So we will record the seminar, and we can start.
Thank you for the introduction, and thank you for the invitation. I just learned some of the things I'm arguing out. Thanks so much for the introduction. So it is a big pleasure, actually, rather for a lab that is actually involved with liquidote, so in a way, I mean, it's kind of, um… A big pleasure, in a way, to introduce liquidote to you, but maybe you may have heard some about that. Um, so, the name of the game is about, uh, I mean, going against transparency, what we have been doing for forever almost when it comes to detection.
The first question basically would be why Ecuador? Why we want to basically look for yet another technology for detection? And there are many good reasons for that, but let me try to kick off by throwing the big reason. So one of the big reasons, of course, that right now we have is that we are.
Um, I'm even surprised in that way. We have discovered model that basically can be characterized and absolutely stunning success. But in fact, we're also surprised by the fact that this is a mystery. The success of the standard model in many ways, and we know the reason for that is because it is incomplete. We know right now.
That the standard model, despite its success, is incomplete, and this in itself is kind of a paradox, and because the question is, what is actually, basically, what is missing, and where is that, basically, these missing elements, essentially, of new physics? And this is why, long story short, we want to have, basically.
explore nature better and better with higher precision, and it is to try to basically try to see a hint for these, uh, new possible physics. And this is, despite, I mean, the huge effort and the theory of possible.
It's clear that this is about basically compelling new experiments with further insensitivity by controlled backgrounds, higher efficiency, and so on and so forth. So we are facing a major experimental target, uh, problem, and this is exactly why, in a way.
We're trying to improve our detectors, our ability to see the nature deeper and deeper.
So let me first kick off with a little disclaimer. I'm a nutritional physicist. I'm going to try to talk about a technology from a more generic way. You may notice that I'm going to be talking about neutrinosity more than maybe I should, but I will use it as an example. But if you have any questions regarding your specific expertise, I will try to address that.
And, uh, bear with me in the debate. And, um, there you go. So I think that, uh, Liquido can go well beyond the neutrino, basically, scenario, and this is very effective on some modified feature of the technology, so… In nuclear detectors, in fact, we have these beautiful pictures when it comes to our detectors of these supergiving, a Nobel Prize 2015 for the discovery of neutrino simulations, or one contribution, very important contribution to that, and it's not the only one. And, um, when it comes to these kind of detectors.
We typically, uh, the reason why detectors are very large is because cross-section of neutrinos is extremely low. This is just a feature of weak interaction. Long story short. And I'm going to disappoint you right away. I don't have a way to prove the cross-section of the neutrino, so the only thing we're going to do is just make our detectors possibly better.
So essentially, with those fewer cleaners that interact, they used to basically learn more and more so that we actually basically get the most of these rare opportunity to see neutrino seat.
Um, you would see, actually, that these detectors are one of the main features is that if you want to make a huge detector, you may ask yourself, I mean, what is the problem with the neutrino detectors? Well, it's cost, long story short, if you want to have a huge detector, and you actually want it to basically cover these huge volumes, you need to simplify it.
Um, as much as you can, and that implies within compromise, long story short, you lose information. Um, and this is to allow to send the name of the game, signatures were discovered, and it has been a challenge that, honestly speaking, and we're still fighting, I would say that we're fighting every single day.
And it's about basically trying to make something that is cost-effective, as simple as we can to lower the cost, and at the same time, as complex enough to get extract as much information from your interactions.
And a long story short, I mean, this implies typically, basically, I'm going to highlight some examples, backgrounds are there. And whenever you see backgrounds that we cannot recognize signal from background, very often I'd like to see this way. This means technology is a limitation, typically, but especially in neutrinus, maybe not necessarily the same when you go to drivers.
different rationality when it comes to addiction, but to a large extent, essentially, whenever you get these background issues, a lot of them is technology. Technology basically is running out, running out of ammunition, um, capabilities, handles, and this is basically what it comes down. So, let me give you an example.
of a beautiful detector, Nobel Prize also. This is no detector that now has become the snow class experiment. Uh, so this detector basically has an acrylic, and we have now scintillator. It used to be heavy water inside, and there is basically this, we call it this pattern where the photomulators are around. You can see the simplicity.
by the end of these kind of machines, and, um, and this is basically kind of what we've been doing. I mean, this is one of the most beautiful experiments, architecture that we have done along the lines. But this is kind of the… this basically gives you the spirit of what we do.
Long story short, we have this volume where the energy interactions are going to be seen, and everything else is about trying to understand the backgrounds. And let me give you some numbers so you appreciate that.
The main purpose of these detectors is that they have no pad. Whenever you actually get your detective SH, you get a flash of light. This is proportional to M. You say, okay, something hit me, but you don't have a clue of what actually hit you, generally. And this implies, essentially, this vector has to be shielded.
You have to basically surrounding basically shields, and sometimes you can use even the planet overbound as a shielding because it's cosmogenic, so basically it's unavoidable. And to a large extent, what I'm going to try to convince you to be seminal, and this is all about technology. The technology is running out of fuel, in a way.
And this is going to basically the problem. So let's consider, for example, these photomultipliers, beautifully, and they are put apart. You may wonder why do they put this space? This is wasting a huge amount of volume. As a matter of fact, this volume that you see here is better than 10% of the total volume that is actually… that it has been excavated. And this excavation has costed basically hundreds of millions of years.
Whatever you prefer. And actually, the rest of the volume, this volume, this buffer volume, is already basically almost 3 times bigger than the volume that we used in the neutrinus, and if you actually consider that is another external volume that you use for muons, uh, as a matter of fact, actually is even 10 times bigger. So, long story short, you put.
let's say 100 million euros, basically, into the system, and out of that, only 10% of your volume is being used for neutrino.
This is not very impressive, because you think about the numbers, but the reality is, we don't know how to do it any better, but we, up to now, we don't know how to do it any better.
The reason why the photo multipliers of these so-called buffer is their capacity to some extent, but actually, basically, you make the detector three times smaller, is that there is reductivity from the forecast of the photon multipliers, and this reflectivity is overkilling, so you just put your volume away.
And of course, this is great, but at the same time, you lost an immense amount of volume. And the other problem basically with cosmogenics is that these detectors don't have any tracking.
No whatsoever. In fact, these detectors are very good to say, my newest study here, my mion basically went out there, you have an entry exit point, and then you basically stop looking straight down and a little frame halfway through, because the reality is you don't have a clear proposition.
Or would it mean it's going to be straight, or whether the numeracy comes, kicks essentially something with high momentum, and basically it goes out there. You don't have occlude generally these adapters, and to a large extent, this implies understanding cosmogenics, essentially, as I said, you know, coming from the… from the media typically is very hard. When it comes here or here, you just.
So, in fact, this cosmological problem is, to a large extent, the reason why all these detectors are placed deep on the ground, sometimes 1 to the meter, sometimes even 2 kilometers, essentially ambigram, and to a large extent, this implies that basically when it comes to neutrino physics.
We are a little bit covered, basically, that in the analytic devices in that way. So we have to put all our detectors over neutrino stabilization happens in underground. And of course, I mean, everybody's dreaming to get out of the cover, in a way, but this is actually very hard, and this is one of the things that actually that we're motivated in Liquid, or at least we think that we.
We want to try to try out is, can we get, basically, out of, basically, the underground, basically, walls, and really start basically conquering the surface. If we did that, I mean, if you have detectors are looking something like that, and this is just artificial intelligence. I mean, I just checked on what kind of basically you get out of basically ChatGPT. And that's basically what it suggests. I mean, not a tribe.
