 All right, everybody, we're going to get started. And thank you all for joining us this afternoon. We're very excited for this talk and this discussion. I want to first thank Race to Brazil, who organized this largely for us, and then also our partners at Google who helped to get this organized as well. So we have Stefan Leichenauer here to talk to us about quantum technologies. And so Stefan has a background in research. So those of you joining, many of you are, of course, research faculty. Stefan was at Berkeley and Caltech and then most recently, Alphabet, where he was lead engineer for those that are where Alphabet, of course, the parent company of Google and subsidiaries. So you're not here to listen to me. I'm just going to hand it right over to Stefan so we can get started. Great. Thank you, Sean. And thanks, everyone, for coming today. Let me share my presentation so we can get going. All right, fantastic. So hopefully, someone will let me know if I cannot be heard or anything like that during the presentation. But yeah, so today I'm going to talk about quantum technologies, a title of my talk, quantum tech coming soon. So there are lots of ways in which quantum technology is already here or is about to be here. And there are different aspects of quantum technology, which I'll explain, including more than just quantum computing. And it's the kind of technology that's going to impact a lot of everyday life, a lot of areas of not only technology areas, but also application areas, including medicine and navigation, cybersecurity is a big one. We'll touch on some of these. But it's similar in spirit to something like AI, which is itself still unfolding as a technology, but something we've learned over the last five or 10 years or so is that the impact and the reach is tremendous. And so a couple of themes I'll mention that you can maybe pay attention to and think about while I'm going through this presentation are the breadth of the technology, both in terms of the kinds of what quantum technology means, but also the application areas, and how because of the vast reach of this technology and the fact that it's rapidly developing and there's an ecosystem, including universities, as well as companies in the commercial sector, as well as governments, forming and being formed in order to develop and pursue this technology and getting involved even at the level of just understanding what's coming so that you can recognize it and know to use it and have some understanding of how the world works really or how the world is going to work. That's great, but also developing this technology is going to require the input and the work of a lot of people, junior people, senior people. Developing the quantum workforce is a big project for the world over the next several years, and that's another theme of this presentation. So with that, let me just jump right in. So zooming out a little bit, what do I mean when I say quantum technology? What are the three pillars of quantum technologies? And I think these are common buckets. I call them pillars. Sometimes I call them buckets that you can put quantum technology into that I think most people would agree that these are the right buckets. So quantum computing, this is one that gets the most press. And it's because quantum computers, it's a new kind of computing that can do things that an ordinary computer cannot do, solve new kinds of problems. It's sort of like if you imagine on your scientific calculator where you have add, subtract, multiply, divide, exponent, things like that, all those buttons. A quantum computer would have extra buttons that could not be built out of the existing buttons in simple ways. It's a new kinds of operations that let you do new kinds of things and solve problems in ways you couldn't solve them before. Very exciting. But there are other aspects of quantum technologies that are just as exciting and less talked about. And so I'll spend some time today talking about all three of these. Quantum sensing is using the same kind of technology as you would in quantum computing, the same kind of underlying principles, the same kinds of hardware, but built in a different way. Rather than building it to do computation, logical things, logical operations, you build it to make a better detector of things, like the most sensitive magnetic field detector you can make, or a extremely sensitive inertial unit, like a gyroscope, something where you can tell your acceleration with an extremely high degree of accuracy, things like that. And then finally, quantum communications. There are a couple of things you could put in this bucket. Some of them are more quantum. Some of them are less quantum. But it's basically about connecting together quantum devices in a way that preserves the quantum nature as part of it, things like a quantum internet that may exist in the future. But there are other aspects of it that are also important today. So let's dive in. And I'll start with kind of a historical view, or a timeline kind of view. It's useful to think about quantum technologies in terms of the progress in quantum over the last 100 years or so. Quantum is now more than 100 years old, depending on when you decide to trace it back, maybe 120 years old, more or less at this point. And thinking of it in kind of three stages of development. The first quantum revolution back in the early 1900s, maybe the first half of the 20th century, back when the world was black and white and all the people, there's a bunch of people wearing nice suits, scientists wearing nice suits, holding conferences and figuring things out. And that's where quantum mechanics really began. And that's where the basic principles were laid out. And most of the understanding of the foundations happened in the first half of the 20th century, really the first quarter, for the most part. And the second quantum revolution is many devices that are based on quantum mechanics that already exist today. Things like transistors, the MRI, lasers, all of these things exist because of quantum mechanics. And then you could call those quantum technologies already if you wanted to. But that's not what people mean when they say quantum technologies these days. When people say quantum technologies these days, they're referring to the technologies that are being developed now in what you might call the third quantum revolution, which is currently happening. And this is where the technology is developing to take into account or to take advantage of the more somewhat esoteric or the more advanced aspects of quantum mechanics, things like entanglement and really leverage those things to do for very interesting applications. So just briefly into the history a little bit, I sort of can't resist, the physicist in me has to talk about this. Quantum mechanics really got its start back in the around the turn of the century in something called the ultraviolet catastrophe, which was a theoretical problem, which would have said that when it came to the energy in light, say coming out of a light being emitted