Alright, not going to lie - quantum physics is tough! But our specialist guest John Azariah does a great job at breaking it down…using mayonnaise and beach balls. From quantum entanglement theory, to solving climate change, if you’ve ever wanted to know all about quantum computing, then prepare to dive in!
The discussion covers:
- Entanglement theory
Do we already have quantum computers?
Truly random sequences
What is a qubit - the beach ball analogy
Quantum mechanics in nature
Solving climate change with quantum
Superconductors & quantum batteries
John Azariah is a Principal Architect with Microsoft and co-creator of the Q# programming language for quantum computing. He was on the QCoDes team and one of the designers of the Azure Quantum offering. He is active in the Azure and F# communities and presents regularly on the topics of distributed and cloud computing; quantum computing fundamentals; and functional programming (particularly in F#) at various international developer conferences.
Further resources on quantum computing
- Getting Started with Quantum Computing (No PHD Needed!) (video)
- Quantum Computing: Getting Started with Q# (course)
- Quantum Computing: Executive Briefing (briefing)
20 days of lethal heat per year, collapsed ecosystems, and more than 1 billion people displaced. Those are all probable scenarios that could devastate societies by 2050 if swift and dramatic action isn't taken to curb climate change, according to Think Tank Report by Melbourne based breakthrough National Center for Climate Restoration. Now it's obvious we need to do something, but well, what? On this episode, we might have part of that answer exploring the world of quantum computing.
My name is Lars Klint. This is TECHnically Possible, a show that investigates future technologies impact on us humans and our connections in the world. Whether that is good, bad, or just plain weird.
If you're new to the podcast, let me give you a quick rundown. In each episode, we discuss an emerging technology and invite an industry expert to help us break down where we are currently at, and more importantly, where this tech could possibly, or impossibly take us. All the while keeping it grounded in what exactly that means for us humans, and maybe even some fun along the way.
Now my guest on this episode is John Azariah. He's a principal architect with Microsoft co-creator of the Q Sharp programming Language for quantum computing, and he was on the QCoDe team and one of the designers of the Azure Quantum offering. He's active in the Azure and F# communities. He presents regularly on the topics of distributed and cloud computing, quantum computing fundamentals, and functional programming, well, particularly in F#, at various international developer conferences. His current interests include well quantum computing, programming language theory, domain-specific languages and type systems. What a nerd. John is also known as the functional wizard, and rumor has it, he can make your dog disappear.
So welcome John to the show.
Hey, nice to be here.
Wow. You have an interest in type systems. Can you explain that to me so I don't fall asleep?
Yeah, absolutely. So it turns out that one of the fallacies, they, they kind of teach you when you learn programming is that everything's about how to move bits and bites around.
One way of actually thinking about programming is actually as an expression of higher mathematics. And it turns out that there's some very, very cool correlations between what we know as type theory and some of the advanced mathematical concepts like category theory and so on. And it turns out that when you use mathematical underpinnings to describe how you do your computation, you can build up a much more rigorous programming model that allows you to sort of bake correctness and proofs and stuff like that into the system. Yeah. So it's a very, it's a, it's a different way of looking at what the foundations of programming are actually.
Oh, for sure. I still like to move bits and bites. I can still do that, right? I'm allowed?
Oh, absolutely. But one of the interesting things we are gonna discuss today where, especially when we talk about quantum computing, is yet another level of abstraction where, you know, we talked about zeros and ones and how all of classical computing is actually sort of founded on just zeros ones and boolean logic.
Well, it actually turns out that we were told a white lie and that really computing is actually a deeply quantum physical process where the abstraction that is correctly used to describe the thing is actually linear algebra. So we'll forgo the math today, but it's an interesting way of looking at it to realize it's a, it's an interesting way of actually realizing that what underpins a real computation, even quantum computation is actually linear algebra. Linear algebra can describe quantum processes and classical processes, and can do so with a, with a great deal of elegance.
That is interesting, and we'll get into why that is interesting why that can describe both. But now, before we get to that meat of this episode, I just wanna challenge your moralities for a bit. Now, don't worry, it's just a bit of fun. There's no wrong answers, and the points actually don't matter.