We can show something better later. And the idea basically is that now is to detect what in this position that would be much, much, much cheaper, essentially, to reveal. For example, these kind of tanks could be, for example, the petrol tanks that are being mobile right now, not far from, but also far enough up here, but nonetheless, they may be.
So, we know how to do these kind of things on surface and make them big. Just to give you a little bit of basically an appetizer, I mean, when it comes to basically what we are preventing neutrinos, I mean, let me highlight reactive neutrinos basically were discovered in the 50s. This was the discovery of the neutrino itself.
And today, I mean, this was a Nobel Prize, by the way, and today is completely back in English. This means the technology that we use today for reactive neutrinos, I mean, essentially is requiring something new, long story short. When it comes to solar neutrinos, discovered in the 60s, that was also a Nobel Prize.
In fact, this is also background imaging. We have to do the detector deep underground, and even so, it's actually extremely hot. When it comes to atmospheric neutrinos, in the 80s, this is also back of the limit, that was also not surprised at the time. If you look at supernova basically neutrinos, also Nobel price, also background limited. In fact, everything is background limited.
But you can see that it was higher to shape, essentially, to see how it goes. Accelerators, and this is the 2000, roughly speaking, they are still basically limited by statistics. So far, nobody can read the state of they are, doesn't have the same in our beautiful, I'm sorry, I missed it this morning. So actually, you've seen basically that even as the ratios are starting to get to the systematics, and this implies technology is soon going to be basically there, that is the case of hyperk.
But for T2K and no, but collages, then the source, essentially, statistics is the problem.
Ge neutrinos, discovered in 2004. This is also Bachner Limited.
It's actually almost like a reactive neutrino. And you may have learned about basically double beta decay or proton decay. If anybody see that, clearly that's going to be highly appreciated. And essentially, I think it is the goal. But nonetheless, these are background limited scenarios, and this is something that people are searching. This would apply.
new physics out there. And this may be one source of view for neutrinos. These are the neutrinos produced, essentially, in the Big Bang, essentially, Europe. I mean, this is something well beyond our reach so far. People trying, but not even our ability to say it, and this would be, of course, something extremely important, essentially, for our standard of the universe.
Long story short, as you can see, the menu of the neutrinos today, and I'm not saying that this is everything, but just to give you a sort of a source, every single source of neutrino that we know of that we can use are completely limited by backgrounds, and this implies technology may be the limitation.
And let me try to basically give you some examples of that by bringing Liquido more into the sea.
Right. So, what is liquidote? So Liquido, long story short, is about this image. I think it can be summarized, essentially, in one image. So what we want to do with liquidote, and this is going to be hopefully a bit surprising or counterintuitive at the very beginning. We want to basically confine the light locally without using.
not using any type of external, basically, material, not any kind of victimization or segmentation. So, to allow system is the art of getting information we like, but without actually using external links. I will explain why this is important.
And these two largest then we want to do, but now instrument it and master it. Long story short. And in fact, Hiculio is about using opaqueness instead of transparency. We're basically moving completely to the rule out.
Yes, we are desperate, you may call it so, and indeed. That's probably a good way to see it. And, uh, to try to basically articulate imaging in a multidimensional way, and I'm going to emphasize basically that in a few minutes, and hopefully convince you that this is something that maybe we know how to do now.
So, when it comes to imaging, let's consider the building blocks. What we want, if we have to bring, is something that whenever there is an energy deposition, essentially we're able to measure the energy. We have already had, and we want to know what energy that is a one-dimensional element.
In a space, X, Y, and Z, essentially, and if you have basically a point, essentially, you have a sequence of points, you have lines between points, you have information, and of course, timing, which is actually a very simple. I mean, to today's technology, where.
reach maybe 100 picoseconds doable when it comes with detectors. This is optional, but nonetheless, this is actually relatively easy to do with instrumentation. If we combine all this information, this means that you can have, basically, a lot of multidimensional information, and if the detector is fast enough, then of course, TPCs typically get a frozen image.
What we want is insure it is to see images that are level, so we can see, actually, like a film what is actually happening at the speed of light in the actual detector. And you're going to see that in a few minutes. Of course, simulation, as for now, but you will see in one second. If we can essentially unlock all this information.
You will see that we can actually start basically re, I mean, kind of.
redoing amino-physic neutral physics that we have right now. So the way to do that.
If you confine the light, and that is easy to say. You can do it with a black hole. We don't know how to do detectors with black holes so far, unfortunately, and so the only way that we can do that is using, basically, another technique. So this is how photons manifest, essentially, in Gen 4 brains essentially going to infinity. These are fibers, for example, just to give you an example, and if you actually go from these.
water bike scenario, and you go into a mixed bike scenario, photons are no longer going to behave essentially like rays, they're going to behave sort of like whipped wheeling, essentially, there. And what they're going to make, essentially, is an effective point in space.
That is proportional to energy, and it has a timing, so it has position, it has time, and it has energy. So, long story short, we have, basically, this is the building block of our imagery capability, and that is that whenever there is one energy deposition there, this translates into a point.
At this point may vary in size, but we can make it as small as something of this size. And the idea, basically, would be that when we have events, we would have put in points in the space, and we would see the correlation of time of all these points. We were able to work out essentially that time.
So, going from these part of stories in part of line, to this paragon, this is exactly what we're going to do, and we're going to use a scattered, elastic scattering. This is Rayleigh scattering and mean scattering, actually, that comes from free. As a matter of fact, what is difficult?
Is that these actually natural. In fact, to make the pictures transparent, we actually work extremely hard basically to make that happen to the level, for example, super gamble, I mean to the level of almost 100 meters. I mean, it's the dimension end. What we want to do here is actually the light to scatter a lot. Of course, we don't want the light to be absorbed or to be lost, because otherwise.
people's information. So what we want is the line to stay locally. And what is going to happen is that the photons are going to stay doing around the world exactly, just very close to the source, on average around the block means the photon never… it's just, on average.
on the position, on the source, and everything else basically is thrown along. Of course, if the light stays local, you can at least photomultipliers located very far away, so you need to go and hang for this information, and we're going to put fibers, optical fibers. These cannot be transparent fibers.
Because these 56 fibers essentially collect the light. I'm going to highlight that in one second. So long story short, all the physics of liquid oil is just just up in the sky. Not today, actually. There are no clouds. If you have, basically, your eyes as a sensor and the center.
As the light source, the reality is that the blue of the sky is radio scattering, and this is exactly one of the scattering we're going to use, elastic scattering of photons, and we can also use knee scattering, and the difference of this one, of course, is that you get basically a very codependence, and these, the molecules in the water in the cloud are actually.
of the right size, so you get these colorless behavior, and this is why, not white versus blue in the sky, as a matter of fact.
the size of the molecules, in fact, in the cloud, in the atmosphere. And these black that you see in there is just these opaque names. Essentially, the light is not able to go through because it's thick enough. But long story short, everything on liquid works exactly that way. All the physics is actually there, so it's.
Just right in front of the glass. So, a nicolo Detector is the best nuclear detector that we want to perform basically strong scattering, is a white light detector. If it's me scattering driven, and in fact, we're going to go by four orders of magnitude, essentially.
discussing, we're going to basically bring it down by four little match. So essentially, this is a huge change. So in fact, we slide that would have gone without interacting, without scattering over tens of meters, I mean, it's going to interact within millimeters or sub-millimeter, and this means that we can make light bulbs.
of this class. Essentially, it's more than the hand. And this means that we're confining photons stochastically within basically centimeter scale or less. It depends, of course, your scattering length, which, by the way, is a variable.
