PassW0rd – 12 March 2025 (Quantum)

Speaker A: This program is brought to you by Resonance FM. If you like what you hear, please support our work by making a donation at resonancefm.com/donate.

Speaker B: Hello and welcome to Password on Resonance FM with me, Peter Warren, your monthly trip to the outer limits of science and technology. In this month’s program, we go as far out as we can go, quantum computing. A technology based upon harnessing the basics of life itself that, according to those working in it, can deliver discoveries that we have not even thought about. Quantum computing is based upon quantum physics, a place that Albert Einstein flirted with and then dismissed as incompatible with his view of physics. It’s a world that goes to the very heart of matter And to the very heart of the matter and to the building blocks of the universe, one that promises undreamt of computational power. It’s a technology the UK government has so far invested around £2.5 billion in, but as in AI, a place where there is a massive arms race with China rumored to be a leader and other countries also limbering up to try to cross the finish line first. Yet, in a science and a technology that many are competing to master, it’s based on a world that many of those working in have trouble not only explaining but also understanding. Which brings me to the heart of the matter, trying to explain something that the experts struggle with. So you’re going to have to bear with me as someone who barely scraped an O-level in physics while having a physicist as a father. The quantum world was discovered by a 42-year-old Max Planck in 1900. Planck had spent nearly 6 years on attempting to understand the fundamental basis for the radiation spectrum produced by an object when it’s heated to a certain temperature. E.g., an electric stove burner turns red upon heating. Planck succeeded and came up with a theory that led to the total upheaval of classical physics and gave us the curious concept of energy quanta. At the atomic level, matter absorbs and emits energy only in chunks, not continuously as classical physics has always assumed. It was a discovery that has absorbed the scientific community ever since and led to the development of even more important technologies like lasers. But recently, quantum physics has started to attract even more interest because of its potential to develop computational power on a scale that has never been dreamed about. The race is on for the quantum computer, a device of unparalleled speed that can carry out a huge number of calculations simultaneously. Mandy Burch, the founder of the quantum computing company Trek, is a Massachusetts Institute of Technology-educated quantum computing expert. A high-ranking officer in the US military and an advisor to the UK government. Birch believes that quantum computers are just as important as AI for solving many of the problems that we face.

Speaker C: So quantum computing involves a being able to leverage our understanding of quantum physics, so a new level of understanding nature at its smallest level and trying to use that understanding and create tools and apply that understanding. What’s exciting, it’s your quantum this year. So we’re celebrating 100 years of codifying quantum mechanics. And that’s historically about the time period that it takes to be able to leverage a new understanding of physics and apply it. I mean, we’ve often defined our eras by the tools we use, the Stone Age, the Iron Age, the Industrial Age. Once we understood thermodynamics, And once we were able to understand Maxwell’s equations, we have the digital age. So we’re about 100 years from that. So it’s the early days of being able to engineer with quantum mechanics. So what that allows us to do is instead of being constrained by the world, the more intuitive world of classical physics, which gives you bits that are 0 or 1, we have the opportunity to leverage the strange world of quantum mechanics that is completely counterintuitive to create new fundamental computational units called quantum bits. And what those do for us is they help us to be able to model things that are inherently quantum mechanical in nature, that are really complex, that we can never have enough computational power with the mathematics we understand behind it to ever model it. So it allows us to encode things that happen in nature directly onto these computational units. And there’s some other hope that they’ll be able to do optimization problems because of the ability for these to hold multiple states of information at the same time that allows some parallel processing that currently bottlenecks our computational capability. So it’s really just trying to leverage what we do understand about quantum physics and apply it to create new tools.

Speaker B: So there is a direct relationship between quantum computing and quantum physics.

Speaker C: Yes, I think we’re trying to leverage some of the quantum mechanical principles like entanglement, being able to have two particles no matter how far apart they are, they are correlated. When something happens to one, it happens to the other. And being able to leverage that for essentially parallel processing is something that we’re working towards being able to do. Constructive and destructive interference on statistics types problems, being able to have different waves and curves and being able to superimpose those on each other is something that we know happens in nature in quantum mechanics quite naturally. So yes, we’re trying to apply that understanding. Right now, there’s a lot of noise, there’s a lot of challenges, there’s a lot of ability to harness that power. It’s an incredibly difficult problem, but Yes, we are leveraging that fundamental understanding to create new tools.

Speaker B: I mean, it’s interesting, isn’t it? Because at the moment, there is so much that’s happening in computing that seems to be in parallel. You’ve got people trying to create these digital twins. You’ve got people who are trying to copy the offline world into the online world so that we can start doing things. I mean, I’ve even had people telling me that people are developing digital me’s and that these are some effective copy of themselves, which is, to be perfectly honest and to use a technical term, bollocks. Because, I mean, psychologists and philosophers have argued about what a me is forever. There’s that famous joke, isn’t there? Descartes, I think therefore I am. Sinatra, I do therefore I am. Frank Sinatra, dooby dooby doo. But what you’re sort of saying is you’re almost extending this, this trend and you’re saying, hey, we can actually copy nature into computers. Can we do that effectively? Could we create an underlying problem if we don’t really understand what we’re doing?

