --> 00:00:40,049 here, BD Ks contribute to the measurement of angles with CP violation measurements. 7 00:00:41,069 --> 00:00:46,919 We get also sides from simulation but then we got these measurement of VC V and VB 8 00:00:47,279 --> 00:00:52,919 that actually have these long standing puzzle, which is the difference between 9 00:00:53,159 --> 00:00:58,529 the increase even death because it's measurements that are here in the cross in 10 00:00:58,529 --> 00:01:03,059 the in the plot here, eventually Measurement of up VCB. And this is the 11 00:01:03,059 --> 00:01:09,389 average of the XYZ measurement. And these are in some disagreement, the level of 12 00:01:09,419 --> 00:01:15,629 three C. This was just, let's say measurement for form at the factories, but 13 00:01:15,629 --> 00:01:21,569 any CV entered the game a few years ago with the first measurement of VB over VCB 14 00:01:21,929 --> 00:01:27,419 done with a completely different system. So, the lambda BD Ks are used here and 15 00:01:27,419 --> 00:01:32,789 they bring a very independent formation with respect to what we use before. So, in 16 00:01:32,789 --> 00:01:37,199 this respect, so bringing additional independent formations to the BS sector is 17 00:01:37,199 --> 00:01:46,289 very promising, both for VB and VCP. For VCP, that is the focus of this talk. We 18 00:01:46,289 --> 00:01:51,449 have some really potential here and these two together the indeed the theoretical 19 00:01:51,449 --> 00:01:57,899 work we already heard the by Nico some of that and there are also on the market 20 00:01:58,889 --> 00:02:04,709 lattice QC D collision that we can profit, some of them are already quite precise. 21 00:02:05,069 --> 00:02:10,379 And we can profit those from calculation the full code spectrum for bsds new 22 00:02:10,379 --> 00:02:17,009 decays. So we can use vsds new decays and yes, and to the S star indicates to 23 00:02:17,009 --> 00:02:23,159 extract the first measurement of, of VCB. From from that. And, by the way, on the 24 00:02:23,159 --> 00:02:29,339 last lap, this calculation of BS should be even more easy, let's say because of the 25 00:02:29,339 --> 00:02:36,359 fact that the S stranger is earlier than the U and D that are the spectator cork in 26 00:02:36,359 --> 00:02:38,279 the B and D is allowed to get 27 00:02:39,750 --> 00:02:46,080 to have a more precise calculation principle. So, at the ECB, we have a lot 28 00:02:46,080 --> 00:02:52,050 of potential on these because we produce a lot of BS medicine. And, and so which 29 00:02:52,050 --> 00:02:57,120 means at the end of the day, we can store samples that comprise several hundred 30 00:02:57,120 --> 00:03:03,150 thousand of the SDKs and indeed, the I will show you the first measurement of VCB 31 00:03:03,150 --> 00:03:10,770 using vs yes and vsds starting in UDK is collected by any sibling. So, the first 32 00:03:10,770 --> 00:03:15,750 style challenging in this kind of measurement is to know are many BSc 33 00:03:15,750 --> 00:03:22,470 producing in your environment. And this is a problem because the cross section for 34 00:03:22,500 --> 00:03:30,180 the production of these 1000 collider is not very precise these will bring the 35 00:03:30,270 --> 00:03:36,540 largest uncertainty in your measurement of VCB. But you can overcome these by using a 36 00:03:36,540 --> 00:03:41,220 normalization channel and explore it for instance a channel that is very well known 37 00:03:41,220 --> 00:03:46,050 and that is very, very similar to your seat now. So in this case, we use the V 38 00:03:46,050 --> 00:03:51,960 zero to Demian u and v zero to determine your DK which are re constructed in the 39 00:03:51,960 --> 00:03:58,260 same data set. So we can send cross section we know in the ratio, but also we 40 00:03:58,260 --> 00:04:03,510 also profit from suppression of systematics in the measurement because we 41 00:04:03,510 --> 00:04:09,840 will use the same finite state for the GI. So, here you can see the very mass of the 42 00:04:09,840 --> 00:04:17,670 kk five finite state and the peak of the DS that is our signal. And when you 43 00:04:17,670 --> 00:04:22,500 combine these deals with immune displaces from the primary vertex, so to identify 44 00:04:23,070 --> 00:04:29,550 the immune system coming from a B, yes, and the D Mew, so the D in the same body 45 