at some temperature, like out of a light bulb, it would have said that there was an infinite amount of energy coming out or being stored or in this sort of high frequency, small wavelength parts of the light. And this was a theoretical problem. It was just clearly not true that there was an infinite amount of energy sitting around there. And nobody, it was a big puzzle what happened. And Max Planck figured out that you could fix up the ultraviolet catastrophe by postulating a new constant of nature called Planck's constant, which had, and there were some principles that were the early principles of quantum mechanics in there, although Planck didn't really understand them in the same way that we understand them today. Einstein famously in 1905 postulated something called the photoelectric effect or an explanation of something called the photoelectric effect. Here is the paper. And this is what got Einstein his Nobel Prize later on. And this is where the concept of a quantum of light basically was invented, the photon. So Einstein, the root of all modern physics can basically be traced back to Einstein in one way or another. And the photoelectric effect was the real first kind of quantum thing that was understood quite well and quite quantitatively. And then in turn offered further insight into Planck's resolution of the ultraviolet catastrophe. It's kind of interesting how people back then, they didn't, they were figuring things out, but they themselves didn't really understand being, even though they were very smart, they didn't really understand things. So here's sort of a funny quote from Planck about Einstein. Saying that Einstein may have missed the target in his speculations, as for example, in his hypothesis of light quantum. So Planck himself, at least at this one of these, when he said this, did not believe in the light quantum, which Einstein postulated and which provided a nice explanation for Planck's own results, but Planck had problems with it. Of course, then there were lots of other interesting developments. Light was of course a big part of it, things like emission absorption spectra, which are under big parts of chemistry. Chemistry itself, the periodic table was understood in terms of quantum mechanics. And this all happened in the early 20th century. And this is the foundations of quantum mechanics as laid out. The people have heard about things like the Bohr model of the hydrogen atom, the idea that there are electrons and a nucleus and what do the electrons do when they're orbiting the nucleus? All of that understood very well in those early days and led to a lot of very important and very profound developments. So we're not gonna spend any time talking about that in detail now. I just wanted to give some of the history. The famous double slit experiment is another one where first done with photons, but later done with electrons, you could see things like interference patterns, which you may have heard about before, the fact that electrons or any particle sometimes behaves like a particle, sometimes exhibits wave-like behavior, things like constructive and destructive interference. And these are the foundations of quantum mechanics and these are the kinds of things that are taken advantage of in quantum technologies in order to do things like quantum computation. So we'll come back to that a little bit later. Later in life, 30 years later, it was Einstein's turn as Plunk before him was doubting like Quanta, it was time for Einstein later on as the quantum mechanics developed, even Einstein himself began doubting it. This is sort of the cycle of progress in some ways. There's a famous paper in 1935 called the EPR paper, Einstein, Podolski and Rosen, where Einstein considered or these three considered what is now called spooky action at a distance. And they were talking about entanglement. This is where entanglement, which was not really well appreciated in the first 30 years of the history of quantum mechanics, but it's where entanglement was really called out for having such strange consequences. And it's only later and really only now that we're taking advantage of things like entanglement to do for the purpose of developing new technologies and to really taking advantage of the possibilities. And I'm not gonna go deep into what entanglement is or why it should not be considered spooky, but even people like Einstein were confused by it. And it's because quantum mechanics, the thing about quantum mechanics is that it's new. It's different from what we're used to. Funny, there was a funny historical note here. So just before the paper came out, the New York Times published this famous article, Einstein attacks quantum theory in 1935. And as the story goes that it was Podolski, the middle author here, who leaked the story to the New York Times and tried to get a lot of attention. And Einstein himself was very, very upset at this. And supposedly never spoke to Podolski again because he was very much against the idea of leaking and having sort of scientific discourse in headlines of newspapers. That did not sit well with him. And so it was another famous Einstein work in 1935, that same year, which was Einstein and Rosen without Podolski, inventing what are now called wormholes or Einstein-Rosen bridges, which are not at the time, they thought it was not about quantum mechanics. It was a different subject, although now we realize there's actually a deep connection between those two ideas. But I think, I don't know, it seems like Podolski was booted out of the collaboration perhaps. Interesting kind of history there. So that was the first quantum revolution. And in the second quantum revolution, this is where we get things like transistors, the MRI, the lasers, things that we're used to and used to talking about. So these are technologies that work because of quantum mechanics. You need to know quantum mechanics in order to design them at their most basic level. They're used to use a computer that's built out of transistors or to operate an MRI machine or to fire a laser pointer. You don't need to know quantum mechanics. And that's true about all technologies. You don't need to know how they work in order to use them. But it's important sometimes to appreciate what goes into these technologies. And so all of these are also based on quantum principles, but they don't take advantage of, say complicated patterns of entanglement or things like that. I wanna call out the MRI machine in particular as a very advanced kind of machine in some ways, but very primitive in other ways. So the MRI machine, it works because of quantum mechanics and it's a really miraculous thing that has impacted us in a lot of ways, impacted our lives. But it's also, I mean, as you can see in the picture, it's really big, it takes up a whole room. It's a special room. There is another room full of electronics next door to this room that controls the thing. And it has to use, there's cryogenic low temperature stuff happening inside. And a lot of, and that's, in that way, it's kind of primitive. So