Speaker C: I mean, I think the history of technology development is getting some sort of new understanding of something that happens from a physics level and being able to apply that. So I think being able to look at the potential benefits and the potential risks together is really important because if we can figure out how to capture this most fundamental principle that we understand about the world, I mean, there’s so many potential benefits of this, right? So of course there’s risk, but the benefits really, I think, outweigh some of the risks if it’s developed in a proper way, right? To be able to find new therapeutics instead of a 10-year drug discovery process that you can fundamentally replace much of the wet chemistry discovery process by doing hundreds of millions of iterations on a computer before you even go to that process, being able to really understand energy at new fundamental levels. How do we optimize grids? How do we optimize fuel efficiency? Like, there are so many really important benefits from economic opportunity, for security, for frankly just to capture the human spirit and discovery. So there’s these three big categories of use that I think makes it really an imperative for us to try to understand this capability. Now, I also share your desire to have this technology develop in a healthy way where we have understanding, and it is one of the motivations for why we created Trek the way we do. We are taking an open architecture approach. We see all of this flourishing innovation happening in the supply chain, and yet earlier in quantum computing, there were only these closed-stack companies developing the technology in-house. We think that there’s a better way not only to accelerate innovation by tapping into this flourishing ecosystem and bringing these technologies together. It’s hard to do working with lots of people in a diverse, open way. It is really challenging. But not only does that accelerate innovation, it gets a much broader base of people involved in developing the technology, which I think is one of the keys to decreasing some of these risks, being able to access a quantum computer on the cloud and start experimenting with it. That is one way of creating broader access, and it’s important, but that’s also closed away in a lab somewhere to some extent, and you’re only getting the top end. So we really feel strongly about being able to deploy these systems on-premise so people can get their hands on them and start working with them so that we have the broadest opportunity to get this into the hands of people who share our values, to be able to develop the technology in a responsible way. And I think, you know, your work in AI, there’s a lot of lessons we’ve been learning from AI, and we’re at the beginning of developing quantum, and I’m really hopeful that we can take some of those lessons and apply them to the development of quantum.

Speaker B: Mandy Burch, founder of the Quantum Company, Trek on why we should make the quantum revolution available to everyone. And why not? If it’s part of the fundamental basis of life, then in a way it follows that all life should use it. Though it’s a bit more complicated than that, as Einstein found out. To find out just how complicated, we went to Oxford University, long considered the home of quantum physics research, to find out. Oxford physics professor Sean Langridge is the associate director for science at the ISIS neutron and muon source, essentially meaning that he studies the properties of incredibly small particles on the science that is underpinning this computing technology.

Speaker A: So Peter, you’re absolutely right that it’s now become part of the vernacular. And I think the first thing to say is that quantum is not new. So our understanding of the quantum world goes right back to the early 1900s. And so a lot of the technologies we rely on today are actually driven by quantum. Quantum mechanics is the kind of description that we use to describe these materials. So if you’ve been fortunate or unfortunate, depending on your perspective, to be in an MRI scanner, that will have a superconducting magnet which is driven by the quantum behavior of the materials in that magnet. So it’s not a new thing, but what is new is now our ability to control materials and actually use them in very new ways. And we’ll perhaps say a little bit later on around quantum computation and so on. So to come back to your question, quantum really is this recognition that the world that we live in is very predictable and deterministic. And what I mean by that is we know when the tides will rise and fall, we can predict orbits and so on. All of the things are very familiar to us. But what we realize is that when we get down to the level of atoms and electrons, so we get to the very smallest length scales, we see that those kinds of rules don’t work anymore. And we have to think about probabilities and uncertainties. And that is at the heart of all of the excitement and potential of quantum is the fact that we’re going from a world in which everything is determined into one in which there’s a degree of uncertainty. As part of that, a whole range of other really exciting and useful phenomena result from this intrinsic uncertainty.

Speaker B: Okay, so far so good. Is it that there is this probability at the atomic level Or is it that we just can’t see at that level?

Speaker A: Well, thankfully we now have the tools, and my lab, which is the ISIS Neutron and Muon Source, we have a lot of very powerful equipment that allows us to study atoms and electrons at exactly the right length scale, the size of the atoms, but also the energies, the way in which they’re moving around. And so what we can do is this uncertainty, we start to see it as rather than thinking of electrons orbiting around a nucleus in a sort of kind of almost like an astronomical view of the world, we start to see about these orbitals and clouds of electron density, which is all to do with something that’s at the heart of quantum, which is the wave function. And this is the thing that really truly describes all of the physics, the chemistry of materials. So if we can understand that both experimentally and theoretically, that’s when we can start to apply them into to really new and powerful techniques because there’s a whole load of things that come out of that that we just don’t experience in the real world. And one of those things, Peter, which you may have come across is this idea of superposition. And what that means is that when we think at the quantum level, we don’t just have a sort of a certainty that something’s either on or off. Actually, we have a superposition of all of those possibilities all at once. And it’s not until until we make a measurement that we go inside and look, do we know that it’s a 1 or a 0 and so on and so forth. And we can do this with electrons. We can do it with, with light particles, so-called photons. There’s a whole range of things, but you can see that if you want to get to new computing technologies, then this idea that you’re not just constrained by 1s and 0s, this is the kind of current state of the art of computing that we’re all familiar with, our binary system. We now have the potential to have all of those states at a given time, and then we can make our calculation and see what the quantum state is. And for particular applications, that’s going to be really powerful and absolutely move us to a place which is way beyond what we can achieve with current computing technologies.