00:04:29,550 --> 00:04:35,190 mass of the kk pi, so, we use the cabbie Bo suppressive mode. So, we have 46 00:04:35,220 --> 00:04:40,500 anonymization channel which bring less statistics than our signal This is not a 47 00:04:40,500 --> 00:04:45,870 problem because we are not afraid of statistics here we are not limited by 48 00:04:45,870 --> 00:04:50,250 statistic but by the external input that we have in our measurement. Mainly the 49 00:04:50,250 --> 00:04:55,260 fact that we have any way to know which is the relative production of s to be zero. 50 00:04:55,260 --> 00:05:01,230 So we need an input the FS over FB, the fragmentation fraction ratios, which is 51 00:05:01,230 --> 00:05:09,510 known by precise measurement around the 5% and will bring a dominance of around 2.5% 52 00:05:09,510 --> 00:05:17,400 on VCP. So, this is our sample that we will use. And then we have to of course, 53 00:05:17,940 --> 00:05:24,780 discriminate our signal so that yes to DSP new MPs to the start menu decay from these 54 00:05:24,810 --> 00:05:31,590 increases samples and since we are missing the neutrino here, we cannot close the 55 00:05:31,590 --> 00:05:37,710 kinematics like in the factories and we don't have a clean beaker to identify our 56 00:05:37,710 --> 00:05:42,900 signal for instant when you look at the visible mass. But anyway, you can recover 57 00:05:42,900 --> 00:05:48,000 part of the of the missing neutrino with these additional valuable the carotid 58 00:05:48,000 --> 00:05:54,270 mass. And so you you recover the part that is conserved along the direction of the of 59 00:05:54,270 --> 00:05:59,640 the B and these allow you to have an hour pika and to discriminate the different 60 00:05:59,640 --> 00:06:05,040 countries. In the increases sample, so you can see in the plot here, the bsts menu, 61 00:06:05,280 --> 00:06:10,500 and that DPS, the star unions that are very well separated from the background 62 00:06:10,500 --> 00:06:16,170 that are his physics background in combinatorics. Here with these a variable 63 00:06:16,290 --> 00:06:20,910 that was already exploited in this paper, which was a measurement of DBS lifetime. 64 00:06:21,750 --> 00:06:28,290 The third challenge in this business is the fact that without the momentum of the 65 00:06:28,290 --> 00:06:32,970 B, So, because of this Miss neutrino, you cannot have the rest frame kinematics that 66 00:06:32,970 --> 00:06:37,800 he will use to make a measurement of VCB because we see V is extracted as a 67 00:06:38,580 --> 00:06:43,800 measurement of the differential decay rate as a function of the recalled variable w 68 00:06:43,800 --> 00:06:49,200 which is the energy of dt, basically in the rest frame, but you don't have this 69 00:06:49,200 --> 00:06:55,320 frame. So you can work with approximation, but here we attempt a different approach, 70 00:06:55,470 --> 00:07:02,460 which was a need a buddy you know, working very well Which is Okay, anyway, we get 71 00:07:02,460 --> 00:07:08,130 accustomed to Bollywood which is fully reconstructed, and it's I liquidated with 72 00:07:08,250 --> 00:07:13,770 the recoil valuables. So, this body where is the transverse momentum of the D, but 73 00:07:13,770 --> 00:07:17,970 transverse with respect to the B fi distance. So, in this sketch here is 74 00:07:17,970 --> 00:07:26,280 reported. And you can see in the plot in MonteCarlo, that Deezer bada bada which is 75 00:07:26,280 --> 00:07:32,430 fully restarted at a very good resolution, then it's highly correlated with the 76 00:07:32,430 --> 00:07:38,400 record Body Body simulation, and which means that at the end, you can use these 77 00:07:38,400 --> 00:07:44,760 valuable to extract all the information that you will use neater with with that 78 00:07:44,760 --> 00:07:50,460 view. And, and so, which means that you can extract the full factor which are 79 00:07:50,460 --> 00:07:56,250 function of value using these these valuable and so perform a measurement of 80 00:07:56,280 --> 00:08:02,850 ABCD and different factors by making a differentiation measurement in the LM 81 00:08:02,850 --> 00:08:07,770 curve volleyball to discriminate signal and background and differential in this 82 00:08:07,800 --> 00:08:15,480 paper to determine the CB and infer factors together, because we already heard 83 00:08:15,480 --> 00:08:22,770 from Nico's