some of the more modern kinds of quantum sensing advances, this is something that you might classify in the quantum sensing bucket that uses quantum mechanics to detect things, will perhaps not maybe not displace the MRI machine, but operate in similar capacities as something like an MRI machine. But some of what we hope to improve upon using more modern technologies are, say the device footprint, maybe the device doesn't have to take up the size of a room, but you can still get useful kind of medical diagnostics out of it. That's an example of a kind of device. And I'll give a couple of examples later on of some more recent quantum devices that could be useful for things like medical diagnostics that don't have to be the size of a room, don't have to be at cryogenic temperatures, things like that. So we're always, this is a historical, a little bit of a historical perspective, but things are always improving. So now what about today as we enter sort of the third quantum revolution? So first thing to know is that there's a lot of money in quantum right now. These numbers I think are a little bit old, but governments around the world, as well as private industry are investing a lot in quantum and the quantum development. And this is something that's going to likely continue. And this comes in the form of, well, not only in the private sector, there seems like every day there are new like even public companies being announced or companies going public, working on quantum technologies. Maybe we're in a little, maybe there's a little bit of a bubble, who knows, we'll see what happens there. But certainly there's a lot of money going into it. And in the public sector, a lot of this money ends up in grants to universities and things like that, where a lot of the technology is sort of being developed, or at least the basic principles of the technology. And the move or the fact that the private sector is really getting into it tells you that there's a move from focusing solely on the basic science, which happens mostly in universities. And surely there's a lot of basic science left to do. But the fact that the private sector gets more and more involved every day is a signal. It's the market telling you that actually there are many, many of the fundamental science problems are solved or close to being solved. And there's some more engineering and scaling things that need to be done, that can maybe be, and productizing that can be handled by the private sector. It's kind of interesting to compare the quantum investment to the AI investment. And if you think about where quantum is and where AI was back in 2013, you might try to draw parallels from the technological maturity point of view as AI was just getting started, now quantum or at least the latest third revolution of quantum is just getting started. But the overall investment in quantum right now is much higher than it used to be in AI. Of course, now AI is really big. So now let me address, let me go into some of these areas, the three pillars, we'll start with computing and computing, there are sort of several slides to go through, but I won't spend too much time or I'll try not to spend too much time on computing since that's the one that gets most attention anyway. But some of the information out there about computing, quantum computing is not, sometimes the message gets muddled a little bit. So I'll try to give my view or sort of maybe a slightly more sober view than people sometimes give. So first, it's important to understand what I mentioned that the way quantum computing works or the way quantum technologies work, it's different than classical technologies. You sort of have extra buttons on your calculator, things that you couldn't do before. And it's very easy, I'm not gonna try and be super technical in this talk. I will say now and I'll say it again later that at some point you have to get very technical if you want to understand this stuff, you need to talk in like using the language of math. There's just no other way to do it. Every time somebody tries to use language that's not math in order to describe what's happening in quantum mechanics and quantum technologies and anything like that, inevitably something is lost, something is missing. This is just a problem with language. This is why math is so useful in the first place is because it is kind of the right language to talk about things. And if you're not using that language then it's just, some things are gonna be lost in translation. So we'll try our best without the math but for those of you who are students especially, please know that you do have to get into the math in order to really understand what's happening. And it's not the hardest math in the world but it is a requirement. But the building blocks of a quantum computer and in many ways these are the building blocks of all quantum technologies are qubits. So the interesting thing about a qubit where you can compare a qubit to a bit. What is a bit? A bit is the zero or one in an ordinary computer. And the way a zero or one is stored is say on a capacitor which has like a positive side and a negative side when it's charged can basically be in two possible states. Zero say if there's no charge or if there's some excess positive charge say on the positive plate, then there's charge is present the capacitor is charged and we call that one. We give that a label. So we've got two, we've got a physical system in this case a capacitor and we've identified two possible states of that capacitor zero or one. And then depending on the patterns of zeros and ones in millions and millions of capacitors we could do things with that. The charge keeps track of information for us and let's us do fun things. A qubit on the other hand the other thing that's interesting about the classical bit is that you may have many capacitors giving you many bits, but each capacitor itself is made up of many, many small parts. There are millions of electrons stored in a single capacitor when it's in the one state. That's kind of interesting. It's not like a single particle. It's many, many particles together. So a qubit is different. So a qubit like the bit the qubit is a physical system. In this case, it's not something as you know it's not made up of sometimes it can be made up of many things but usually it's much simpler. It's perhaps like a single atom but you identify two states that it can be in and you again label them zero and one but there are many more possibilities in quantum mechanics and those possibilities this is something that people don't normally talk about in lay explanations but those possibilities can be represented by this sphere by the surface of the sphere. So zero is say the arrow pointing up the arrow can point to any direction on the sphere and one maybe is the arrow pointing down those are two possible states but there are many other possibilities for the qubit. The qubit could be in this other state pointing in some other direction on the sphere there's just a lot more going on in the qubit. It can do a lot