So Liquido is about that, essentially. And let me just show you how liquidote effectively. But first, and the most important element, if you don't have that, you cannot take, you need to go to the source of where the light, basically, the energy is deposited, and there you need fibers.
These fibers have to be either wave-shaped fibers or basically scintillating fibers. Both of them actually work. Actually, these you can consider wave-shifting filters just a cheap scintillating fiber, a scintillating fiber gives light by itself. And the wave of.
Basically, essentially change. Why do you need that? And the reason is because if you don't have that, you don't get light into the fibers. The fibers are designed, so any photon that comes in goes out just by snapping out, unless there is a little scattering.
But this is basically to the permit level. So with the left. So generally, if we don't basically make these fibers effectively active, you don't get light inside the virus. Long story. And this is why we need this kind of virus. Clear fibers do not work. I mean, well, your light level will be basically 4 orders of magnitude lower.
The detectors who relied on certain elements. We need fibers, magically hanging in the volume for now, and there's a lot of engineering to do that magic, and I really struggling because we've been for more than 10 years, actually, developing technology is being developed here at Proud.
Uh, we would need, basically, new type of scintillators that are going to be opaque. They will be essentially milk like or cloud-like hole.
Yeah, my unit is like essentially this is basically what happens. Fibers, fast electronic silicon PMs at the end of the fibers, and very fast electronics that is able to identify every single P, and this is an example of basically waveform reconstructions that we need in double show, for example, and is able to basically.
give you every single P in every single file. So that's the kind of things that we use, essentially, for build an event.
So, imagine that you have basically a detector with a lot of fibers, nuclear light, and every single point here is given by Gen 4 and tells you I've got some energy deposition. In fact, these are basically two gammas from a positive election. Every single point is a quantum, and the last point is also represent essentially that. So every single point is just an electron. It's a point-like.
And then what is going to happen is that every single point is going to transform into a little light bulb, where there are tens of thousands of photons, thousands of photons basically there, and then you have to multiply your detection efficiencies in the fiber, the corrections. But what's going to happen is that in the top and the bottom.
You're going to have two identical images. In principle, if you have some sensors, and these two images are carbon copies, essentially beam splitted 50-50, essentially to the top of the fibers. And this means that everything that is correlated top to bottom means it's geni-like.
Everything is in unknown, could be inflation, but it could also be dark noise, for example, and things like that. So that also gives you, basically, a certain ability to basically cross-check and call an improvement. What is very, very important now is that you see this detector is completely.
I'll segment, you just put the fibers in the space, and is the opacity of the scintillator that is giving you an effective sedimentation. We call that effect cellular segmentation. In fact, you don't need to put anything, you don't need to split your detector, the volume of your detector. This is just done automatically, essentially, by opacity, and this is actually very good in ADV, because putting walls implies basically radioactivity. So that's very.
You have to be very careful about that. Of course, if you're in the hopping GV, the only problem of that is that you're going to lose a lot of photos, you're going to hit essentially the walls, and the walls typically going to go with a good reflector, you're going to use a lot of the light there. So, long story short.
What you get out of that is if you get more light, the light is always collected, providing that absorption, reflecting the beach pole essentially in comparison, and you get these beautiful topology naturally centrality.
You may be wondering, well, in this simplest configuration, you can put fibers. Nothing other than the wallets basically prevents to do that. But you can also be tiny. And these basically slide. So basically, if you are in a nanosecond, picosecond basically routine, you can figure out z, the z-axis will some, essentially, caveats, essentially you need more light and so on, but you can basically figure out whether more or less this.
position is allocated. So this works like a typical TPC, but now TPC moving at the speed of light. If I can think of liquidote, the best way to think of liquidote is a TPC, instead of using slow electrons.
We just use… I mean, this is the highest duty cycle nature can allow providing neutrinos to go faster life. Yeah, but about that in the past. So this is the images that basically we are basically talking about. So this is the positron annihilation. So you see basically the positron stop.
I will show you high energies later on, and you see the inhibition back-to-back. In fact, this is basically the physics of a PET scanner, is to see the first PET, and actually the first counter, and try to work out with information. And you can see.
In Gen 4, this is the color is proportional to the amount of photons in every fiber. Every point is a fiber.
You can see that you see better with opacity than with transparency. Transparency, in fact, washes out of all that information, and in fact, maybe you can argue that this is not a point light. So you can say that this is not an electron with a high probability, but you wouldn't know that it's exactly basically a positron as you would see there.
say that maybe it's account. We'll talk about that. So this means that you can distinguish now electrons from positrons and gammas, and as soon as you do that.
You're shielding to run into the detector is supposed to be done because most of the reason for the bathroom, remember, is the cameras coming into the detector, so this means you're basically start removing shielding out of your detector.
Hopefully we're going to work out in the cosmogenics and that's the next step when I scan. Now, once you have fibers, we can think of these simple scenario. This is the cheapest liquid scenario. We call it one-dimension, the liquid or vanilla liquid if you want to put it away. You get beautiful precision.
in X and Y because you know the position of fibers. You can be submillimeter. The previous detector that I showed is 10 centimeters, so we have gone basically by almost 3 order of magnitude in terms of position to three, maybe.
But now, basically, the timing basically is worked out on Z, as we highlighted. But now you can start playing some tricks. And this is just an example of that. How about if you start crossing your fibers? Now you can do the center of mass. If you think that the center… I mean, the event was here, what you would see is that your events diverge.
called buyers. They meet in one place, this is your position, and they diverge otherwise. So just by changing the position of the geometry of how you put the fibers, this is just a trivial example. If you can do the mechanics with workflow, whatever.
They're very functional and you may have subjects. Your mechanical engineer may suffer, but that's another issue. I mean, at this moment, but you will get much more information. What is beautiful about is that you can combine position information with diagram information and produce, essentially, the resolution Z.
in comparison to just using tiny typically you need more light. So let me give you another way to basically think of liquid. Imagine that you drop a little bit of ink in a glass.
And you have a lot of information of what happened originally. If you wait basically to the infinity, this basically ink is going to diffuse, and everything is lost. That's exactly what transparent data.
everything's diffuse. You cannot go back to what actually happened, because information has been washed out. You have still the amount of ink, which is proportional to the energy you like, like this example, because that basically includes our intuition. This is what we're doing today. Indeed, we don't have topology, and liquidote is going to basically try to do that.
at least done for free, because the photons don't last forever. This is not like putting milk in your coffee and the milk stays forever and you get your coffee going from dark to basically brown or whatever. Okay, that's exactly the same rationale. In fact, the photons ephemeral's life.
He's going to essentially petrify a sort of anchoring time into the information. So he wants better information with both fibers, connect your photons faster. That's what it comes down to. So the game of liquidote is going away from it. It's going from here.
And that's essentially what you could do is with fibers in a funky way, and ink is much easier, much slower. I agree with that, but we want to do better safely just pure flight.
non-negligible, but it's still possible. Right, long story short, whilst you have basically this formation of these light bulbs, which you can find the information, this means that you can actually work out if you get a lot of lithology, and now basically starting to have fun doing physics on that. Now, before we actually get into the fun level, this has a potential implication.