So this is to get you warmed up, get your brain waves on track and warm up your unilateral face detractors in a segment we would like to call Moral Technicality. All right. So John, using quantum computing, you will be able to advance cancer research dramatically, and the health impact, of course, will be immense.
A cure for cancer has been found using quantum computing, and it's up to you to make it public. However, of course there's a catch. If you release the cure, you will also compromise all security algorithms and implementations currently in existence. So what do you do?
Wow, that's an interesting question. Um, they're different ways to answer this. I'm actually going to cheat a bit. I'm going to give you one answer now. But I'm going to come, I'm going to ask you to come back to this after we discuss the state of quantum computing, and then we'll actually delve into the real meaning of, well, how to answer that question.
But I guess my, my initial knee jerk reaction is, you know, cancer has been such a profoundly debilitating influence on human society that if we had the opportunity to get rid of it, even at the cost of some of the financial and other economic factors that are supported by by the encryption, I would say that the good far outweighs the bad in this case, and we should actually do what is right for the good of mankind and get rid of cancer. That's, that's the gut reaction right now. But let's, let's explore this conversation again in about 10 minutes when we talk about the state of quantum computing as it is.
But I'll take that answer. I mean I'd like to get rid of cancer. That sounds great. Um, So, alright, so let's start the conversation. Yeah. Let's go over what quantum computing offers today and what the current status is. All right. So to explore sort of the current status of what quantum computing looks like today, I thought we'll start with a bit of a, a fun fact. Maybe it's not, Yeah. Let's call it a fun fact. Can I get you to explain quantum entanglement, because that's probably the weirdest concept I know of in, well within quantum.
I think that's a great question. In fact, this question is actually one of the more difficult questions even for the superstar physicists like Einstein, who, who was starting to have trouble with the concept of entanglement because entanglement is actually the most fundamental difference between quantum physics and classical physics. Now, classical physics as we know it you know, we can always describe, say for example if I throw a ball in the air, I can describe the entire state of the system by writing down an equation about, you know, kinetic energy and potential energy, and so on and so forth.
And that equation will describe the system at all points. Okay, and it'll describe that ball completely. If I throw two balls in the air, I can describe the system with two equations, and each of the equations will describe each ball that they are written for perfectly. All right. Now we are used to this and we can do things like measure the velocity of a ball, for example.
Anyone who's watched a cricket match sees Hawkeye and knows how the ball is spinning, how fast it's going, where it pitches on the pitch, and so on and so forth. That comes from the equations that describe its motion, and that is the classical way of looking at it. However, when you talk about quantum systems, something really, really interesting happens. And that is when you have two things, two entities that interfere with each other, they interact with each other in some way, initially you can write down in individual equations to describe the two systems, but when they interfere together in specific ways, you can't do that anymore.
You only have one equation that describes the whole system with both pieces as part of it. And that's kind of a weird thing. It's like mayonnaise. You can have egg and you can have lemons and you know, you can describe the egg and the lemons up until the point where you actually make mayonnaise with it, right?
But then once you make the mayonnaise, you can't actually talk about the egg part of the mayonnaise or the lemon part of the mayonnaise. They're just mayonnaise. That's what you have, right? What's really cool though is that the properties of this system are not attached to an individual component of the system.
So when you talk about things like quantum spin is one of those general properties, but any, any property really is not associated with any of the individual particles anymore. The spin of the system becomes something that is indivisible, you can't break it apart into two individual pieces to describe the spin comes from this piece and this piece. It's actually just the one spin of the mixed system, and that mixed system is called entanglement. And if you try to actually observe or describe one part of the system, after you have an entangled system, you'll end up actually affecting every other part of the entangle system.
So that's where the whole spooky action at a distance paradox kind of comes in, where it appears that you are measuring out the spin of one of the two electrons and immediately affecting what the other spin looks like. But that only becomes a paradox if you think of them as two individual pieces like we would in classical mechanics. But you can't think of it that way anymore in quantum mechanics. The measured spins of the system are property of the group of entangled items, not of the individual items themselves.
And there is no, there's no classical analog for it, so it's very difficult to get an intuition. Like you can get a naive intuitions like mayonnaise, right?