more things than just be in zero or one and sometimes these points that are on the sphere but are not at the north or south pole not in zero or one. Those are the superposition states and the fact that those things exist and they must exist according to quantum mechanics that's one of the basic rules of quantum mechanics. The fact that those things exist means that the qubit has a lot more flexibility a lot more interesting things you can do and the pattern of qubits if you had many, many qubits that they can do things besides just be in zeros and ones each one in zero or one there can be many, many other possibilities for the states and these states can interplay with each other in very interesting ways. It allows you to do operations besides just flipping between zero and one and that's where the extra power comes from. The language that we use to describe how to work with these qubits the sort of dance that the qubits undergo is played according to what looks like this this looks kind of like shit music in a way and this is the language of quantum circuits. So I'm not gonna go into the details of quantum circuits but this is a language for that we use when we program a quantum computer and we say, what does a quantum computer do? Well, let me tell you how the qubits interplay with each other, different operations that the qubits perform. And you sort of read it like music like notes on a sheet music where each line represents a different qubit and these interactions between the qubits. And the whole point is to make these qubits do interesting things involving these in-between states that are not just zeros and ones. So we could go deeper into the technicalities which we're not going to do but the point is this kind of quantum behavior is something that classically or with an ordinary computer you can try to calculate like you would on a piece of paper or just use an ordinary computer to calculate what's going to happen when the qubits undergo these operations but it becomes very quickly impossible. When you have several qubits say 50 qubits and you wanna figure out what's gonna happen to those 50 qubits as they undergo some sequence of quantum operations already with 50 qubits, the top super computers in the world would have trouble calculating what's going on with 50 qubits, 60 qubits, 70 qubits, 80 qubits, 100 qubits forget about it. And so the quantum computers are really doing something completely new. There are many algorithms that take advantage of this. We're not gonna go into detail on most of these algorithms but one important point that I wanna get across before moving on is that quantum computers are not magic. There's a few things, these extra things that they can do that ordinary computers can't do, they're very special and you have to try really hard to figure out how to take advantage of those. And here's like a small list of algorithms which to various extents take advantage of the quantum nature of things but it's a lot of hard work to figure out a useful quantum algorithm and there's still a lot of work to be done, the list is not exhaustive but it's also not the case that a quantum computer automatically helps you with every problem. There are very few problems that a quantum computer has a real advantage over a classical computer but the applications of those few problems are many and I'll touch on some of these as I go through or we can sort of leave some of it to the questions. I will say for those of you who are more interested in this kind of thing as an example of current algorithmic development in quantum computers there's some like recent work from out of MIT for example which kind of takes that small list of quantum algorithms and thinks of them in like a single framework that has a lot of interesting properties. So the bottom line here is that there's a lot of current, there's a lot of active development of trying to make use of these quantum operations to do useful things, developing the algorithms. It's not very, it's not cut and dry and there's a lot of theoretical work going on. One would hope or one, it's not so hard to believe that when we have bigger and better quantum computers to actually play with the speed of algorithmic development will likewise increase and who knows what the ultimate endpoint will be sort of like how the development of ordinary computer algorithms or the development of say AI had to wait until the computers were powerful enough to actually run the algorithms. So it's kind of a stay tuned situation when it comes to quantum algorithms. We'll come back to this later, but as I said before, not all algorithms are useful. Some of them have exponential speed up, some of them don't. Very few of them have been identified that have good exponential speed up which means it's something where a quantum computer really, really can help. We'll come back to that in a little bit. Just a few points on use of a quantum computer, some more practical things. So the future of quantum computing is probably, it's not just quantum computing. It's quantum computers interacting with ordinary computers and doing like a hybrid kind of approach. That's the way you should think about it. So here, for example, this is a graphic that I took from a Google paper that was explaining the TensorFlow and TensorFlow Quantum and how it uses a variety of processing, a variety of ways of processing, including CPUs, GPUs, QPUs, which are quantum processing units, at least in principle, it can use these. And you can put together, there's a whole software stack that allows quantum operations and classical operations to play together. And this is for the application of machine learning. So the software is already being written. This is one of the activities happening now and it's kind of an open problem. What is the best software stack in order to take advantage of these emerging quantum algorithms? This is development that's happening that's not just putting together the computer but putting together the software packages that one needs to use the computer to write the algorithms, to discover the algorithms, to implement the algorithms. What is the best way to do it? Well, there are ideas out there but this is an area of active development, something that people will be improving upon over the years. What could a quantum computer be useful for? Well, one option is to, if you had quantum data, some problems, like I said, not all problems are, quantum computers are not useful for all problems. One class of problems where quantum computers will be useful is if the problem itself is quantum mechanical in nature. Now, who has such problems? Well, physicists have such problems. Physicists who are doing experiments trying to discover new materials or do basic science on new materials. And there was some work recently on using fancy quantum processing to understand the properties of materials and basically doing a version of machine learning where the machine learning part was not too complex but if you could use, if you could have quantum ingredients or quantum processing