Speaker B: Doesn’t that theoretically mean though that you’ve got an indeterminate position, which is your superposition, and you don’t know what that position is until until you do the calculation.

Speaker A: So until you make the measurement, yeah, until you try and read out the state of that computer, that’s where you’ll get the answer. And of course, that is the power of it. The power is that it surveys, if you like, a huge amount of space and possibilities at a given time. So one of the earliest applications, let’s say, of quantum computing would be around cryptography, because in principle it’s very good at sort of trying to challenge some of the techniques that we use to encrypt data and so on and so forth. And that’s because it explores all of this space in a very quick and efficient way. And then we make our measurement and we get out the answer. And that’s something that only works in the quantum world because we have the superposition. So we have all of the states at any given time, but also we have— so another feature of quantum is entanglement, which is If we have these elements, so you’ll be familiar in a conventional computer, we have bits of data, ones and zeros. Now in quantum, rather imaginatively, we have qubits, and these are little quantum devices, objects, could be electrons, could be photons, as I say. And they actually talk to each other in a very profound, fundamental way. It’s something that Einstein really struggled with because it seemed to, at some level, suggest things were traveling faster than light. Light. But that turns out, because there’s no information in these things being transferred, then, then that doesn’t break that particular universal law. But this also means that if we can scale up the size of these qubits to get more of them to talk to each other, then we get more and more power. Now, at the moment, that’s challenging because of the materials properties. And this is one of the things that’s really important. We need to understand the materials that we used to produce these objects, these devices, because then we can make them more efficiently. At the moment, many of the technologies require very low temperatures, for example. So we can do that in our lab, we have lots of experience in that, but if you want to make a device that you can use routinely, then clearly that’s not what people will have in their own homes. And so at the moment, it’s only the big research labs that companies like Google or IBM who are able to produce these quantum computers with maybe 10, 20, 50 qubits all joined together, but they’re all operating at very low temperatures. And that’s one of the things that we would like to study using the capabilities that we have, is that we know the materials that operate at higher temperatures. I mentioned superconductors earlier on. So by understanding these new materials at the atomic scale, then maybe we can find a way to make these things more applicable, make them more sustainable. We don’t want to have to keep things very cold all the time.

Speaker B: That was Oxford University’s Professor Sean Langridge, an expert on the essence of matter and why its movements can create a computer that can help us, in a sense, reprogram the world by building models of how it works in a computer that works in the way it works. Essentially, making a microscope that we can shine onto certain key problems that will allow us to manipulate what is observed through it to see what the outcome can be. Science at incredible speed. The Victorian romantic poet William Blake may have summed it up when he wrote: To see a world in a grain of sand, and a heaven in a wild flower, hold infinity in the palm of your hand, and eternity in an hour. Because the sheer speed and potential of this computational power can simultaneously contract and expand, making its applications literally earth-shaking. For Trek’s Mandy Burch, who we heard from earlier, learning where and when to use quantum is going to be as important as building the computers.

Speaker C: That’s a good way of looking at it. You know, just, I don’t think that quantum right away is going to be applicable to every problem out there. I mean, there’s certain problems that are inherently quantum mechanical, have to do with statistics and probability, that quantum is going to leaf in gradually with high-performance computing. And I think we’ll see starts and fits. I think that, you know, one day someone will announce that they’ve done something better, faster, or cheaper than a classical computer can do on a useful problem. Well, it wouldn’t surprise me if a few weeks or months later, classical computing advances to the point that it overtakes it again. So I think we’ll see lots of back and forth, and, you know, there is a huge discovery process going on right now just to find the applications for which quantum computing is going to be most relevant. And frankly, we need some big breakthroughs. I mean, there are things we understand and we’re being able to engineer with this, but I often see these claims in media, you know, we’ve had a breakthrough. I would say we’re seeing lots of steady progress, progress, but we still need lots of breakthroughs. Those breakthroughs could happen overnight. Someone could have that innovation overnight, or it may take a decade.

Speaker B: Trex Mandy Burge. So we have to decide where we can apply quantum, but of course, before we can even find out how to do that, we have to build the things. And to do that, we have to understand what it is that we are trying to replicate. As Professor Simon Benjamin, a professor of quantum technologies, again from the Oxford University Quantum Hotspot, points out.