Which is that we need to now change the paradigm of simulation, because insulation until now, it was about transparency. Anything that was not transparent, actually, we see the B.
Because it was useless, basically, for physics, or for detection for not just that. Long story short. So now we need to basically go back, essentially, to the origins if you like, and start looking.
All the things that can scintillate, and they don't have to be transparent natively. And it turns out that scintillation is actually a very mundane process in nature.
What is very hard is to combine scintillation and transparency. That is very hard.
As a matter of fact. So actually, we have a lot of things out there that could be scintillating, and they are opaque, and they have never been used. That's why you never hear about it, even on me, as a matter of fact. And this is exactly where you open a completely new universe of materials.
science, and this is, of course, with a lot of people essentially in the detection world are brothers have an immense amount of funds. As a matter of fact, one of our best colleagues are photochemists, material scientists, because a lot of that has been done already, and we just didn't use it because it was not transparent.
Then we give a couple of examples of that. What we're going to do, in fact, the way it works is very simple. Energy.
is deposited, quantum mechanics is going to make basically get this energy transformed in your scintillator into non-radiated glucose is quantum mechanics is basically exciting disintegrator in your solvent. So, in fact, you have a… essentially, it's like a glass of water, and you put a pinch of salt, and that pinch of salt is actually the Berme level is producing the light.
And this is quantum mechanics is tunneling all this energy. As a matter of fact, and producing light of the little pinch of salt in the water. So this is actually typically the solvent, and this is the scintillator, the first scintillator. And what we normally do in transparent detectors.
is that we put photosensors directly, I will mention this light that is emitted, or if you have a very, very large vector and a snow globs that I showed before, you put a second scintigator, so the photons of this one get absorbed and re-emitted even closer to the greener.
Essentially, and you optimize this better with the photosensor, so your detector is even more transparent. That's basically how Juno works, that's how basically the offshore will work this way. We have business speed. For example, this is just an example, and this is how snowplass actually work, the detector I showed before. It's too big.
We just work on one SQL scintillator. In fact, what we do in Liquido is very, very simple. We just go break up the second simulation data, go to the fire. That's it.
because we know that's exactly. So this is tuned to that, and basically the the color is tuned, and that's it. That's what we're doing. And instead of photographers, we put silicon photographers, and we're done. So if you think about it, I mean, we are actually recycling.
Almost 100 years of knowledge by basically doing… from the point of view of the detection chain, this is mine. This is a data that is changing, the detection change. This means the efficiency is going to be high. We know the type evolves relatively very well, because we are basically in the shoulders of giants. This is a hundred years, basically, of the action that we basically relying on.
Jupiter singlets, full shape, all that, all that works. Everything that works in the novice insulator should work in the liquid, provided that the opacification is not basically going to spoil it.
The first vaccine later we're building in Paris, in fact, back in 2018, and we were doing something a bit funky. We were dreaming with an idea, and it's that instead of basically we put something to pacify the scintillator, and we're wondering, okay, if we could now grab this into the simulator, that's going to keep the light.
But what if we put another incidental in our liquid scintillator with a crystal scintillators, so we get the opacity, we get the scattering, and we also generate light. So we're not putting something that is going to kill the light, but it's something that is going to generate light. So in fact, we call this microprystal scenario. If your crystals are nano.
In fact, the light is not going to basically scatter enough, and you don't get basically white enough, as a matter of fact. This is why we have to stay on the micro, and this is because the wavelength of the light that we're talking about. Long story short, so that was the first attempt, and worked to some extent. And then some colleagues of us in Germany, Max Planck, in fact, they use.
The waxify so that it will make the opacity, so this is like a candle. Remember a candle? When you hit it, essentially it gets transparent, you get liquid untransparent, and when it cools down, it becomes white. This is me scattering, the photons are scattering essentially the wax, essentially, and this looks essentially like a candle.
In fact, it's like a temperature essentially to find it, and it doesn't blow up. By the way, scintillators is the most stable way to have a lot of hydrogen.
just before it explodes. A bit more, and you have basically your main time at home. As a matter of fact, this will cook as a matter of fact. So see that scintillator that is just not a stable enough.
Another way to do that is emulsions. This is basically, you can call this milk. Milk is just water with some fat, with a fat 3% typically 4.5%. Some people can choose less, but it's actually got worse for the input of you, but for health, maybe. And so you have water, basically, the droplets of water, micrometer. This is why melted water. Milk is not… Sorry, this is why milk is white. Milk is not white because it's white. Milk is white because the photon is scattered through me is scattered. You see? This is exactly as a cloud. And a minion is the opposite. It's oil with a little droplets of milk of water, and this is where myness and milk look exactly the same color, even though you could consider this the negative one in the upper, in terms of composition, in terms of water.
So emulsions, we can do it. So if we think that liquid scintillator, we put a bit of water, we have basically a white system, instantaneous, essentially. In that case, there will be more biomass. If you take water and we put a bit of scintillator, this is more what people call water-based liquid scintillators, but I still get water.
Very easy. You can try. Just give it a shake, and you will have it right away. So we have several ways to do this opacification. So we can use wax, we can do emulsions, we can do microcrystal. We have tried nanocrystals, they are not that good, and the reality is that we have several ideas which are secret right now, but we have at least two or three or more ideas that we haven't we haven't basically put into publications.
And all of these ideas basically are speaking the work of that. Now, we are not just in the first, if you want to make the vectors, you need to master the size of the light bulb.
to the proportional to the fibers to sampling problem, and this is the level that we're at. Essentially, there is an immense amount of, basically, the physics that you can get there.
We are actually even a sponsor, essentially, by, oh, we've got an extra 1 million euros as part of one of our projects in the European community in the UK, right? In fact, we have to explore that, so actually we're encouraged to really push these obtain basically paradigm in many ways, and improve fibers and so on and so forth, and here we're basically now.
creating technology for the long social. As for today, we're using the technology. Now, there is another interesting feature of liquidote is when you actually go into the basically the Google level. So this is basically when you make call basically the typical detectors with a lot of scintillation fibers.
So this is just fire and hardly is insulator. This actually has been done before.
Even if the simulator is very transparent, you have to understand things before, but this caused an immense amount of readout every noodle is a fiber. And you have to read it out. In fact, Liquid works more in the noodle soup scenario.
So in fact, you have more liquids in them. And this means that with less channels, you get the same level of information, and that's the power. The opacity that happens essentially in the growth is exactly what we want in Equino. So you you get almost the same level of information.
But you use MAC made you much less chance. Long story short, if you don't got the optimization at the end of the day. So Liquidu is just optimizing with opacity discourse. Long story, which, by the way, has been done, and it's very expensive.
Right, um, so that's what we're speaking on that level. Now, if you have a scintillator that can be opacified, this means that you can add a lot of things that before it was forgiven. Anything that screwed up is simply the transparency, it will submit it. And as a matter of fact.
Everything screws up your topic. Anything you do is just against transpire. So if you want very good transparent vector, long story short, you cannot basically put anything on that. And it turns out that now if you're a detector, you want it to be transparent. This means that you can start basically noting your detector, you can now basically know the pinch of salt.