in order to try and understand these quantum materials and then you put on, put a little bit of simple machine learning on top of that, then you could really understand in some interesting way using the power of entanglement and entangled measurements and probing your system in a way that was, that involved harnessing the power of entanglement, it could be useful for physics. So it's natural that this is the kind of an early application of quantum computers but it's an important one. And then that itself could lead into further discoveries down the line. Richard Feynman used to say that back in the 80s in the early days of quantum computing, just thinking about the idea of what quantum computing could mean that this kind of thing is along the lines of the first, this kind of thing is along the lines of the first envisioned applications of quantum computers, namely to understand better the physical world, which is quantum mechanical itself. And of course, as I was saying before, you could string these things together with ordinary computers to make some hybrid model of computing and that's where the future is going. So I'm not gonna spend a lot of time talking about the different kinds of technologies or all the different companies that are working on, that are working on quantum computing, but there are many, there's new ones coming out every day, each of them has a roadmap of quantum computing that they think, oh, this is where it's going. And this is all very interesting. Sometimes people say, oh, quantum computing development, it's been 10 years away for 20 years. And some people have a fair point, sometimes the quantum computing is overhyped. But I should say that in my view, quantum computing is more of a when rather than an if. It's true that there are some unanswered questions in how we go from the small quantum computers that exist today with less than a hundred qubits to the million qubits or millions plural of qubits that we might need in order to do some of the really interesting applications. But there don't appear to be any kind of fundamental obstacles to solving those problems. And the advancement when it happens, it'll likely happen in fits and starts, right? Like the, it's not gonna just progress linearly. Like the, all of a sudden before you know it, where there's gonna be a, once we get to thousands of qubits going from thousands of qubits to say tens of thousands or hundreds of thousands of qubits might happen much faster than getting to thousands of qubits. And I'm not just saying that. There are reasons for that. It has to do with error correction on quantum computing. Once you've tackled the problem of error correction, which you can do with a level of say a thousand to 10,000 qubits scaling up from there. It's a different set of problems, but in some ways it might be an easier set of problems to solve. So it's hard to predict, but it may surprise us the development of quantum computing in the future. And as I've mentioned, there are many, many, many companies getting into this, which sort of, you know, it's a sociological argument for the fact that this is coming. So, you know, if anyone wants to ask me at the end about some of the actual technologies or some of the, some of what's going on, please feel free, but we'll, for now we'll move on to some of the other areas. So sensing, all right. So computing, we took care of computing. Now let's talk about these other areas which don't get as much attention. So let me say again what quantum sensing is. So the reason why quantum computing is so difficult is because these qubits, these little very tiny sensitive or these tiny units of quantum information that you try to put together to do computing, they're very sensitive. They, you have to shield them very strongly in order to prevent them, even one stray photon, if it hits your quantum computer in the wrong way could just ruin the whole computation. And eliminating all of that noise is a big struggle. And that's why quantum engineering of quantum computer is very hard. It's sort of the hardest thing you can do within quantum technologies, you know, scale. If you, once you've made a scaled quantum computer, it means you can do pretty much anything you want as far as the technology is concerned because you've solved so many problems along the way. But if you're not, but if you have a different objective like quantum sensing, the path forward is much easier. So quantum sensing is kind of taking this, you know, it's turning a bug into a feature almost. The fact that the qubits are extremely sensitive to the environment is now a good thing. Before you had to shield them from the environment if you were trying to do quantum computing, or for quantum sensing, you know, you have to still take some care, but you actually want them to feel what's going on in the environment. And you use that as a way to tell what's happening in the outside world. And so a, and that's what, you know, in kind of a little bit of a hand-waving way, that's kind of a motivation behind thinking that quantum sensors might be a good idea. And there are examples of this because it's the kind of thing that, you know, does not require that you solve all the problems you would need to solve to build a computer. It's a much more near-term technology. So this is one of the main messages that I wanted to give today. It's a much more near-term technology. There are quantum sensing, there are also quantum sensing companies out there that don't get as much attention as the quantum computing ones. And there are quantum sensing devices that are being developed and, you know, third-revolution quantum sensing devices that are either on the market or could be on the market very soon that are not taking maximal advantage of things like entanglement, but, you know, they will eventually, but even on the way there, there are interesting things you can do even at today's level of quantum technology. 10 years from now, at the same time that you have big-scaled quantum computers, you'll be doing even more amazing things on the sensing side, but along the way, there's an interesting path to progression. So here's an example. This is this nice medieval torture device. It's not a torture device. It's a brain scanner, measures magnetic fields from the brain, magnetoencephalography. Using each of those devices, each of those black sort of pen-sized devices plugged into the helmet is a quantum sensor. That is a very sensitive magnetic field detector. And the whole thing, you know, reads magnetic fields generated from your brain, from the electrical activity in your brain. And this lab that created the sensor that has since spun out a company that is, that created this helmet has since spun out a company about this topic. And the actual devices themselves, the actual sensing devices themselves, at least in that prototype came from another quantum sensing company called QSPIN, which builds these kinds of quantum sensors. Another, so they used a certain kind of quantum technology. There's another kind of quantum technology