Speaker D: Well, Oxford was, I would say, the first university to really invest in quantum computing. That was under a chap called Artur Eckert decades ago, and we’ve never really given up that advantage. So in the In the UK, Oxford is the university with the most quantum people. Of course, around the world there are other universities that invest very heavily, and then you have to think about exactly what it is you want to see.

Speaker B: Quantum. Now, everybody— I’ve been doing all of these interviews and everybody has ended up doing a trick question on me, which is they ask me whether I understand at the end, and when I say I do, then they say that they don’t. So explain quantum to me, Simon.

Speaker D: Okay, well, the first thing to say is that quantum computing has been shortened to the word quantum very often. That’s understandable, but really there’s lots of different kinds of quantum technology. So if you want me to explain quantum, I’d have to take you through quantum communications, quantum sensing, and quantum computing. But I expect you’re most interested in quantum computing. Is that right? Yeah. Okay. So really it’s an idea for a new kind of computer. And it’s one that of course we’re racing to build worldwide in academia and in now many small and large companies. This computer will harness quantum physics at a deeper level than any technology has before, deeper really than life harnesses things with its technology. So it will be a new kind of thing, a machine that can go about solving problems in a profoundly different way.

Speaker B: Okay, as I understand it, with my very limited understanding, it’s doing that because it doesn’t have the positions that the conventional binary computer has.

Speaker D: It is doing that because it is able to use these deep properties of quantum physics, that’s right. So the two that We always talk about superposition. That’s often described as a quantum system being in two places or two different conditions at the same time. So then we have our quantum bit that can be a 0 and a 1 at the same time. And of course, 8 quantum bits then can be in 256 different configurations simultaneously. So that sounds intriguing and possibly powerful, and it turns out to be. And then there’s this second property quantum entanglement that is even stranger for our, our mammoth-hunting brains to get a grip on, and that’s the one that Einstein called spooky. And he didn’t mean that in an encouraging way, he meant it in a derogatory way. He felt that it was the kind of thing that shouldn’t be in physics. But entanglement is the sort of generalization of superposition to multiple components. So these are, these are very strange phenomena, and indeed, you know, it’s famously said that if you If you don’t find quantum physics shocking, then you really haven’t understood it because it isn’t something we can experience at the everyday scale, and therefore we’re really just not ready for it— to understand it, I mean.

Speaker B: Now, in terms of this computational power that derives from this, this is simply because it is, in a sense, so many things simultaneously.

Speaker D: That is a crucial part of it. So it’s difficult to encapsulate in a sentence what it is that makes quantum computers so powerful, but we can say what it needs. And it certainly needs this superposition principle, which allows it to, at least from as we try to understand it, as we look at the mathematics, we’re tempted to say that the quantum computer is able to explore a whole set of possibilities in some sense simultaneously. And that these different possibilities can, we say, interfere with each other so that a single piece of information can be extracted from the multitude. So yes, it’s essential to have superposition, it’s essential to have entanglement, but it is a real challenge to try and encapsulate in a single sentence what gives it its power.

Speaker B: And as you would expect, If you’re going to develop a new computer based on the essence of the universe, it will need to be built differently to the computers we know. Something that explains the announcement by Microsoft at the beginning of this year that it had had some success in developing a prototype quantum computing chip. As Professor Benjamin adds, there is much that we must yet build. Indeed. We have to.

Speaker D: So, I mean, if you’d have asked me that back when I got started, I would have said to you that what we’ll need is a very different kind of hardware than we have in conventional computers. We will absolutely need atoms that are held in vacuums by lasers or tiny superconducting elements exploiting the strange physics there. But actually the good news is that you don’t need that.. And in fact, the company that I’m associated with, Quantum Motion, has shown that you can use conventional chips coming from the same factories, foundries they’re called, that produce the chips for your phone or your washing machine. You just have to design the layout rather differently and then cool them down, which is essential. You have to get to a sort of pristine condition of very low temperature, and then those systems can be your quantum computer. So the More exotic approaches to making a quantum computer are still going ahead. There are many companies and groups powering ahead with those ideas, but it can be as simple as a chip that to the human eye would look as if it had just, you know, come out of an iPhone, but which is in fact redesigned at the smaller scale to create qubits rather than bits. Essentially, the trick is that whereas a conventional chip has as it were, blobs of charge, lots of electrons, the particles of electricity moving from A to B, we instead get it down to a single electron, and that single quantum particle can then be our qubit.

Speaker B: You mentioned these low temperatures. Some people have said that we will be doing quantum computing at normal temperatures, but I assume that that is because we will be doing quantum computing on a quantum computer that’s in some server bank somewhere that is supercooled?

Speaker D: Yes, most of the approaches, really all of them to some extent, require low temperatures. Temperature is kind of noise, it’s disturbance. And when you’re trying to control aspects of the quantum world, you don’t want that. So the temperature you need to get to varies from one scheme to another, but the good news is that you don’t have to worry about that as someone who might use or benefit from a quantum computer. Quantum computer because it just requires a very fancy kind of fridge, which you would then put the quantum chip inside. So we have several of these in our London laboratory, and then as it reaches the low temperatures, essentially the quantum phenomena switch on and we can control the various processes that we want it to perform. But yes, as a user, you would use it online, and we already have members of our laboratory sometimes don’t need to come in and be next to the device. Of course, they can use it online, and that is also the likely model for how we would use quantum computers as they become common.