But, but really there's no, there's no classical equivalent that you can appeal to and say, well, this is like that. And that is actually the biggest leap in terms of getting a handle on how these quantum systems work,
Yeah, yeah. Yeah.
and it's not unreasonable to have even you know, scientists with, with a great deal of experience in other things, face some initial trouble to get that intuition.
Yeah, it's, I've never heard entanglement explained as mayonnaise. That's kind of cool. But as you say, it is a bit naive. So if I understand it right, I can have two, let's say electrons and they can be anywhere in the universe in relation to each other for argument's sake, and if one says spins around its axis, the other one will do something similar or in conjunction or the opposite, like they're connected.
Is that right?
They're connected, but they don't communicate. They're one system. And that actually changes the way in which we even look at, you know, how the universe is put together. What is space, what is time? And they're more profoundly fundamental questions that come in. But there's one small caveat to your example, which I should point out.
Usually the entangled system fundamentally means that these two electrons, they have to actually interfere with each other somehow. They have to interact with each other somehow and traditionally, even before you start separating the two electrons out, you actually create them in the same place so that they come out entangled, they come out like twins.
Then you have the entanglement, they, they're entangled, then you pull them apart, and then when you measure the system so that you collapse one of the wave forms, it automatically collapses the other wave form as well.
Yeah. It's just, it's mind blowing that it's like they're not connected like as, as a human, you go, well, they don't touch each other and there's no way radio waves and there's not like, how does that work? So anyway.
Yeah. And they don't even communicate.
No, that's right.
We have proof. In fact, this experiment has been done many, many, many times. We know that there is no communication between these two entangled pieces. We can prove that and we have seen it.
But when you affect one part of the system, the other part of the system is automatically affected as well.
It messes with your head. So, so now we sort of, let's say, defined quantum computing. Where are we at today? Like, does understanding entanglement actually help us in building quantum computers for example? Have we got quantum computers?
Yes and no. It's a classical quantum joke, right? It's both yes and no at the same time. Right? So we have systems that exhibit quantum properties, which we have been able to exploit for the purpose of computing. Now, if you talk to a standard physicist, he will tell you that a transistor that you use on any of the normal chips for classical computing fundamentally work at a quantum level.
They actually are a quantum device. However, we are not using the quantum-ness of that device to do any computation with. We have actually moved up to one level of abstraction above that. So the current state of the art is that there are devices that exhibit quantum properties, which can be exploited for the purposes of computation, and we have actually performed non-trivial computations on them.
That does not mean these computations are useful, but they're complex. In fact there is literature out there that shows that we can do computation using these quantum devices that in a, in a matter of hours, that would've normally taken a supercomputer weeks of time to do.
And so in some sense, we have a quantum device.
However, the nature of the problems that you solved with quantum computing is so large that the device that you have is still not yet big enough, strong enough, long-lived enough in order to actually solve any real world problems.
So I lie a little bit, okay? There is one really interesting real world problem which we can solve with quantum devices today. And that is the the problem of getting a truly random sequence of bits. So it turns out that one of the things that you can do with a single qubit, a single unit of quantum computing is called qubit.
Even if you have just one qubit that lasts for a very short period of time, you can harness it to generate a random bit between zero and one. And you can do that repeatedly so that you can get random bit sequences which are not biased. So when you run a standard computing library in Python, for example, and ask for random number, what's actually happening is it's generating a pseudo-random sequence, a sequence that has a period that is very, very long. So it, it looks like it's random, but it's actually not. You can recreate the same sequence if you start with the same seed and you work through the same operations, you'll get the same sequence back. It's not truly random in that sense.
However, with a quantum device, you can get from a fundamentally natural process purely a random sequence of bits, and that is actually quite useful.
So there are actually devices that you can buy today that literally look like a UBI key that work entirely off of quantum processes. And when you ask it for a random number, it gives you a random number.
Okay. Now let's just for those that aren't in the quantum physics space, what, what is, what is quantum computing made out of? So we sort of explored quantum entanglement, which is one of those, you know, concepts really, but an actual computer will have you mentioned qubits. So how do the qubits relate to the computation of a quantum computer?