called the Nitrogen and Vacancy Center and Diamond. This is one that, it was mentioned on a slide that I've kind of skipped past before, but it's, you know, sometimes people talk about atoms as being good qubits. And, you know, if you want people building quantum computers, often trap atoms, say in the form of ions inside laser traps and, you know, have to be very careful about how they're handled and things like that. Another way to deal, to have almost the same kind of structure is rather than trapping an atom or an ion in lasers, you can sort of trap it inside of a diamond. That's at least that's one way of thinking about it. And so you have these little impurities inside of the diamond and maybe you have millions of them and each of them can act like a qubit. And this kind of technology is maybe more challenging to use for computing, but it's very interesting for sensing and communication. This kind of diamond based technology. It's the kind of thing, the thing that's interesting about it is that it does not require ultra cold temperatures. It doesn't require a lot of laser traps and things like that. It's much more simple, closer to being off the shelf kind of technology. And there are companies out there also taking this kind of thing to market. So an example is QDTI. QDT is quantum diamond technology. They are creating a, they have already, you know, in prototype form, a device, you know, it's a box, that has this kind of magnetic sensing technology inside of it using these diamonds and they use it to detect things in blood, in whole blood. And so this is a promising future tool for something for different kinds of medical diagnostics. This is an example of an emerging quantum technology, the quantum sensing technology that is essentially here today or at the level of, you know, it's very close to market, at least as compared to something like quantum computing. So this is worth appreciating. Once in a while, you read about quantum radar, which is, you know, maybe it's less clear if quantum radar is as, you know, quantum radar might not be as close to market as some of these others, but this is another one that comes up every once in a while. This is making use of entanglement, entangled light in order to detect objects that are far away in the same, in a similar way as ordinary radar, you know, bounces light off of objects or different wavelengths of light off of objects in order to tell that they're there. Adding entanglement to that picture makes quantum radar. This is another thing that's in development. Something I alluded to before, there are different versions of what you might call a quantum compass used for navigation or positioning, things that can detect different kinds of acceleration or similar kind of technology can be used to detect the strength of, you know, the gravitational field. You know, there's those of you who are, you know, have taken physics classes, know that there's a relation between gravity and acceleration. And the, so you can use these, you can use these kinds of things in order to, in order to build very sensitive inertial sensing devices or very sensitive gravitometers for say underground surveys, survey, you know, what's happening, what's happening under the ground. Well, let me try and figure it out by doing a very sensitive survey of the gravitational field to find say mineral deposits or natural gas or something. This is a very promising technology. Again, it's something that you don't hear about all the time, but it's happening right now. There are devices out there right now that are at least in the prototype level working on these things using, you know, quantum principles like interference and so on. So now that's sensing. Let's move on to communication. And this will be sort of the last section and then we'll stop for questions in a few minutes. So this one, this one is kind of interesting. There's two points to make here. One is coming back to this idea of quantum computers and I can't give a talk about quantum technologies without mentioning this, but let's say you believe that quantum computers are coming and what I'm about to say is even true even if you have doubts about whether quantum computers are coming or not. But the fact is that quantum computers are a problem for cybersecurity and this has to do with one of those very few, one of those algorithms on the very small list of algorithms that is known and it was discovered in the mid 90s that uses quantum computers. The problem is that there's an algorithm that has an exponential advantage when run on quantum computers that you can use to break modern cybersecurity crypto schemes without going into the details. Basically, public key cryptography as implemented today depends on the fact that certain things are hard to do and those things indeed are hard to do with ordinary computers, but not so hard with quantum computers. And this is because of this exponential advantage with this algorithm. And it's kind of, didn't have to be this way but as history unfolded, it turned out that we based a lot of our cybersecurity on these issues which quantum computers happen to be able to attack. It's a little bit coincidental, but that's the way it is. So the Shor's algorithm as there's kind of Aquaman attacking Superman here. And Shor's algorithm spells trouble for RSA. And even if you think that this might be a long ways off that we're a long way from having such a quantum computer that can actually implement this algorithm, which is true, at the level of risk assessment, it's still something you need to take into account. And there are a couple of ways to address this risk. One is with post quantum cryptography, which is kind of an adjacent, it's kind of an area that's adjacent to quantum technologies but it's worth mentioning. It just means redo your conventional cryptography doesn't involve quantum at all, but don't make use of algorithms which have this quantum weakness. This is something that could have been done a long time ago, but there was no reason to do it because we thought we were okay. Another thing you could try to do is quantum cryptography. The naming here is a little bit confusing with schemes such as quantum key distribution. This is actually using quantum technologies, using entanglement, using superposition in order to generate kind of secure keys that you can then use for cryptographic purposes, things like that. And there are pros and cons to each sort of approach. It's worth mentioning that post quantum cryptography is an area under extremely active development right now. There's a standardization process happening and actually later this month, keep an eye out for it in the news, we expect that the first, that there will be some first schemes, this standardization process has been happening for multiple years now and steps toward actual final standards are gonna be taken later this month. So keep an eye out for that. And then it'll be, there's plans being put in place for years worth of upgrades, cryptography upgrades that take into account this issue. Something