Speaker B: So some people that I’ve been talking to, some people that we’ve been interviewing, they’ve been saying that you need a quantum computer that’s the size of a football pitch.

Speaker D: Is that right? Ah, well, that’s, that’s where it makes a big difference what kind of approach you’re taking to making your quantum computer. Is it lasers that trap individual atoms in a high vacuum? Is it small but not tiny loops of superconducting material? Is it, is it, is it all these? There’s actually 5 at least very credible approaches to quantum computing with lots of variants, and they come out at different sizes because what we do know from our paper studies of quantum computing is that we’ll want quite a lot of qubits, and that shouldn’t surprise us because of course we need huge numbers of bits inside even a laptop in order for it to fulfill its functions. So we’re likely to want millions at least of qubits into the billions, and if each of those qubits is, let’s say, a square millimeter, that rapidly becomes an enormous proposition, and the full-scale machine, much bigger than anything we have today, would then require something like an entire server center, maybe a building with a staff, mind you, to keep it running, and that’s just for one quantum computer. And unfortunately, a quantum computer can’t really divide its attention between many different users because that will greatly limit its power. You really want to be just the sole user at a time. So I agree with that concern. It would be interesting, but not the best possible scenario, not the most exciting future If we have quantum computers, but each one is the size of a building, and so maybe the UK has one or two, you know, and America has, you know, 10 or 15, and so does China, these would then be national resources that are available to— who would they be available to? Governments, military, Big Pharma maybe, and to alliances of academics. And as an academic who works in this area, I might then have access to such a machine.

Speaker B: Oxford University’s Professor of Quantum Technologies, Simon Benjamin. It is this coming together of the parts of the technology that is beginning to generate the same sort of excitement that has surrounded AI. To actually make quantum computers work at peak efficiency, as with all computers, generates huge amounts of heat. And to counter that, to achieve that cool-thinking quantum computer, it must be cooled to incredibly low temperatures. A problem that Stuart Woods, the chief executive officer of Quantum Exponential, not coincidentally an Oxford-based company specializing in quantum cooling, sets out.

Speaker E: It’s the reverse. It is because we are taking all the heat out that we’re allowing these quanta to exist and live. If you want to call them living, I guess, you know, the transfer and sort of this movement of electrons at these subatomic levels. We have to create that environment and we use helium-3 and helium-4 to do that. And we create an environment where we are able to pull enough of the energy out as well as to shield it from vibration and noise and other elements like that in order to allow it to exist.

Speaker B: What’s the rate of introduction of this quantum cooling? Because obviously the quantum cooling is the essential part of the thing. If you don’t have that, then you can’t start doing it. So what’s the rate of introduction into the data centers?

Speaker E: I think that’s a good question. And I think the other thing to probably to add to that, Peter, is that there are multiple types of quantum computer technologies. You and I can build quantum computers a couple different ways and probably only about 75% of them or the investment is in the cold side of it. There is a whole nother side where they are working to build room temperature quantum computers. Some of those are at different levels where maybe the devices that detect some of the quantum activity is also at a cold temperature, right? Because when you’re measuring from, you know, what you’ve written from— I’ve looked at your website, you know, sometimes it’s the detector side that has to be cold, right? And cameras and different types of surveillance activities. So it’s no different in sensing of quanta. You might need to have the detector cold. So let’s say 75% of the technology or the direction or investment is is within cold quantum computers. I would say the rate of infrastructure outside of labs and university academic environments or research centers is probably just starting over the past, like I said, 6 months. The rate of investment will probably accelerate over the next 2 to 3 years. It is really targeted probably in the mega data centers, the one outside of London down here, there’s some in Japan, there’s some particularly ones, you know, if you look at the US, I think there’s like 5 hubs where everything sort of comes together. You can imagine that it’s only a handful of data centers that are to that point to drive that. And at the same time, you probably are in a handful of large mega data center owners, Equinox for example being one, you can name others, that are actively aware of and driving their infrastructure.

Speaker B: Okay, now you say that people are working to develop room temperature quantum computers. What are the horses for courses arguments in both of this then? Well, why do you need— do the super cold ones perform calculations that the room temperature ones are not going to be as good at? Is the super cold ones— are they the preferred computer of choice for research organizations?