The closest analog you could think of to a qubit is an arithmetic logic unit in a classical machine. It's not just the bit in terms of storage it's also the part that does the operations on the bit. So an ALU, for example, a 2-bit ALU will know how to add two numbers together - 'AND' and 'OR' 2 bits together, right? And so that arithmetic logic unit is kind of like a piece that both has a state based on what value you put in there, and the ability to operate on that state. And a qubit is exactly like that, except that you can start it say for example, in a zero state, apply certain quantum operations on it and encode quantum information, which basically acts as both the repository and the thing that operates on the value that's held inside. The clear difference between a quantum bit and a standard bit is that you can always probe a bit and say, 'Hey, are you a zero or a one?' Whereas with a quantum bit, you can't actually probe it to say, 'What state are you in?'
Because the moment you measure that state, it collapses itself to a zero or a one.
That's the interesting part as a non quantum person, is that you have this, of course, I'm gonna try and relate it to something I know. So that's the classical computing model of bits and bites and storage, et cetera. Right. And this idea of I can have eight bits in a bite in a classical computer, and I know what they are, and if I look at 'em tomorrow, they're gonna be the same cuz I know what they are.
Whereas if you do it in a quantum computer with eight qubits, as soon as you, measure it or you know, view it or read it, observe it, they collapse into a state and they're gone.
It's a very difficult concept.
Well, think of a beach ball. Let's just imagine that I'm holding up a beach ball and I have a little Sharpie, right? And I put a dot on the beach ball and I hold the dot in such a way that the dot appears like the north pole of this beach ball.
So now with a finite number of rotations, I can take that dot to any place on the surface.
I can rotate it 90 degrees. That way the dot will come onto the equator. Or I can rotate it 180 degrees. It'll come down to the South pole. Or I can rotate it 17 degrees one way and then spin it around a little bit and the dot shows up somewhere else. So if you think of the dot as being the value of the qubit in some sense, the dot could be actually one of an infinite number of points.
It could be one of an infinite number of values as opposed to a bit, which is either zero or a one.
The problem is nature doesn't let you look over her shoulder and say, 'Hey, tell me exactly where the dot is', because the moment you ask for that, following a set of probabilistic rules, it spins the globe back to either so that the dot is at the North Pole or at a South Pole. And so one way of actually representing all of these rotations and so on and so forth, is by actually using linear algebra. Right. But if you now think about classical computing, classical computing basically is the same ball except that you can only rotate it from North Pole to South Pole and South Pole to North pole.
That's all you can do.
Yeah, and it never resets.
Well, it doesn't reset because it's already at the north or the south, and probabilistically, if it's in the North Pole, it'll stay at the North Pole. Even in the quantum sense of things, right? But now you only have two locations where you can have these dots.
And you built an entire computation system, the classical computing model, based on those two things. I mean, everything that we know of as a computer right now, including the device that you're recording this podcast on, works with the globe just being North Pole to South Pole and one rotation only.
Right? Imagine how complex or how rich the computations you can do if you could actually rotate the ball more finely so that it could take up any one of an infinite number of, of precision positions. Right? And that's what quantum computing actually lets you do. So it allows you to encode one of a myriad number of values into a single qubit, right?
With, with the proviso that if you dare to ask, where is the dot? It will always be 'I'm at the North Pole, or I'm at the South Pole' and nowhere else.
I like the way you said that. You're dare to ask
Yes. So as long as you don't dare to ask, as long as you don't interfere with a qubit, you can actually encode a very rich set of values in there, and you can do things with two beach balls that you can't do classically, like entangle them and so on and so forth, and do all of these other things, and you can build up a much richer computational model. And I think that's really the only intuition that you should walk away from is that, you know, with just the north and south pole and individual beach balls, we are able to create 64-bit math and do all of the classical computing that we are doing right now. Imagine the richness of the computation that you would be able to do if you didn't have to limit yourself to just the north and south pole and you could entangle all the bits together to do other things. And that's really the power that you harness in quantum computing.