like QKD, quantum key distribution uses entanglement or other principles of quantum mechanics in order to avoid this issue entirely and the claim is that one can have security using based on the principles of quantum mechanics, not based on the fact that it's hard to accomplish some tasks using an ordinary computer or a quantum computer, just that if we believe that quantum mechanics is true, which of course we do, then there should be, then there's some security guarantees because of some clever uses of things like entanglement and superposition. And of course there's a debate over exactly how useful this is, but it's worth understanding and knowing. And the most interesting thing about it though, perhaps is that the same kind of technology that you would use for something like quantum key distribution also happens to be the basis of technology you would use to make a quantum internet. And this is the kind of thing you would need in order to connect together quantum computers. Really, when you wanna run some of these very sophisticated quantum algorithms that take millions of qubits, when you have like a, rather than have a single gigantic computer, maybe the right way to think about it is many smaller computers connected together. And connecting those computers together, whether they're in the same building or not, you can think of as like a quantum internet. And so working on aspects of the quantum internet or the connections between quantum computers is another aspect of quantum technology that's very important. And of course has overlap with this other QKD which has a different motivation. So that's kind of quantum communications. I'll just end by saying, oh, it's kind of reminds us of, it might remind you a little bit of the early days of the ordinary internet where nodes, various nodes between like universities and government labs and so on were set up that created what is now known as the internet. And a similar thing will happen in the next few years as different kinds of channels, different, there's gonna be a setup of different quantum communication nodes. So I'll conclude by just mentioning that again, there's lots of opportunities here, lots of activity happening, public sector and private sector. This is not even a complete list of companies that are involved. There's an impact in all kinds of areas both on the computing side but also like the sensing and communication. And all of these areas are gonna need people to work on. There's beyond like the domain expertise that you would need in each of these areas. There's gonna have to be in the same way that in addition to whatever domain you wanna work in, you should also learn AI and ML because there will be applications of AI to that domain. The same is gonna be true for quantum. So you've got your domain expertise but then there's also the basic understanding of quantum in, contained in some of these other STEM disciplines that the workforce will be needing. All right, so I'll stop there. Thank you, thank you so much. And I think we have a few minutes for questions. And we indeed we do. Thank you so much, Stefan. I would like to invite anybody who would be interested in asking a question. You can, if you don't feel comfortable raising your hand, please go ahead and include that in the chat box. And we'll go ahead and start with Drew Brown. Drew, would you like to unmute yourself? Sure, thank you. So, okay, I can start my video as well. It's like, thank you. So my question is a little bit around what we should be doing to help the public when it comes to quantum. The public already understands so little about the world and now they're gonna have increasingly approaching their lives, things that appear magic. But any thoughts on what we should be doing to help the general public to prepare for the existence of quantum devices happening around them? Yeah, yeah, I mean, that's a good question. I think myself, my first reaction to this and something that I'm trying to get involved in as well is to try and provide some kind of basic level of education and understanding so that it doesn't seem like magic. So I guess the first point is that you don't need to understand quantum in order to be like an ultimate end user. If you wanna like help develop, then yes, but to be an ultimate end user, you don't need to understand. But for things like policy makers, for instance, are gonna have to have some kind of understanding and voters should have some understanding of things when they're, and so this is a problem that AI has and a problem that quantum has. Both of them have this reputation or it's this sort of sense of being magical and solving all problems. And we don't understand what's happening on the inside. These are all things that get repeated about all of these subjects. And it's not, I mean, the truth is like very, very like nuanced. And so I think trying not to overhype things is a big first step. And having more kind of public facing education things, things that people can access, having quantum be something that's not just some class that you take in the physics department, but a thing that is trying to change the narrative that it's actually accessible, right? Don't give it, don't feed in the reputation that it's inaccessible. I think that's like the first step. We had somebody ask if these slides will be available. Stephen, is that something you're okay with? Or do you wish we, we're gonna share the room, we'll have the recording available. Yeah, so the recording will be available. I'm not sure about the slides. The recording is fine, but the slides, maybe we can get to that offline or something. Sure, thanks. I've received a couple of direct message questions that I can try to try to answer. So, someone is asking about what is the, about attractive candidates for different, different like qubit modalities like trapdion or those MV centers and diamond, which of them are better for things like quantum communication? I think in a lot of ways, the jury is out on which kind of quantum technology, which kind of like hardware is best for which application. People have different horses and depending on who you ask, we'll get a bunch of different answers. I think really what we'll probably find out as a community is as these things develop, we'll just find that there are different, different technologies are useful for different parts of the stack. Which ones are most useful for which, I'm not sure, but there are certain kinds of advantages or disadvantages. So like an example possibility is that like something like trapped ions, the thing that's cool about trapped ions is that they're extremely robust, like they last a long time before decohering, before becoming useless, before losing their quantum properties. And so they might be attractive for something like a quantum memory where you wanna store information for a while. Kind of the flip side of being able to having this long lifetime is that manipulating the information stored in a trapped ion system. It's slow compared to other situations. It's kind of the fact that