Speaker E: I think like anything that we’ve seen in our lifetime, you start at the two extremes and at some point you meet in the middle. A lot of the activity when you’re trying to get this type of physics to work We need a quiet, cold environment where nothing else can interfere. And it happens that creating these kind of environments at absolute zero is one of the easier ways to create this environment. Whether or not we can learn to create unique materials to raise that temperature so that these unique quantum effects at the subatomic particle level continue continue to— let’s just keep saying that they’re living, for the lack of a better word. As they start to warm up or get higher in temperature, it really depends upon the composition and the uniqueness of the materials. There is probably very much a limit as to how far that can go, and at the same time, much like what we see with detectors with regards to astronomy or astrophysics activities, sometimes it’s it’s best to make the detector so cold that it improves the signal-to-noise ratio. We might see some sort of hybrid activity where some things are cooled and some things are not. And much like anything that we’ve developed in technology, it takes a while for us as humans to find the right recipe for new technology. And we’re still trying to to find that right now. But what’s interesting, and I would say what’s different with quantum, is that at no point in humanity have we been able to take something as cutting edge and to stick it onto the web and give 7 billion people access to it. I think that has caused the technology to accelerate from a brute force standpoint, because that means we want to get as much of a brute force prototype available to these 7 billion people so that we can start to learn the applications, learn which elements of the technology is applicable. And in the case of like what you work with, with cybersecurity, to be able to understand the limits and risks of the technology. And I think that’s part of what’s unique in quantum is that we do live in this cloud age where commoditization of technology is possible. And to me, it’s almost mind-boggling because to be able to now take such technologies, and let’s just broadly talk about it even beyond this, and continue to expose them to the wealth of the minds of the world is astonishing.

Speaker B: Stuart Woods of Quantum Exponential on the problems of both making quantum computing and how we roll it out to everyone via the cloud. We have the physical theory, we have the computing theory, we have parts of the system, and we can cool it. In so doing, we could also cut down on the huge energy and cooling issues that conventional computing systems are developing. And though there is also another significant issue for quantum computing and one that is currently affecting AI development, errors. Data errors in AI are potentially incredibly dangerous. In quantum, given the speed of its processing, they could be terrifying.

Speaker C: That is provably we’ll never be able to have enough computational power to do the math of molecular dynamics in enough detail to run these types of simulations. So that’s, I mean, we’re seeing that happen today. It’s just at a smaller scale. There’s errors. Error correction is one of the biggest problems that has to be addressed right now so that we actually can trust the answers and that we can get enough depth and time on the circuit to actually be able to get meaningful answers. But that’s where we’re seeing great progress. Also in optimization right now, there’s different quantum technologies. I mean, there’s dozens of different qubit types and it’s early days. Maybe the qubits that will be most useful haven’t even been invented yet, but people are using the earlier versions of quantum computing with annealing to run optimization problems. Does it change everything? Maybe not, but if it takes you manually, you have to do an optimization problem. If your crane goes down at a port and you have to reflow your logistics, being able to run a quantum simulation that gets you back on track in 15 minutes versus 2 or 3 hours, that has real business value now. And that is being delivered by some of the early quantum computing companies.

Speaker B: How do you get rid of those errors? I mean, you know, to our poor brains, an error will proliferate at such speed that it will be terrifying, really.

Speaker C: Right, well, I would say that that’s the fundamental breakthrough that we need in quantum computing right now is better understanding error correction. And there’s a lot of research research. We don’t know if that’s going to be done on the chip at a surface level, parity codes, if it’s being done in post-processing. Like, there’s lots of different ways to get after this problem. No one’s had a huge breakthrough. There’s been a lot of announcements in the last year where people have made progress that some of the error correction techniques that Google, for instance, made their announcement with the Willow chip that their techniques will not only scale but actually get exponentially better with larger chips. In the interim, there are huge theoretical questions about how do we know that we get the right answer out of a quantum computer. Right now, a lot of it is around statistics on these smaller-scale problems that we can verify and develop. In ATRAC, we’re really focused on the more practical aspects. There was lots of people working on the theory, and we’re trying to push the boundaries of what’s possible on the practical standpoint to be able to get systems in more people’s hands so that they can do this type of of development work. I do think the cloud offering quantum computers on the cloud is really important so that people can begin experimenting with the technology that’s there. There’s a lot of work to be done to even figure out how to properly integrate quantum computers with high-performance computing. It’s a long journey. I don’t think that problem will be solved with a year or two experiment. I mean, we’re going to learn over 5, 10 years how to do this. So the people who want to capture the first mover advantage, you know, the pioneers, that’s who, that’s who’s working on this now. And we are seeing these projects, you know, do we need, I don’t know how many of them we need, but we certainly do need some of these projects from a practical level to start thinking about how these things can be integrated. And I think, you know, you bring up a really good point about, you know, our democratic values and getting this into lots of people’s hands. I think that there’s a bit of an irony. Our democratic ideals slow us down. People who don’t share our values don’t necessarily have their safeguards on data, AI. They don’t follow the same principles that respect individual rights. And how do we balance this? How do we get this technology into lots of people’s hands and engage in the debate and develop this technology responsibly without slowing ourselves down because of if others who don’t share our values get ahead of us in that way, then we’ve just handicapped ourselves. I think this is a really important question that we need to answer. It’s not just quantum computing, but technology overall as it moves so rapidly. We’ve always, with our democratic ideals, we create space for the minority voice and dissent, but at the same time, we can’t be paralyzed because others are moving forward with it, right? So I think Figuring out how to navigate this tension is going to be one of the big questions of the century.