But if you take a beat, basically, big spoon, and you throw stuff into the detector, because that is going to give you the opacity, maybe for free, and hopefully it's going to do all the physics. Now, this is interesting if you are basically in the low energy, because the scintillator is one of the most pure.
things that you can actually handle in your life. In fact, Boric Signal has made this number n to the minus 19, essentially ground to ground reganatorium. This means that even the MEV, you almost eliminate the Hoover up essentially all the basically Uranian potassium ability, a little bit more complicated, but nonetheless, this is good. Fibers are very clean.
anything that's black is actually really, really good. Segmentation. We said, you don't need it. You don't need borders. You need to put anything to the desktop, because that means bitness and antifice, anger, all kinds of relativity like vision. So you don't want that. Photosensors are going to be far away. You don't have to put the photographic bias reading the whole thing, so no photomouic wires, no buffer, no receptivity.
From the, basically, from the method. Remember, automotive reliars use metals. Silicon clear semiconductors. These are rather, rather pure, as opposed to the metal of the fire. And this means that now we can load your system with anything. So let me just give you an example of how we have done physics in neutrino that.
So you can take a liquid scintillator, this is almost an absolute basically purified system by nature. Carbon protein essentially is 99% essentially of any carbon constituent hydrogen is also very clear. And what people have done. Remember the discovery of neutrino. It was done by Reynolds using a little bit of cadmium.
I mean, to get basically on the scintillator. You may have heard about loading Badolini or loading in lithium. This is what we've done so far, because it worked on the pinch level.
But what if you start adding a new element, for example, lead, that has a cross section, for example, of neutrino, and this is 500 times larger than the cross section it would be native liquid neutrinos in a carbon system.
That is the only thing, but this means you can do completely new physics. You can do neutral current, or charge current. This means that now you can put so much stuff in your detector that your detector becomes… I mean, they don't that your doping is actually becomes an actual package. And this has to now.
Has been possible so far. The other possibility that you can do, and you may have heard about that, there is a Kernand experiment, is actually put a huge amount of double data, for example, elements, and used your simulator detector as a diffuse double database system. And that is actually has been done, and you can get named to the top network.
So, these means, these physics has been very, very impractical so far. Kevin Zen has been working for a while through the world record in WBD in terms of… and this has been known since a long time. But trying to do this kind of things, this has been so far impossible, because putting this amount of loading.
was basically making this inflated paint. Many of you the latest status of the R&D are going to be faster, sorry. Liquid user collaboration. We have about 100, basically, people in five in Barcelona just joined not long ago. So, our first paper actually came just after a seminar at CERT in 2019. We were in the middle of COVID, and we went about time? I mean, to release the project timing, but yeah, we can choose everything.
And very recently, probably highlight, essentially, is that in March last year, in July last year, we released two papers that we call Liquid1 and Liquid 2. This is a sort of monolithic small detector, makes sort of things like the smell that I showed before, and this is more of a new tracker. I'm going to give you a highlight of the results. You can find things in.
In our college, this paper is how the genes, and this paper is being interviewed as we speak. So this is a little detector, monolithic detector. This is how a liquid detector may be applied. This is… individual design, a lot of fibers for the level of 7 milliliters between each fiber, and a lot through that. You think about how much… the cost of that is a small prototype costs an immense amount of money on the radar level, but this later on, the vector will scale very nicely. In fact, the vector of liquorous detectors like spaghetti growing.
So if I was alone, you can go away and you still read the out at the end of the fiber. So spaghetti any spaghetti direction, directionality is good for a particular thing.
These are things that we fill it with water. So we see Jenko, we fill with insulated normalcy, and then a scintillator that can become opacified by using temperature. This was wax. So we warm up the detector, it becomes transparent, we cool it down five degrees.
And it becomes very big. So this is basically the transparent configuration. You can see one operator squared. This is what you expect. Every point basically is the fiber. And this is what the detector basically is called. Essentially, we make the light bulb, and most of the light, almost basically 50-60% of the light, is in two fire.
In fact, the light bulb is extremely confined. This is what we measure data. This is what the Monte Carlo says that you should see. In fact, you see every single point here is where the photons interact, and you can see the photons all interact when they hit the fiber directly.
Whereas, when you actually ask the Monte Carlo, I mean, how this looks like, the photons are interacting everywhere. That's disgusting. In fact, you don't even see the fire. Because the photons are interacting brutally well before you get to the fibers. And this is often between the confinement that we talked about.
So we get more energetic electrodes in this system, which is actually very hot, but I think possible, and you will see why we do that.
We have a very fast electronic that was able, basically, to measure every single bee, even distinguish two elements within a very small fraction of the second. And this is our data basically with water. So what you see here is this is the beam was injected here.
This is one of us, where, roughly speaking, the length of life is a bit forward, but this is local agility. This is not a bad survival, this is a vein scattering particle, essentially, the Move is huge. As a matter of fact, so it scatters a lot. And this is beautifully, basically, the Cherenkov's light.
And this is, you can think, is the fibers. This is the decay of the fibers. These are fast fibers, but still, there is no time of correction. No correction whatsoever. What you see is the wrong data as it goes out into the data. So this is as simple as you can possibly do.
But then you can basically feel it. This is filled with water, but you can fill it with scintillator and inject electrons more energetically from low energy to high energy. The energy threshold of the Chernob threshold is about 340 kV. You can see that the Cherenkov is appearing.
smoking gun, so we're seeing it beautifully in the Chenenkov versus insulation, just out of the box. No calibration on time whatsoever without showing it away, because that is… if you have a detector that's just out of the box, give you that.
Imagine when you start touching and calibrating the whole detector. So this is, to me, this is… this is the power. To see a cool detector that gives you that. And this, this is something that even… transparent detectors fail very frequently. The best experiments in the planet have reached something like that. So this is just out of the box.
And that's where you see the power. And I remind you, basically, again, these electrodes are as highly scattered. So these Chelenkov is no line moving forward. It's light that is scattered because the photon is scattering, essentially, and we can distinguish change of light. And this is very interesting for calorimetry. I mean, you have these dual calorimetry concept, essentially.
It's called Blocker Luma Direct. For calorimeters essentially colliders, and it's about separating this information, what we have in there.
But if you actually now optimize your simulator, you can see this is to get much more light 100 times almost more, and you may be wondering, oh, if you actually have a scattering, you may have spoiled your timing a little bit. You're right. Absolutely. You can see this is.
transparent, and this is with this calcium. You can see that there is a little bit of a tail 15 nanosecond, but this needs your time is well-preserved, your rice tiny is well protected, and your blade time, I mean, that you don't use all, essentially, for your timing, is a little bit slow, a slower.
More scattering, this is going to get, of course, worse, evidently so, but you can tune these if you want to do a time of flight or a fast system, you may change things. I mean, essentially, to get your preserved.
Okay, so this is basically to keep in mind. And this is basically the line quote. This is a little basically light bulb.
So what you're going to see is data with different energies, and you can see that regardless of the energy, you have the same light bulb because it's a fractional effect. Excuse me.
And this is an analytical basic example, not here in Monte Carlo to make it mathematically very simple, even a mathematical simple model of the scattering actually works beautifully out of the box. So this is basically within two centimeters, half of the light is essentially 2 centimeters, half of the light is detected.
within, essentially, if you want 90%, you need 5 centimeters. So 5 centimeters, and you are detecting 90% of your distance.
And the light level increases. Okay, so indeed, and this is what's called liquid O is because the detector after 10 centimeters is okay. You don't see anything beyond it is as dark as if it has. It's as useful for detection as your shoes.
And putting that aside, I mean, this is now another meter track. This was done in Sussex University, our colleagues, and with the contributions for the other people, this is basically how liquid the opex internet of similar. This is now going to have been solidified. This is basically what it's called. This is how the detector looks like when the detector has been warmed up. And you can see this indicator looks just beautifully just fine.