talk that you need them to to instructor again VCB. So, by doing a 84 00:08:22,770 --> 00:08:31,410 template feed in these two dimensional plane this space at the end you can assess 85 00:08:31,410 --> 00:08:38,520 these information. And in our eyes We also use some constraints from the four 86 00:08:38,520 --> 00:08:43,470 different factors. So to improve precision from these large disk cases, because 87 00:08:43,470 --> 00:08:47,940 correlation that there was mentioning at the beginning, and of course, as I said, 88 00:08:47,940 --> 00:08:53,760 you need some reference measurement, which is then the measurement of the ease of the 89 00:08:53,760 --> 00:09:01,680 Bz v zero the case that I presented the missing sample. So through a similar 90 00:09:01,680 --> 00:09:07,320 feature and another external input the are the potential ratio of course of your ddk 91 00:09:07,320 --> 00:09:13,950 is of the zero maximum use as the case is as a reference and Fs over D, which are 92 00:09:13,980 --> 00:09:20,550 delimitation at the end of this method. So, this is the result of defeat. So, you 93 00:09:20,550 --> 00:09:28,080 can see the production of defeat in the two dimension the karate master and the 94 00:09:28,080 --> 00:09:33,810 bird and you can see the good value of these feet 95 00:09:35,130 --> 00:09:42,450 and at the end, we we are measuring for factors a serie BCD into form factor 96 00:09:42,450 --> 00:09:50,790 parameterization because there was some idea some some years ago that by 97 00:09:50,790 --> 00:09:56,820 reanalyzing Bell data that the discrepancy of of the inquisitive and ask is 98 00:09:56,820 --> 00:10:01,440 measurement. Cool depends on how on how you put him criteria for factor. So, we 99 00:10:01,440 --> 00:10:05,940 tested the measurements with different parameterization This is the more general 100 00:10:05,940 --> 00:10:12,660 model as you can add the GL and nikora dimension it and this is the value of PCB 101 00:10:12,660 --> 00:10:17,220 that we extracted from by by parameterizing the foot factor using the 102 00:10:17,220 --> 00:10:26,310 bgl model. So is a measurement of VCD which is with a good procedure and but at 103 00:10:26,310 --> 00:10:30,300 the end as you can see here we disentangled uncertainty contribution, so 104 00:10:30,300 --> 00:10:35,400 static statistical only the systematic as usual but then you have these external 105 00:10:35,400 --> 00:10:42,120 input contribution which are the dominant contribution and this is the result of 106 00:10:42,150 --> 00:10:49,800 defeater when you do the measurement using the CLM parameterization. And at the end 107 00:10:49,800 --> 00:10:55,020 of the day, there is no big difference in VCB. So even when you can see there the 108 00:10:55,020 --> 00:11:00,000 correlation between these two numbers, they are perfect agreement. So we know 109 00:11:00,000 --> 00:11:06,150 difference. Now dependents actually have VCB with respect to the parameterization, 110 00:11:06,150 --> 00:11:12,690 used extracted dissolved, and you can see also these in the plot here that show the 111 00:11:12,720 --> 00:11:18,390 projection of defeater with background subtracted. So these only signal on the 112 00:11:18,390 --> 00:11:25,380 left for TBS to DSP new on the right for the DSPs 30 new when you compare the two 113 00:11:25,380 --> 00:11:34,020 different feet down with the CLN or the bgl model, so the dots are the data back 114 00:11:34,020 --> 00:11:42,000 on subtracted, and the projection is the result of the feet. As I said a systematic 115 00:11:42,000 --> 00:11:46,950 uncertainty are just mediated by the external inputs. So I will not spend much 116 00:11:46,980 --> 00:11:51,150 more time on these I just want to say that there's a byproduct of the analysis we 117 00:11:51,150 --> 00:11:57,270 have also not only the measurement of VCB and four factor parameters, but also some 118 00:11:57,300 --> 00:12:04,890 ratios and branchy ratio, which are very interesting. To test also order like su 119 00:12:04,890 --> 00:12:13,560 three for instance, order theory assumption Okay. Then now I switch to a 120 00:12:13,560 --> 00:12:20,760 related the measurement, which is a measurement of the W distribution in VST s 121 00:12:20,760 --> 00:12:26,310 timing is the case and this concern basically deeper study of different factor 