You said at the start of the show as well, that, well, the start of the segment even that we have actual quantum computers now that does create some computations very quickly. That would've taken weeks with classical computers. And that's sort of one of the things that I've, I guess latched onto is that we might have a way of computing extremely let's say complex scenarios that would take many, many years, or it might even be impossible with classic computing. And we can do it more or less instantly with quantum because of what you said, the beach ball. You can place it at all positions at the same time.
And that is, I think that's probably the promise, isn't it, of quantum? We're not quite there yet, or are we, is there anything sort of happening now that might lead us to that?
Let's actually step back and take a look at nature first of all, right? Like, I think we love looking at the beach. We go and see the forest, we see the trees, we see leaves, and we are struck by wondered how beautiful the thing is and how much complexity is there already. But in reality, what's actually happening inside nature is quantum mechanics.
If you look inside the inside of a leaf and you look inside the inside of, say, a chloroplast, which is the part of the cell in the leaf that allows you to trigger photosynthesis, and then you look at chlorophyll, which is the molecule inside the chloroplast, and you wonder how that works.
Well, it turns out nature is doing incredible maths. That's all it's doing. The solution to the math equation is the chlorophyll molecule. And in order for us to try to even model that math problem, it turns out that if you just limit yourselves to zeros and ones, there are not enough atoms in the universe for us to be able to describe the problem.
That's a lot.
Right? But nature doesn't seem to mind. Like if you just walk out and look at my garden, there must be a million leaves out there, right? Each of those leaves will have trillions of cells, and each of those cells will have honks and honks of chlorophyll in them, and nature is solving that math problem without even thinking.
Right? And the way it's solving that math problem is by using quantum mechanics. So the application that we are looking for is to somehow use the quantum processes that are already there in nature, but harness them to solve different problems. And that's really what, what it is.
All right. What I get out of it now is it's complicated and we knew that, right? Especially when you're used to classical computing with bits and bites, but where's sort of the current status today? What can I, as a consumer, use quantum computing for, are there things that I should care about that it's solving?
That's a fantastically good question, and as you'll appreciate right, the answer to this changes roughly every day.
But also it hasn't changed significantly in the last 20 years. So, I mean it's a superposition of, it's changing a lot and it's not really changing much. Same story, right?
Tell me when you're sick and tired of these quantum jokes, right? But so, we can basically lump quantum class problems into three sort of major groups. Okay. The simple solution, which already exists to some degree and which is commercially kind of available, is the random number sequence generator, which turns out to be profoundly useful, especially when you're doing things like machine learning modeling and so on.
The quality of the random number sequence that you use matters a great deal, in terms of the quality of the solution that you get. So having truly random sequences is important and we can get that now. Okay. To some degree we can get that. That said let's talk about the other two types of problems where I kind of indicated earlier that you know, nature is doing quantum mechanics at the molecular level and the fact that it seems to be able to have no problem synthesizing complex molecules and getting them to behave in a particular way while we have an extraordinary difficult problem trying to understand mathematically why a molecule behaves like that, effectively shows you the potential of using quantum computing. Right? Well, one area that we might actually want quantum computers for is to actually simulate natural systems, complex molecules in nature, and be able to get a better understanding of why they behave the way they do.
So, for example the molecule that's like pumping around in our veins, hemoglobin how it interacts with oxygen, how it actually latches onto oxygen, so on and so forth,
We can't do that today.
We cannot do that today. It turns out that anytime you have a metal in the molecule, specifically a transition metal, but roughly speaking, anytime you talk about iron or magnesium or any of these metals inside a molecule, chlorophyll is another one of those and so on, right?
It makes it extremely difficult to do the maths. Maths becomes completely intractable. Okay.
So we can't understand how chlorophyll works. We can't understand how hemoglobin works. And,it sounds a bit fatalistic, but really we can't, because the complexity of the number of electrons in this molecule fundamentally make it intractable for classical computing.
So when I say can't, it's not because we haven't tried hard enough. It's actually because we actually cannot, and we can prove it. Right. So there are other interesting molecules. Like for example, there's one that grows in the root of a bean plant, which knows how to fix atmospheric nitrogen and fertilize the soil.