I just showed before. It's been pictures, beautiful in fact. And we can now do Taki. So this is basically they have some little nice tacks where you can see the new basically comes within this new telescope if you want. I just put a little diagram to say you can.
The news is already there, and these are basically the liquidote actually going there. But this is a Monte Carlo basic example that you can even try to see delta rays and so forth. Again, you have this aurora counter that gives you tracking on the numerator.
And these are people something, well, this is maybe this is the liquid or two paper. I'm not sure what came out.
And, um, and he is basically the tracking capability is actually in transparent mode, and this is an opaque mode. You can see where subway emitted already, and this basically is on the level of half, essentially, 500 micrometers, but we think with simulation, we have been extrapolating, optimizing a non-optimized detector for that configuration. If we optimize the vector, we did that with heat simulation, we think that we can go below 100.
100 micrometers, this is a way that is scary numbers when it comes to tracking position. Okay, this is a very tiny detector, so of course, if you have a bigger detector, you get even better, even better timing.
So long social, if you actually combine the outcome of these two papers, we have essentially convinced ourselves to confinement were just as expected. We see the topology of the electrons, which is basically every point in a countdown electron. We understand our energy level. This detector, we lower the energy level on purpose to be able to scale and to understand the scaling very well.
And, uh, if you have any questions, don't hesitate to ask. With this scaling, we know that we can go basically to the level of hundreds of people in the league, and certainty is a bit larger. This is almost difficult of a prototype. And with the liquidote2 paper, we were able to demonstrate the subrimeter tracking capability.
You see the topology of the immune system, we see the tux, we see the points, long story short, and we can measure at my level that is consistent to the predictions there, so everything is just a beautiful, happy story. Long story short, with those two papers, we consider… I mean, we are closing to some extent, essentially, the.
R&B of demonstration R&D, and now we're moving into the R&D of pushing, optimizing, and getting delivery to its even better. Long story short, getting more like, getting more tracking, getting more energy. So that's basically where we're moving, and this is basically the next… in the next phase of the collaboration.
So a summary when it comes to basically is probably we are able to we demonstrated the stochastic-like confidence, we demonstrate that we can confine the light. We are demonstrating that we can measure the light scintillation. We can use any medium liquid and solid gas is a bit harder to make capacity enough. I don't know how to do it, but if anybody has a good idea, don't hesitate to propose.
We're able to talk, we actually did talk, and we actually basically opened this new paradigm of obesity. So long story short, it looks like a happy story so far. And despite coming halfway through. So we believe that we could have basically just works in fact.
And then we get beyond that. And, um… so let me show you some images of the capabilities. So we're moving from this paradigm or we use photomultipliers. We have this buffer, and we activate the right way. Well, the possible ways to eliminate the photomultipliers, put some fibers. But if you just do that.
That doesn't work. What you need to do is to get opacity, so you need fibers and opacity to really work out what happens inside the sensor. So just the fibers. Actually, some people did that before. It doesn't work out. It's very expensive, and we don't get more light. I think you get this light and it's less. So let's try to now get.
To a point, like, basic information track information, which is a configuration of that, or any any normal periodic information, any possible basically topology of the detector. And let's see how that works. So, so far it has been impossible, basically, to distinguish electrons, positrons, and gammas. These gammas.
are the nasty reason why detectors use buffers. So, this is the nasty reason why one-third of the detector size is gone. If you're able to distinguish that.
from a possible neutrino or an antigen, instantaneously, the detox happening buffer. This means that all this huge volume that costed you millions of euros, essentially, to dig out.
You can use it. After that, so this means you'll take to be utilized by 104. All this information was washed out by the transit time spreading frequency drivers. Transit time spreading device, you have very good drivers in 1 nanosecond, 1 nanosecond speed of light in these medium 20 centimeters. Anything within 20 centimeters is just washed out. This is just… When you have a better telescope, sometimes you figure out that there are two stars instead of only one. It's very simple resolution problem. That's what we had. And this is the kind of imagery that we're talking about. A positron is almost half a meter basically disc. An electron is actually millimeter.
Ironically, in our detectors, I will show June or whatever, we are not able to tell the difference between half a meter.
This is the reality of what is happening today in our for this reason, we have to put it on the ground. If we're able to tell the difference between millimeters and half a meter, that's remarkable, we will tell and we can do a lot more physics. And this is a camera. This would be… typical of physics and delays, sometimes you have neutral carbon here for gammals, but let's put that aside. This is typical reactivity. This means you can actually remove your shielding and do things like that. For example, in a reactor neutrino, anti-neutrinos, all your cosmogenics.
are beta minus. This means that if we all distinguish an electron from a positron, your cosmogenics are gone. This means.
In principle, you can do reactive neutrinos on surface. Nobody has ever tried. Well, people have tried, and people he was very happy because their brains, the first neutrino experimented discovery, they wouldn't surface, and they didn't match as a matter of fact.
It was the second one where they realized that actually let's go a little bit on the ground, and that was the one that basically managed three years later. So in fact, the idea is to get detectors on surface and demonstrate that whether that is actually true. Can we go? Can we get neutrino detectors in our surface?
And that would be a major change in the data. So it would imply that we can change entirely our shifting strategy if these numbers can be done and we can change our environment strategy. I remind you that basically putting a detector on the ground just by making the hole is super expensive. I mean, it was in June, it was probably.
half a billion euros, if I remember correctly, more or less, the new laboratory on the ground, and the detector actually was much, much more expensive. So this means that half of the money went into the… into making a hole, as opposed to making a better detector. It's a beautiful detector, I like it very much, but if you put twice the money on that, I mean, maybe you get even a better time.
Now, if you want to distinguish electrons from gammas, this was basically this all this washed out information. And let me just give you into context our latest data. So this was our paper in the past with Monte Carlo. This is what we get out of the detector. This is of the 5 centimeter. We did it on purpose, we just… We wanted to be protective if you'd like to be conservative, we make it big light bulbs, and these were measuring the laboratory. So if you scale that, this is, I mean, of course, this is just a simple example. I mean, you would be getting off that level. This is not totally correct.
the light bulbs proportional to the energy, actually to the load of the energy, and they would be able to distinguish that very straightforward. Roughly speaking, we expect a pattern of hundreds of rejection electron to gamma.
Uh, with 90% efficiency roughly, and that is just consider that this is just impossible today, but that's that's already quite a big step forward.
So if we're able to come back essentially to our last detector, like, well, these gammas would be eliminated because they are recognized, so you don't care about that anymore. You can make the data bigger. If you make the detector bigger, you move from using only 10% of the football of the full space that you have.
maybe to 80, 90% is dream, of course, but this is basically the potential to get on that. So this means that every single meter cube of excavation you pay for.
also ensure that they have. That doesn't mean that you make it bigger. That means actually you can make less generally, as a matter of fact. And we can have native striking, as you saw the needles to the millimeter level. This means that anything that happens along the main track, we can figure it out. So now we can tag the neon within even less than a millimeter and see what happens all around that. This means.
that we are changing entirely the paradigm of versatility, because the new, if you ask me.
One SQL feature that we need out quickly and revolutionize the power stream.
The cosmogenic is called the ground. If you check that, if you change the value.