122 00:12:26,310 --> 00:12:33,510 if you want to support the fact that indeed the demand the DCP extracted from 123 00:12:33,510 --> 00:12:41,010 the previous analysis indeed, different parts are very well modeled. So, in these 124 00:12:41,010 --> 00:12:45,510 analogies, we are using an independent data set that the one used for the PCB 125 00:12:45,510 --> 00:12:53,850 measurement. And we are going to focus on bsds starting in UDK, where the d s star 126 00:12:53,970 --> 00:12:59,880 is fully reconstructed in the case of the two IDs and a photon. So, the photon here 127 00:12:59,880 --> 00:13:05,280 is Very soft as you can see from the PT spectrum here constructed on the laughter, 128 00:13:05,430 --> 00:13:12,600 but we anyway are able to reconstruct the DSR peak that you can see in the body mass 129 00:13:12,600 --> 00:13:18,600 of the DS gamma system in this plot and subtract the background here and using 130 00:13:18,600 --> 00:13:25,110 just the signal in this speaker, we are able to perform a measurement of the W 131 00:13:25,110 --> 00:13:31,440 shape. So of the record variable. As I said, before, you cannot reconstruct fully 132 00:13:31,440 --> 00:13:36,030 this variable, but you can make a summation based for instance of some 133 00:13:36,330 --> 00:13:42,450 multivariate analysis. And the idea that you you been in this approximate variable, 134 00:13:42,720 --> 00:13:47,490 and you make a feat in each being for the sample composition using a crafted master. 135 00:13:47,730 --> 00:13:53,580 And then you can extract the shape of your signal and unfolding these using Monte 136 00:13:53,580 --> 00:14:00,660 Carlo to unfold the solution and efficiency. You can then use You have this 137 00:14:00,660 --> 00:14:05,520 spectrum here constructed of W that you can compare for instance, with 138 00:14:05,610 --> 00:14:12,000 parameterization. They're either from the VC v ni is in the GL and in the CA CLM 139 00:14:12,000 --> 00:14:16,650 case, and you can see very good agreement. And with this background also 140 00:14:18,240 --> 00:14:21,930 phenomenologist can play can work to extract or so 141 00:14:22,020 --> 00:14:31,020 data for model. So, in summary, I just show you the first measurement of VCB 142 00:14:31,710 --> 00:14:39,090 presented a mystery made another collider and the first one using VST s. And yes, 143 00:14:39,180 --> 00:14:47,940 the star unity case, we get the Deezer result for the CLR and for the DCP in the 144 00:14:47,940 --> 00:14:53,550 cillian and vgl parameterization that show no difference between each other and we 145 00:14:53,670 --> 00:14:57,330 are in agreement with both the US presenting credit measurement and that 146 00:14:57,330 --> 00:15:01,860 report here in this plot a summary of all the pieces Just measurements. So you see 147 00:15:01,860 --> 00:15:05,010 all these point are the previous measurement done 148 00:15:05,100 --> 00:15:07,500 at the factories, but actually 149 00:15:07,770 --> 00:15:14,550 also, so let's say in a blasting mines Collider, and which average to the green 150 00:15:14,550 --> 00:15:16,620 band here, which is the average of this 151 00:15:16,620 --> 00:15:16,980 crazy 152 00:15:17,520 --> 00:15:18,330 measurement 153 00:15:19,020 --> 00:15:25,050 without the LSP booth and in the orange you have the average of the increases 154 00:15:25,050 --> 00:15:30,060 measurement. You see our measurement is in between It's okay, it's maybe more or 155 00:15:30,060 --> 00:15:34,110 green increases the point but okay, we don't have the precision here, 156 00:15:34,350 --> 00:15:38,490 unfortunately to say something prompted. And that's all. 157 00:15:41,490 --> 00:15:42,570 Thank you. You've got 158 00:15:44,520 --> 00:15:46,050 other questions for me. 159 00:15:49,650 --> 00:15:54,720 I have a couple question on page nine. Yes. 160 00:15:58,830 --> 00:16:05,550 Thank you. So the fifth The following software basically not. Okay. I think it's 161 00:16:05,550 --> 00:16:10,110 very good, very nice analysis, just to understand that you're here you're not 162 00:16:10,110 --> 00:16:18,420 normalizing to be zero into star. So, I think that you use these normalization not 163 00:16:18,420 --> 00:16:24,510 only for the branching ratio, but also for B Yes, that you have in these in about 164 00:16:25,860 --> 00:16:34,470 this