And it turns out that that has the potential, if we understood how that works and we don't, and we can't without quantum mechanics, it turns out that that would have a, you know, predictably profound impact on things like global hunger, right? Because we spend, as a human race, we spend about 4% of the energy that we produce in our oil wells and so on to make ammonia, which then we use to make fertilizer, which we then use for industrialized farming. And the fact that it's an extraordinarily energy heavy process immediately that leads to sociopolitical impacts, such as only the countries that actually have the energy can make the fertilizer, which then means that they're the only ones who can actually use the fertilizer to grow enough food.
And so you have a growing imbalance socioeconomically across the world where the availability of fertilizer is the difference between having food and not, right. And in some sense, if you are able to solve that problem, because we understand how nitrogenous works and it doesn't take much energy to do what it needs to do, but it we, don't know how to mathematically model the thing.
If we can get a better understanding of how that molecule works, then potentially there is a trillion dollar impact to the human race, right?
We are talking a little bit about the future now, which we we're, you know, kind of getting to. But it sounds like it's currently as me being, you know, say I'm gonna walk down to the shops and I'm gonna figure out how to do my garden or build my house or build a farm.
There's nothing right now that impacts how I do that in quantum computing.
Is that fair?
No. That's totally fair?
All right. So, what can the future of quantum computing hold though? Like, what is technically possible?
So we've got a bunch of information so far about, you know, what, how quantum computing works and sort of the impact it can have. But today, currently there isn't much that we can do that impacts the human world.
However, one of the things that I know, cuz I spoke to you, John, about this before we actually recorded the show, was that there's a small topic called climate change, which quantum computing actually can, or seems to be likely to have a great impact on, in us solving it or at least mitigating it. So I'd love to talk more about climate change as a topic of future of quantum computing, if that's all right with you.
Absolutely. So this again is an application of the chemical simulation piece, right? I've been banding about relatively complex molecules that we kind of are very familiar with, right? I've mentioned hemoglobin in the past. I've talked about hydrogenous, which is that bean thing, and I've talked about chlorophyll to some degree, right?
Chlorophyll is one of those things that all the leaves have that actually allows you to capture carbon. Now, if you think about carbon capture you know the best way to deal with carbon capture at the moment is to plant more trees. And the reason why that happens is because leaves know how to soak up carbon dioxide from the atmosphere and turn it into food right? But we don't know how that works. We can't know how that works because chlorophyl is a super complex molecule and we don't have the computational bandwidth to be able to figure that out. But if we were able to use quantum devices, for example, to figure out things like how to understand how chlorophyll works, then potentially there's a profound impact that we can gain out of it. And of course, chlorophyl isn't the only approach, right? Like there's different nano structures, there are some really exciting properties of what happens when you have very fine forms that actually are able to literally trap physically carbonide molecules and and actually remove them from the equation, right?
And you can model some of those exotic materials and exotic physical structures with quantum mechanics. And instead of doing the traditional, 'Hey, I poured these two things together and it gave me this thing, and it seems to have this property', which seems to be the way in which we've kind of fumbled around most of our chemistry from the dawn of time.
Right? It's really a matter of experimental sort of discovery. Whereas quantum chemistry is quite different. It basically says, 'Hey if I solve these equations in this particular way, I can actually invent things that will have certain properties that don't exist today.'
Or I can learn from things that exist and modify them so that they work even better. And that's kind of the promise that we have as far as some of the approaches that you can use quantum computing for in terms of directly affecting the science of climate change. Directly affecting the science of carbon capture.
So what kind of quantum computer do we need to do this? Like we, cuz we were talking about before even using two qubits, you can do incredible things.
But how, like what size are we talking? Cause you were then talking about 10,000 doesn't seem unreasonable theoretically, but can we even build a 10,000 qubit quantum computer?
We'd love to. Right. And we'll meet our old friend entanglement again because entanglement plays a very key role in some interesting properties I'll try to address in a bit. You asked that initial question about what quantum computers look like, what are the building blocks of a quantum device? But as it turns out the building blocks of a quantum device actually, something that exhibits anything. In fact, that exhibits the property where it can stay stable in two states, right, at two energy levels and be able to perform superposition and entanglement.
So the things that we know of that can do these kinds of things turn out to be very small, right. So things like electrons and photons. These are entities that exhibit quantum mechanical behavior and they're able to encode information.