Speaker B: Mandy Burch, as well as a quantum scientist, is a specialist in geopolitics, and it is this universal access to quantum computing that she stresses must happen if we are to achieve the most from the technology.

Speaker C: And I think just engaging a broader base, I mean, I don’t think there’s another way to de-risk that other than, you know, engaging a broad base of people from diverse backgrounds, diverse cultures, uh, to be able to get after those problems.

Speaker B: I thought diversity was off the agenda these days.

Speaker C: Well, there’s lots of kinds of diversity. I mean, diversity, culture, and values, you know. I mean, we do see, like, right now, much of the work in quantum has been done by PhDs in quantum physics, and that, that’s a pretty narrow group of people. One of our dreams with TREC is to be able to open this up to a much broader group of people. We’re more engineers than we are physicists. You know, there’s people that have RF microwave engineering experience from the space industry that can bring their lessons and experiences to this. There are people that are technicians, electricians, you know, that are going to bring their expertise, and they’re going to have insights So the faster we can begin creating jobs and platforms for engagement for a broader section of society, I think the better off that we’ll be. And we’ll recognize those moments. I mean, some of the challenges with other technology development is we inadvertently give up our agency to these technologies, right? And really just being thoughtful and aware of what do we trust the computer to do? How do we keep the human in the loop? The same conversations we’re having with AI. Where’s the appropriate place for the human to be in the loop and making decision-making and not accidentally delegating that agency to others? I think those are really important. And we have to have lots of people involved with different backgrounds to do that.

Speaker B: Trex, laudably high-minded Mandy Burch. But the problem with all of this is that this sort of computational ability is power. As we’ve seen from the US big tech It now runs and owns the world. At the start of the race for AI, we were told that the technology was so powerful that everyone had to be included in the debate over its future. All sectors of society had to be consulted and would be to make sure that they were reflected in the technology’s development. Yet, at the recent AI safety summit in Paris in February of this year,, it became obvious that that promise had not been honoured as politicians, big tech, and AI experts sat down to decide the future of the technology without us and, as US Vice President J.D. Vance summarily announced, would dispense with regulation as much as possible to prevent hampering the technology’s potential. For though quantum computers promise, like AI, incredible developments for the human race, and for the planet too, if used right. They can also totally destabilize our economic systems due to their ability to destroy all of the encryption systems that are used to protect our money, personal communications, and data. A problem that, according to Tim Callan, Chief Experience Officer of Sectigo, who told me that quantum computers can even strip governments of their encryption, leaving all of their secrets open. A danger that many of those in cybersecurity say explains why the Chinese have been stealing huge blocks of encrypted data in a process that is being called steal now, decrypt later, banking on their country beating everyone else in the quantum computing race. Tim Callan on that challenge.

Speaker F: Yeah, I mean, depends on how big the computer is, but, but what happens is those get bigger and bigger over time. So right, you take something that today would take, you know, 60 million years, and you say, okay, a quantum computer, a fully realized quantum computer, will do it in a week, or even if it’ll do it in a year, for the right secret, a year is still no good. So we really need to come up with a new set of algorithms that won’t have this problem, and this is what the industry and academics and government have been working on for about 4 years now.

Speaker B: Currently though, we found that, as I understand it, the Chinese, but I’m sure the Russians, I’m sure the Americans, I’m sure lots and lots of governments have been accessing lots of databases. They’ve been stealing lots of data and they’ve been storing it up against the time that possibly they can decrypt that information Is that correct?

Speaker F: You’re absolutely right, Peter. And they have a word for this. They call it harvest and decrypt. And the basic idea is, right, if you have really, really, really valuable secrets and I manage to get inside of your network— let me back up one step. One of the things that we do in a defense-in-depth strategy is just encrypt everything. So you go, even if I think nobody bad is looking at this transaction, I’m gonna go ahead and encrypt it anyway, ’cause what if I’m wrong? And that is a smart defense in depth strategy. And that is one of the ways that security professionals feel this is like the last line of defense. If everything else fails, if my stuff is encrypted and undecryptable, then I’m still okay. And if an advanced persistent threat was after a high value target today, and they managed to penetrate the network, one of the things they could do is just grab and exfiltrate every data blob they see. Just store them, label them as well as they can. I got it in this place at this time, and then wait for the day that they have a quantum computer that will allow them to unlock those secrets. Now, for some secrets, this won’t matter. My credit card number is going to be no good in 2 years because my credit card’s gonna expire. My credit card number is also a pretty low-value target. What can you run my credit card up for? A few tens of thousands of dollars. But what about secrets that are long-lived and are extraordinarily valuable? Think about industrial secrets. Think about government and military secrets. The kinds of things, you know, the plans of the nuclear submarine or the location of all the missile silos, right? There are things that are still going to be very very valuable and very important in 5 years or 10 years. And yes, some people argue that we’re already too late, that that stuff may have been stolen and eventually it will come out.