That's where you get the level that we are potentially there. It depends, of course, on your physics. I mean, the new might hit you different if you're on an anti-neutrino, if you're on a neutrino, but… Reportations almost getting there. Now, let's imagine that we have a beautiful GEB as a narrator somewhere and shooting basically nice particles, I mean, for CP violation, and this is what an anti-neutrino, now of 2GB, would look like. You get your electromagnetic shadow.
And now you can see almost the multicolored truth right in front of your eyes, and you can see your gammas. These are simple gammas. There are some annihilations of the gammas of annihilation. You can see, basically, you have your pi minus that decays into a mu- and decays into a Michel electron.
And this initial electron, because you remember, if this was initial positron, you should see the regulation of the positron, and you don't see this means you can track even with a magnetic field.
Beautiful. I remember that almost all the particle station, I'm like, hey, and this implies also show that you can track with a magnetic field. You don't have to get, but if you have to give you a better magnetic field depends on how the particle is arranged. Your magnetic field. Here you don't care about the rotation.
Clearly, regardless in which direction magnetic field goes, is actually… And then you can see neutrons, which is very important because a lot of the energy of the neutrino goes into the neutrons, and you can see a neutron very slowly, you will see in one second. Proton recalls brutally, and this is a lot of the energy in the neutrino went into this guy. So if you want to reconstruct.
Neutrino energy, you breathe through energy to make oscillation physics or any physics. The energy of this guy. In fact, if you miss these guys, we are in a serious problem.
Because a lot of the energy goes there. I'll give you one example in one second. So this means that we can actually basically get a lot of this information. We kind of flight in addition, you can measure the energy of the neutrons. Matter of fact, you'll see in one second, and the thing that you see there has been effectively.
validated by the Likuda won paper and the tracks are there, the points are there, everything is there. Every point that you see in there is just an electron, as a matter of fact, unsurprisingly, there is a lot of electrons in that.
Turns out to be right. all the topology, basically, building blocks have been validated, so everything, the GEB, in many ways, is just a step is easier. You have more energy, you have more staff, you have more topology you can do in many ways. So if I take the word today, in general, this should be relatively accurate and easy way. So this is just to be an example.
of a Michel Positron. Looks like, basically, an electron clock with fireworks and these are the shared electrons and shared positron. So I just go back very quickly. Sorry about that. If you have a positron here, the Michel positron, you would have seen this annihilation gamers. You would have seen some of these little things out there, and you would have said, oh.
And you track the sign. And this image is just perfect.
This is just to highlight that you can tell the difference between those 2, and you don't care about magnetic field rotation at very much, but as you go in different angles, you may not be aligned to the magnetic field position. And then here you have tracking. So you can get directionality and so on and so forth. So, for example, this is event, you can consider that is.
a super global neutrino and a supernova anti-neutrino. This is the right images and artifact. So you're actually testing supernova or decayed moist accelerated, as a matter of fact. That's exactly the kind of event. This means you can distinguish the sun, this means you can do an CP violation with them.
Thank you. Now, these events, I'm going to put it back, you see neutrons. Boom, boom, boom. You can see the neutron, and you can see how it's got there. All the energy, a lot of energy went into those neutrons, because you're punching, essentially, the nuclei and none of the energy going into that. Some of the nuclei are direct, some of them are generated, and it's, you know, it's very complicated interaction-based system, as you go into GV.
But you can see a lot of information. I chose on purpose these more, I mean, less precision. This is a detector that will make the light bulbs somewhat thicker, so we use scattering, it's less scattering, but you can see you can play with that. You want a better detector? You make it thinner, and you put.
More fires. In this case, it's overdesign that clearly see that you have so many fibers, and you need to go with. This is completely represented. This is just an example, this is not an optimized detector at all. I'm just going to put it again, so you can see.
So, this is the speed of light. In fact, there is a clock here. I'm just trying to stop it, because you will see that within a few nanoseconds.
is actually something like that. I didn't do that. But if you go very quickly, I put it there. Within a few milliseconds, you see two nanoseconds, you see the development of the band. So you are seeing the event is coming from here and it's going that way. Your reconstruction is primarily the part.
If you have a TPC, for example, with electrons, you get a frozen image.
In this event is easy to know the neutrino came that way, but the way the generator is that way, which is relatively easy. But in some other specific atmospherics, that is not that easy. And atmosphericans sometimes.
Okay? So anyway, this is just giving you handles, and handles is the starting image again. And this is basically proton decay in super chemical, for example, or in hyperchemic ambit. And this is an interesting channel. This channel of the positron is your electron.
These appearance, appearance, this is due to a CP violation channel, and this is your background CP violation by zero production. And you can see that at pi zero can be separated from a positive one electron. It doesn't matter because the shower is shower, okay? So this is basically your neutral current back from the CP evaluation. This is your main background.
Because this, in hyperchemical and superchemical can look like this. And you can see it below.
But this is the kind of thing that you can do.
And this means that you can try, you can say, oh, this is not going to be necessarily bigger than hyperk, but remember that the efficiency of hyperk on this channel is about 10%.
This means that your detective is 10 times smaller, effectively. So you can do basically that. Now, to cells that put into KC channel. In fact, nobody knows.
prosecute the game would know how it's going to get.
So it's good to check multiple channels, and this is the kind of thing that we're trying to look in Liquid. We do proton decay in all different ways, because that's one single channel, because that's the channel of superkinetic candles. If you look at Juno, they use the Km decay.
I'm used time for that. That's beautiful. Actually, humans, because I don't have the time. Do you want to use the timing, but you get this beautiful image of the game. That's beautiful. But there's only one child.
What are all the chats? neutronik.
That is Nobel Prize physics. 100%. Right. I stop there. I mean, just a little summary. So Liquido is about basically using opacity. The thing that we try to avoid, the thing that we have been trying to basically kill since ever turns out to be our ally. We just have to change the detector a little bit.
But now technology was not up to this level in the past. But we're getting there. And this means that we can have imaging, topology, PID, and it depends on your physique. I cannot speak from plasma minus infinity and for all biopsy means, we could know there are some things that are counter.
We can discuss about that in the questions, and uh… but there are probably a lot of things that you can do.
We have these five primitive information, and the deposition and time.
It works like an effect in the TPC at the speed of light.
highest duty cycle. This means you can put it on some surface. That's no problem whatsoever. Principle, but we're doing that with the nuclear reactors. Imagine, I mean, with a beam, if that was the case. Uniform kernelimetry, with a lot of information. Stochastic and non-stochastic, relatively what everyone understood.
The reality is that it worked like a time of flight in multi-dimensional. That's when you saw the neon. I mean, you can do the time of flight of a neutron, sorry, that's a mu, a neutron. So the neutron, this is just a time-of-flight measurement.
That's essentially what it comes down. So we have a calorimeter with a time of life system, with an imaging system working as a TPC. That's what we could describe. In fact, you cannot really speak of either it's all at the same time.
All of this entire time. I can define it that way. This is why I make this a slide, I mean, because maybe summarizes any addition.
Hopefully, we can do this for the stuff that makes even more physics predictive. Remember, if you have a scintillator, it's hydrogen carbon negatively.
You may say, well, that's not my 360s or helium or carbon. Well, that's as much as we can do at this moment. Water also is oxygen and hydrogen, and that's that's what it is. Can we make it big? Well, it turns out.
Nova in the US is our R&D digital nomin actually, but this is our liquid R&D in terms of scale. In fact, the scintillator, these fibers, oh, the segmentation, we don't care. And the light collection, they actually get a reasonable light collection, but we can improve that copious speeding by a factor of 10. We believe that we understand that, especially as soon as we remove the segmentation.