But if you remember, electrons are really tiny, photons are even tinier, right? And so they're very, very prone to disturbance from the environment. And so when you build a system, say, built around electrons, you have to go through great lengths to make sure that the electrons are kept safely isolated from you know, interference from the environment, and yet you're able to sort of like predictably put them into you know, do the operations of the rotations that I mentioned earlier, right?
Like, if you want to do that on an electron, you need to have a way of doing that. Similarly with photons, you can actually create photons that are in multiple states and you can perform entanglement on them and do the computation on them. So depending on the kind of physical device that you use, you have different physical manifestations of qubits that have different physical properties in terms of how well, they compute or how fast they compute and how reliable they are. Now, it turns out that the processes that you actually require in order for there to be, you know, say a two level system, so it's kind of like walking over to St. Kilda beach with a piece of stick and standing where the waves come in and trying to do maths on the beach, right? So just as your starting write stuff down, the water comes in and starts like wiping your values out and how much information you preserve between waves is a function of how well you can actually error correct for what happens when the wave goes away, and how deeply you can embed the information into the sand so that you can survive one or two or three or 10 waves, right?
Sorry, is this why quantum computers have to run at like, what is it 0.03 Kelvin? Like unbelievably cold?
Yes. And, well not all quantum computers, but the ones that involve using electrons, as it turns out. One way of actually making sure that they're safe and isolated from losing their state and reducing the impact of natural decoherence is the term, like natural loss of information, right? Is to basically chill the thing down so it doesn't move very much.
And as we know, as you get closer to absolute zero things stop moving. Like atoms stop moving, it's easier to hold onto them and it's easier to do certain things with them. Right. So it turns out that if you do photonics you can actually do them at room temperature, but they have other issues. You're dealing with photons and those are not affected by temperature, but they are affected by other things.
And so you can have room temperatures quantum computers, but they will basically be different from the, from the el ectron-based ones.
But how far are we from that?
Well we do. We have, okay, and this is what I was trying to say. So we have physical qubits of all kinds, like we have six or seven technologies where you can actually exhibit the quantum phenomena of superposition, for example, and entanglement. And you can do all of that. But the decoherence factor is still very, very, very, very high.
As in like, the qubit will only hold information for a millionth of a second, right. And you gotta, and you gotta basically do all of your operations before that if you want to use it. And so we're in this phase of quantum computing, where the hardware is extremely noisy.
And we can only create like dozens of qubits because in order to keep something chilled at like 15 millikelvin, you can't have a wafer that's the size of my desk.
You can only have a wafer that's like you know, the size of a hockey puck. And you put that inside this fridge and bring it down. And depending on the kind of qubit that you grow on it, you can have, you know, a few dozen at this point. The state of the art, a few dozen qubits. And as it turns out, you can entangle multiple qubits together to create a logical qubit that will hold its information for much longer.
So this is like error-corrected RAM.
You can create error-corrected qubits and hardware error-corrected qubits. Actually they're very, you know, you need about 10,000 qubits to just create one logical qubit. So at the moment, if you wanna think about how many logical qubits do we have, we, none of us has any, right?
But if you want to think about noisy physical state qubits, we have a few dozen.
Okay. And would a few dozen be enough to help solve climate change or say, model the Earth's climate, for instance? Is that enough? Are we still far, far, away from that?
We're enormously far away from that.
So you'll need on the order of 10,000 logical qubits, which means now 10 to the 10 physical qubits, all providing the sufficient amount of entanglement and the ability for you to be able to hold the information and we are no way close to that.
That's right. That doesn't sound like my lifetime.
So that's an interesting thing as well. So there are different people approaching this problem in different ways. Microsoft, for example, just put out a paper in July where they effectively created in very loose terms, a super massive electron.
Which fundamentally means they created a mechanism by which the electron is far less susceptible to noise, right.
But it's still able to perform the quantum operations that you require and therefore you have a hardware corrected qubit, which you synthesize with the hardware connection built in, which you can then maybe put a million on in a wafer.