these are almost two sides of the same coin. You sort of get one with the other. And so it might be, I mean, this is certainly not a consensus by any means, but you could maybe find out that something like a trapped ion is useful for like storage of quantum information. But then when you wanna do some rapid computations with it, maybe you kind of move it to some other modality and then compute with it for a while. You know, there'll probably be a hybrid approach for any given application, ultimately. Stefan, I realize it's 401. Are you comfortable staying on for a couple of hours? I can stay for a few more minutes. Yeah. And answer similar questions. It looks like we have Doug Jennywine who has his hand up. Do you want to unmute yourself, Doug? And go ahead and ask your question. Good thing. Thank you, Stefan. Fantastic talk. I lead the research computing group here at ASU. We support high performance computing, super computing. And our message is always solve bigger problems faster, always in on size and speed and wanting to save researchers time. And I wonder as quantum computing resources become more the norm as a campus resource, what our messaging to researchers, to faculty and how that might need to change. It doesn't sound like quantum is exactly about speed. You gave a good example of scale and size with the qubits to bits example. But I wonder what the messaging is if it's not speed. What might we say? Yeah, that's a good question. So let me first emphasize that quantum computing is not about speed. Let me just emphasize that point that you already said. A quantum computer in principle can do anything that a ordinary computer can do. It can do all the same stuff, but that would be a very poor use of the quantum resource because a quantum computer will be extremely slow and cumbersome when it comes to doing things that it does not have special advantage. There's a very straightforward reason for that. It's because a quantum computer is a very complicated device and every basic operation on a quantum computer takes a long time and is a lot more going into it than a basic operation on a classical computer, which is just like shuttling charge around on wires at some base level. And so for ordinary, and this is why the hybrid model of computation is what's important to you. You do as much as you can with the ordinary computer, could be a laptop, could be a supercomputer, could be cloud-based. And then you kind of think of the quantum computer as like a special machine that you pass like a subroutine over to when there's a particular part of the algorithm that happens to be amenable to quantum computation, then you just give that piece to the quantum computer. And so the use of quantum computer is really about identifying those subroutines that can run really well on a quantum computer. And there's a very small list of things that we know of right now, things like Schwarz algorithm and so on. Or if you're studying like a physical system, like if you're like a popular use of supercomputers is to do things like big chemistry simulations, for example, which are ultimately quantum mechanical. And so if there's a good chance that those kinds of things would be well handled by a quantum computer because quantum mechanics is intrinsic to the problem. And so the first step toward using a quantum computer efficiently is to identify those parts of the problem or algorithm that are useful for quantum computers and then develop a scheme where you can kind of shuttle that part off to the quantum computer and then use your supercomputer for the rest of it or your cloud-based computer. The other thing that's worth saying at this moment is that certainly today, but probably also in the future, you should not have your own quantum computer. Nobody should own like a quantum computer and have to maintain it and have the expertise to use it and things like that. Quantum computers make a lot of sense as cloud-based devices that you sort of access when you need them. But I think very few people would probably want to have their own quantum computer, at least for the foreseeable future. Who know, 100 years again, 100 years from now, who knows? But I think for the foreseeable future, that's the way it'll be. Stefan, I received a question in chat. What is the advantage of quantum internet? So quantum internet, for the same reason that quantum computers should not be used for ordinary things, you should not use a quantum internet for things you would use the ordinary internet for. The quantum internet is really useful for two things. One is maybe, and this is kind of a big, there's lots of asterisks here, maybe you could use it for different kinds of secure communication. If you cared a lot about security, a quantum internet may come with security guarantees when you want to send information to your friend. But there's a lot going on underneath the service in that question. But the other thing the quantum internet is good for is transmitting quantum information. So if you have a quantum computer that is doing some kind of like, I mean, I just got, I just said that quantum computers maybe are, maybe the best quantum computers are located centrally in some, not everybody has one, right? They're located in quantum data centers, so to speak. But maybe you have locally say in your university lab, some quantum sensor or that you want to, that sensor is collecting information, collecting quantum information from the world, but it needs to be processed on a quantum computer. Then you would have to transmit that information somehow to the quantum computer, whether it's in the same room as the quantum sensor or across the country. There has to be some kind of information transfer and it has to be quantum mechanical in nature, like the whole way. You cannot like go from quantum to non-quantum and then back to quantum, the ruins everything. And so that's what you would use the quantum internet for is to transmit that kind of quantum information, say from sensor to computer or between computers, things like that. That's something like a quantum internet that's more than just connecting things together in one room, like a quantum internet like across the country. That's a very far, that's a far future kind of quantum technology. Like that's not the kind of thing that's going to be happening tomorrow, but it's interesting to imagine. I appreciate that. I hadn't actually heard that stated plainly in terms of the need for transmitting that way and not ruining it all, as he said. We've been even generous with your time. We greatly appreciate it and we can let you go for now, but I've been getting messages the entire time. Everyone really appreciates the presentation and how you spelled things out. It's been super informative. So thank you for that. And you're always welcome back. We'd love to have you back sometime in the future. But for now, thank you very much and we greatly appreciate it. Great. Well, thank you for having me and thank you everyone for coming. I hope it was good. Absolutely. Take care. Thanks everyone.