For the sensor, they use different silicon PM clouds and other quality bulk, we believe the reason today.
Essentially. So, to allow us to stand this architecture that can go about 6 meters, and we remember they all know about a fiber, they twist it and goes up, and it's red out on one side, we can do that. We can do that.
So we sort of showed nobody is already demonstrating that we can make this detector reasonably big.
It depends on the physics. Doesn't have to be almost there. But clearly, I mean, Nova is a beautiful example that we can make these technologies scale. So I think I'm going to just repeat myself. So maybe no need for that, but I'll just then, I think we're very satisfied at this moment. I mean, we are very happy to see that.
These two papers, very important papers, they really put the demonstrated experimentally what we think that it was needed to say.
nuclear works as planned, and the next level is just improve upon improvement. And if people are interested in, I mean, please think about that, and maybe your physics works, maybe it doesn't. Thanks so much.
Thank you.
No problem. Okay. Thank you very much. Nice talk. So let's questions.
I'm quickly. Um, I was wondering if you could say, I mean, you said at the beginning you speak a lot about virtual physics.
I wonder if you can talk a bit about, you know, other uses of liquidotechnology. I mean, you know, you mentioned dual bead out calorimetry, for example. I mean, you know, how… you know, if we're talking about future.
glider calorimeters, you know, what are the… How easily does it scale? Where does it fall down if it does fall down? What's missing at the moment for that? I did a little bit at some point, but anecdotally. So please, what I'm going to say may be, please correct me, don't hesitate.
Um, so, in fact, there is already a liquidote calorimetry project in France, if I have derived. People are looking into that by using microprystals with, uh, essentially… Very high density, as a matter of fact. And they realized that actually this is the LHCB people. They are actually… they have these segmented calorimetry and realized that actually very bad to have the segmented calorimeter, the sandwich calorimeters alike, and the resolution that you get with calorimage of this topic is for the.
Not to derive too much, but the resolution is just that of i. In fact, using stochastic something to stochastic something, which is a stochastic term of the parametry, and is extremely good. So there is some testing data, and it's looking very good.
Now, in addition, I mentioned the tungsten because it just wants to increase the density to make the carbonate more compact. But imagine you want to emphasize an electromagnetic orimeter, so you use basically more.
That would be great. Imagine that you want to emphasize and compensate the calibers or something like that, you want to emphasize your neutrons.
So, in a way, by actually being able to do and not constrain essentially to a very specific material that you can actually make a solid of materials. As a matter of fact, you can actually basically play with that in the uranium if you like, programmability.
This calorimeter, so you can play with a lot of tricks on there, and you just put a pinch, depending on what you need, and then you can imagine, for example, a detector that you have certain composition at the very beginning, so you don't want to sport your beautiful electromagnetic alarm for some beautiful electromagnetic channels, it's like what they're about.
And then you have your harmonic part where you want to really do more and emphasize essentially nutrients or whatever you can do that. So you can actually have a detector, even a relative humid from calorimeter, using only one single technology. Advantage, you can change the simulator anytime.
It's a liquid, you can remove it. If there is any, for example, deterioration with exposure, if you just change the simplates of peanuts. I mean, our objectives are much bigger than your chloridians in general, so just change the calorimeter. Back problem? Fires. Your radiation is going to probably affect the fibers. I'm not an expert on that, so we do know much better than I do.
Probably the fibers is going to be an issue when it's exposed to very high radiation, it's a plastic, I'm not sure how it works on that. There are alternatives to do that. You can use coarse fibers and things like that. There are other ways to basically try out things will be more expensive on the one hand, but maybe last for longer. This is beyond my range now.
But there are possible ways to basically play that game.
I'm not so sure that was satisfied in there, but I'm not really an expert. Yeah, thank you very much. No problem. But you saw, if you don't mind me just emphasizing, Magic.
These kind of events. In fact, I mean, and this is your electromagnetic shower. Of course, there is too compact, and if this was, sorry, I didn't emphasize this. This is about 3 meters.
And the idea is that you make this much more condensed, but you have particle flow and particle… particle flow, which is… we call the energy flow. There you are the energy flow. We'd love to have a picture like this.
But imagine you have main uploads, and we can actually use the segmentation that you can get out of that. Of course, if you compound just from solid angle, you are piling everything up in the same position, but that's the thing that you can play, depending on your energy and someone's photos you're looking. Maybe the forward, you can try a different way. Some rapidity you can apply in a one way or another. This is beyond my.
my physics, but I hope it inspires you. Brilliant. Thank you.
Um, yeah, I was going to come to one of the comments you made right from the beginning. You talked about, uh, relatively neutrino.
which haven't yet been observed. So how how are you defining relative cleaners? What about the very high energy neutrinos that coupled in essentially the the nuclear fences.
And these are basically cooled down, essentially, as the universe expanded, and they are so low energy that nobody knows how to do that. I mean, there is probably no longer one of the projects using very cold cryogenics.
and try to basically measure some of that, but very honestly, very early on the experiment, by the way. I'm not sure nuclear would ever get that. I was not suggesting that this was the beginning of Victoria, by the way. I think on that, maybe that's the moment. I'm not sure how you would get there. No, I… That will tell you you're really seeing, essentially, a relic of the data. In the same way that we're seeing the map.
But, uh, but, uh, but worth fighting. If anybody knows how to do that, I mean, for sure people will remember to do that.
So then, uh, other question, you talked about gaseous slur stuff.
Is it possible to have any… It's not a particular type of gas. So you've got, you know, like smoke. Yeah. So you've got particles, and presumably they settle over time, but you could blow… You have single naping gases like CO6, I mean, that it was used in the past. In fact, I mean, uh, and so on.
not very good for the ozone, and that's anecdotic. Big issue, I think, there, this is my take, number five. I think in principle, nothing… I mean, it's not impossible. The problem is going to be basically to get enough scattering to get the point. I mean, like a cloud chamber. I mean, I don't think that we would have that capability. Because you need to, for example, a cloud chamber, as you know, you see the ultra super low, I mean, they are very long tracks, they would be in a liquids, in liquid and in density about one.
um, in a notebook is about, if you're lucky, between 10 to 100 micrometers. So it's 90, maybe the thickness of my head, long story short. So, I mean, by using the gas, you will see these very low tracks at low energies, but the problem is how to pacify, how to get enough of opacity, how to confine enough with something that has a low density. I mean a cloud.
It was a cloud-like system, but a cloud actually is very low density. So I'm not sure how to do that. I mean, in a way, the two things kind of kill one another. I suspect, for example, very often the question comes out, can we do that matter in the kb or something like that?
Because as you go lower and lower in energy, if you have a liquid, everything is more… I need the light bulb. And so a positron is a point, an electron is a point, and proton is a point, everything is a point. So, well, a point, point, point, point where you come back to the original problem. You don't know, you don't have PID. So, for example, that is the kind of range where where liquidity would work.
You can, with glucose integration, lower the density, that's already funky. Maybe you can try something like that and then your events are a factor of two longer by lowering the density. But again, you would have to play with maybe other material gas, I just don't know that.
That's what I really… I really need it, because I think I really had a good idea, please call me anytime.
I think there's a queue for me. Are you my fault? No, no. I think we can talk. You are still around the department, so we can.
in the corridor. Yes. Okay. Thank you. So we have to close the seminar now. Thanks also for people on Zoom.
Thanks.