case, since also the the rate of B zero into the star new depends on VCB. I 165 00:16:34,470 --> 00:16:38,370 think that you should have some similarity here or at least you lose a beat to the 166 00:16:38,370 --> 00:16:40,290 sensitivity in the ratio of the two 167 00:16:40,950 --> 00:16:47,490 or not. So the point is, is the fact that we are using the measure the consideration 168 00:16:48,120 --> 00:16:54,990 Okay, we are not making noises of like here the composing heat as differential 169 00:16:54,990 --> 00:17:01,230 decay rate or inferring the potential ratio of the pieces From the failure of 170 00:17:01,230 --> 00:17:08,550 the CPM for factor measure the factors. So this is a just a measurement that is used 171 00:17:08,550 --> 00:17:14,760 just to set the scale at let's say. So there is no silly circularity because they 172 00:17:14,790 --> 00:17:16,350 use the measure 173 00:17:17,579 --> 00:17:18,209 number. 174 00:17:19,980 --> 00:17:21,630 I don't know if I'm clear enough. 175 00:17:23,130 --> 00:17:27,510 not usually don't use a DDD user that you add in is 176 00:17:30,240 --> 00:17:38,220 yes, you use the EDA, of course. But this is a measurement of the so you just see 177 00:17:38,220 --> 00:17:39,840 the upset of Is that so? 178 00:17:40,470 --> 00:17:44,940 So you don't have an explicit dependence on the No, no, no. And then a second 179 00:17:44,940 --> 00:17:50,850 question. Sorry, Jonathan. To understand better in you use these two variables that 180 00:17:50,850 --> 00:17:56,250 are I think, strongly correlated in the feet that because you obtain one in terms 181 00:17:56,250 --> 00:18:04,620 of the other no is not usually one would like to have in DC would like to have some 182 00:18:05,370 --> 00:18:09,900 variables that are not so correlated in this case, of course, okay you cannot 183 00:18:09,900 --> 00:18:15,930 factorize them you use a plain English. Yes. But in any case you have a strong 184 00:18:15,930 --> 00:18:20,940 correlation between them, because you obtain the incorrect internals of the 185 00:18:20,940 --> 00:18:21,420 other. 186 00:18:22,350 --> 00:18:26,880 So, yes, you're right that they are highly correlated. 187 00:18:28,380 --> 00:18:35,430 So, I yeah, they are very correlated, say, but the there is one fact that they didn't 188 00:18:35,430 --> 00:18:41,310 present here that they didn't put any plot because of Of course of time constraint in 189 00:18:41,310 --> 00:18:45,210 this plane, this to the plane, the good thing is that 190 00:18:47,070 --> 00:18:49,950 the signal and the background are committing 191 00:18:49,950 --> 00:18:55,500 very different region. So it's not only anchor alone that allow you to separate 192 00:18:55,500 --> 00:18:59,640 the different component but it's actually the to the plane first point, second 193 00:18:59,640 --> 00:19:03,660 point, you That they even if they are correlated, we don't care because we are 194 00:19:03,660 --> 00:19:10,110 doing we are modeling this correlation. So, the full information is inside in the 195 00:19:10,110 --> 00:19:17,910 2d template. So that so you are not losing, actually you are gaining it 196 00:19:18,210 --> 00:19:26,010 because the anchor allows you with the people to either battle discrimination of 197 00:19:26,010 --> 00:19:30,450 signal and background in the plane, but the anchor didn't don't bring any 198 00:19:30,450 --> 00:19:36,630 information the fourth factor is barely dependent on the fourth factor, while on 199 00:19:36,630 --> 00:19:41,280 the other end the pair is highly depend on the four factor so he brings all the 200 00:19:41,280 --> 00:19:42,720 information on the form factor. 201 00:19:44,700 --> 00:19:46,560 Looking at again, 202 00:19:47,850 --> 00:19:57,570 curiosity on page 20 like you can go to Yes. Okay, yes. So basically you can hear 203 00:19:57,810 --> 00:20:03,030 separate things out for the start is in the Yes or no? Do you think that you have 204 00:20:03,030 --> 00:20:08,520 a son? Yes, that come from the star key. So. 205 00:20:10,800 --> 00:20:15,240 So yes. So, so basically you have to separate the two sample. 