Speaker B: Tim Callan of Sectigo on perhaps the fundamental problem that we face with the deployment of all-powerful technologies: the flaws in human nature.— the one error that Mandy Burch and all of her fellow scientists and technologists working in the area may not be able to correct. Though if we do, says Jennifer Harding, a quantum expert working for the technology consultancy Capco, we could improve the lives of the many and not the few.

Speaker G: I think there are a few key fields that we’re really going to see advancement in quantum computing. I believe the first one will be in chemistry, because in chemistry, when we’re looking at modeling molecules, the fundamental behavior of molecules itself is quantum, and the way that the atoms interact with each other is fundamentally quantum. Therefore, it means that quantum computers are very good at modeling this strange behavior that currently classical computers really struggle with. And obviously that has lots of implications in the kind of pharmaceutical space or material science. So there are lots of players in the industry that are interested in those use cases. And I think that’s where we could really start to see the earlier use cases of it. And then one of the other things that quantum is really good at is performing complex optimization optimisation problems where we have lots and lots of variables and it becomes overwhelming to classical computers. So a few of the industries that are currently looking at this type of optimisation are in finance and logistics. So in finance, one of the use cases that they’re looking at is in derivative pricing. So they’re looking at encoding things like the stock value, the time, the volatility of the stock, and they’re kind of creating that into an algorithm which looks at optimising the pricing for derivatives. And in logistics, for example, we have something— when we look at something like last mile delivery, it’s the case that if all delivery companies in the world just optimise their last mile delivery by kind of, I believe it’s like 1%, you would have hundreds of millions of pounds a year saving in kind of people time, in transportation costs, lots of different things. So difficult optimisation problems that we see in logistics, I think is going to be another really interesting use case for quantum.

Speaker B: So is quantum a very specialised type of computing? Is it something that has an application only for particular areas?

Speaker G: Yes, definitely. It’s not possible for quantum computers to completely replace classical computers, and one thing that quantum computers aren’t necessarily very good at is giving real-time updates. So anything that requires a real-time real-time update quantum will never be able to do, or not as well as a classical machine. And there are lots of problems that quantum is not able to solve. Really, we’re looking at problems that make use of that kind of combinatorial optimization problems, factorization, search algorithms. But there are many kind of day-to-day tasks which quantum wouldn’t be good at, and it also wouldn’t be very practical to use a quantum computer for those.

Speaker B: So I’m not really going to have a quantum laptop is what you’re saying?

Speaker G: Good point. So lots of people are talking about how they think quantum will only ever be accessible on the cloud, but I do believe that there will be other methods of quantum available in the future. That potentially maybe you wouldn’t quite have in your home, but say a research group could have in their office. So it depends on the type of quantum computer that you’re looking at, but having something on site isn’t completely unrealistic.

Speaker B: But the model that everybody’s been talking about at the moment, it seems to be that you would have a quantum computing facility in some big server farm or something like that, and that would then be available for people to use on the cloud, which is something that you mentioned.

Speaker G: Yeah, exactly. I think that will be the most common method for people to use quantum computers. But if we look at somewhere like that’s interested in high security, so say there are health companies out there and also defense companies that are much more interested in having a quantum computer on site. So that could be very large, but they obviously have the space for it. And there are some companies out there that are looking at doing— looking at creating smaller quantum computers. So there are some out there at the moment that are kind of the size of 2 or 3 desktop computers, and they’re looking at creating those to be smaller in the next few years. So it depends on the type of quantum computer that you have. If you’re looking at something that requires supercooling or a complex laser system, then of course that’s going to be extremely large and not practical for most people to have. But there are different types of quantum computers that don’t require those, but unfortunately they’re much smaller at the moment. At the moment, they’re not quite as powerful, so that will be something in the far, far future. So whilst I don’t disagree that the cloud model will be the most popular one going forward, I think it’s important that we don’t discredit the other options available because there are lots of interesting options out there.

Speaker B: Quantum computing expert Jennifer Harding from Capco what quantum could do. So as you can see, both quantum and AI will be inextricably and inexplicably linked, one providing a hyper-powerful platform for the other to run on when it’s not using conventional computer systems. Theoretically, AI would be able to make the decision on which platform the AI should carry out calculations on based upon the technology’s need for processing power. Well, as Birch and Professors Langrich and Benjamin have pointed out, quantum could render our world inside the machine and allow us to understand it in microcosmic slices. We are possibly seeing a move towards telescoping and microscoping worlds, perhaps the metaverses and multiverses that Password has covered in past programs that begin to set out the fundamental ethical problems that these technologies are also ushering in. Who should control these technologies? Who should own them and why? You’ve been listening to Password on Resonance FM, written and presented by me, Peter Warren, and produced by the incomparable Blue Buffery.

Speaker C: Thanks for listening and goodbye. This program has been brought to you by Resonance FM.

Speaker A: If you like what you heard, please support our work by making a donation at resonancefm.com/donate.