206 00:20:15,419 --> 00:20:21,509 Yeah, yeah, but you do it in defeat. So they you are feeding the inclusive sample 207 00:20:21,509 --> 00:20:28,019 all together. So here in these the peak of the DS, there is of course, everything. So 208 00:20:28,019 --> 00:20:34,139 there are also DS coming from the esta which is the dominant component. And then 209 00:20:34,139 --> 00:20:39,629 when you look at in the in the 2d plane here shows us the projection, but when you 210 00:20:39,659 --> 00:20:45,449 look in the plane of the increase sample, then you can discriminate the different 211 00:20:45,449 --> 00:20:50,519 components. And this is actually the points know that, indeed you can you're 212 00:20:50,519 --> 00:20:57,449 making a simultaneous analysis of PS, DS and PS DS star, where vcv is a common 213 00:20:57,449 --> 00:21:05,699 parameter. So you're you're profiting From analyzing them simultaneously and these 214 00:21:06,029 --> 00:21:14,219 can be done because they use these people if you have to make the approximated w for 215 00:21:14,219 --> 00:21:19,829 one or the other you will lose a sensitivity is one of the two because you 216 00:21:19,829 --> 00:21:25,499 have to make a choice to approximating the increase and polar for to have a gain 217 00:21:25,499 --> 00:21:31,949 sensitivity in one sample on the other through these people you can simulate a 218 00:21:33,149 --> 00:21:37,859 fit them, analyze them without losing sensitivity in one of the two. 219 00:21:39,180 --> 00:21:40,350 Okay, thank you very much. 220 00:21:44,670 --> 00:21:45,990 Are there more questions? 221 00:21:50,520 --> 00:21:54,870 Yes, sir. Mark, please. You should be able to ask. 222 00:21:56,310 --> 00:21:59,820 Okay. Yeah, thanks. I was just wondering if you could mention a few words about the 223 00:21:59,820 --> 00:22:03,720 process. For the future given the statistical uncertainty is already already 224 00:22:03,720 --> 00:22:04,410 the smoothest 225 00:22:06,120 --> 00:22:15,540 Okay, so, about prospect here. So, first comment is that the same method can be 226 00:22:15,540 --> 00:22:21,090 applied to the zeros, finding the proper minimization, let's say which will be 227 00:22:21,090 --> 00:22:26,700 another channel but we have already the idea here and you then don't you get read 228 00:22:26,700 --> 00:22:32,790 from the input data subjective which is the dominant contribution. Then the other 229 00:22:32,790 --> 00:22:39,780 systematic that you have here are just, you know, on the experimental method that 230 00:22:39,780 --> 00:22:45,810 you use that can be of course improved. And so in that case would be zero the 231 00:22:45,810 --> 00:22:52,020 dominant contribution will be the brain shift ratios of the channel, normalization 232 00:22:52,020 --> 00:22:59,550 channel that you will use. And at the end of the day, you will love precision which 233 00:22:59,550 --> 00:23:05,040 is leaving Bye, bye bye that external input, so it will be the same of 234 00:23:05,070 --> 00:23:12,150 measurement at the factories. So yeah, that's a limitation of this method, of 235 00:23:12,150 --> 00:23:20,910 course. And here for DBS First, you have to improve on Fs over fd. So for instance, 236 00:23:20,940 --> 00:23:27,150 with new data in two MB around three and beyond the first year to improve on your 237 00:23:27,150 --> 00:23:33,480 input, and then you can improve on this measure, or you can exploit maybe other 238 00:23:33,750 --> 00:23:39,750 other thing like for instance, we know that Fs over fd depends on the beauty of 239 00:23:39,750 --> 00:23:46,560 the BS. So you can think of making these measurements in beings of the beauty of 240 00:23:46,560 --> 00:23:54,870 the BS and measuring then there's loads of these dependencies in an in a separate 241 00:23:54,870 --> 00:24:03,990 sample like we already do, using BST Say file that is 02 tips ik for instance, then 242 00:24:03,990 --> 00:24:08,700 you can get this load from these external measurement which can be done at very high 243 00:24:08,700 --> 00:24:17,010 precision and measure here simultaneously VCB vs Fs over fd using that though the 244 00:24:17,010 --> 00:24:17,880 input as an 245 00:24:19,529 --> 00:24:20,579 external measurement. 246 00:24:24,930 --> 00:24:26,250 Okay, very clear. Thank you. 247 00:24:35,250 --> 00:24:37,320 Additional questions or comments? 248 00:24:50,160 --> 00:24:50,730 If 249 00:24:52,200 --> 00:24:53,070 not done 250 00:24:56,940 --> 00:24:57,780 maybe 251 00:25:00,240 --> 00:25:02,010 Maybe we can close the session here.