And now you're in a situation where you can actually talk about, you know, a hardware-corrected qubits, but it took them a good 20 years to get one single observation of the supermassive electron. Right. And now in order for them to convert that into a qubit is another probably, I have no idea how long, but I expect that it's not in my lifetime.
You're a lot younger than I am, but uh, so maybe in your lifetime, but certainly not in mine, is really how I would like to put it.
Okay, so it's sort of within you know, modern times. I think, it's not too sci-fi is what I'm getting at. However, you know, something like climate change obviously has a bit of a deadline. Like we need some sort of solution. So I'm just wondering, maybe we can use parts of what we get with quantum computing, cuz of course we are gonna get better and better and better at it.
And it might just be something that, that will help us. Another thing that I have sort of read a little bit about and come up in my research for this show was that we can potentially create better batteries with Quantum. Is that something you've heard about, cuz that would be part of, you know, moving to electrics as well.
Yes, absolutely. So again, a whole host of, material science becomes possible with quantum computing. This is basically the impact of using quantum devices to model quantum phenomena that naturally happen as quantum phenomena. So things like room temperature superconductors, which are kind of useful because we lose a lot of energy just moving power from point A to point B, right.
And so having superconductors that actually don't charge you resistive power loss as you move power from point A to point B have an impact. Battery life is another one. Various kinds of chemical capture gels are another point. The whole chemistry of ceramics is a very beautiful and profound area of science where you can get superconducting magnets outta ceramics and so on and so forth. All of them work that way because they have really exotic metals in them that we can't model mathematically. So anytime. Yeah, anytime you have these metals come into the equation you naturally start leaning towards expecting that a quantum device will eventually be needed to solve that problem.
Of course, as you pointed out it may not have a direct impact because it may just come too late. Too little too late. Who knows? Maybe what needs to happen is uh, sociopolitical change in a classical sense to stave off the impact until you have the computational advantages from quantum computing in order for them to play a role in this game.
Yep. Okay. So if I'm gonna summarize what we just sort of said for the future, the good is, is it's got massive potential, right? There's so many things that we can solve with this that it just isn't possible with classical computing. But the downside of it is that it's horribly complex and we are nowhere near anything that can do that.
So it'll take a very long time before it becomes mainstream, I think. Is that fair?
That's absolutely fair. I mean, you can add the caveat that we can solve interesting academic problems with the hardware that we have.But in order for us to solve real world problems, we are some distance away from actually demonstrating any sort of quantum advantage.
So if we were to now circle back cuz we did promise we were gonna do that to the technical dilemma, how would you now answer that based on the conversation we've had and what we now know, sort of more depth about quantum computing?
So here's actually the reality of the situation, right? So we will need tens of thousands of qubits to solve both problems, either the problem of factoring large numbers.
And to talk about complex molecules that potentially may have an impact on cancer, for example.
You'll also need roughly 10,000 qubits. So let's say that we've fast forward in life to the point where we have 10,000 qubits and people starting to find solutions for them, and you've got, you know, Mr. Red Hat doing the cancer research stuff and then Mr. Black Hat walking around trying to break encryption for the humanity, right?
The reality is there's Mr. White Hat already. Which is post-quantum crypto is already a thing. Because the mathematics that we currently use for doing encryption is just based on factorization, it's clearly vulnerable in the future anyway to quantum computing. However, there are other encryption schemes which turn out to actually be quantum resistant.
They're actually not going to be crackable, even with the quantum device. So when I initially said, 'Hey, let's just go all, all out and give us, get the cancer solution', I would still stick with that because now I know that even if you did break the existing factorization-based encryption, you actually won't lose much because you can already go towards other schemes that don't require factorization to act as the linchpin for the encryption algorithm.
And so you have post-quantum crypto, it's already a thing, and you can already start future-proofing your encryption systems with post quantum crypto algorithms. And so in some sense it's, it's not really a dilemma. This is actually how it's going to play out.
I like it. Well that's good. And you know, thank God we getting rid of cancer. Hooray! So, exactly. Now is there anything at the end of the episode here that you want to add, John, anything we missed that you think we need to know about the future of quantum computing?
Yes. I think the biggest future that we have actually not talked about is quantum algorithms. Now we have actually made very, very little progress as a computing community. We've actually got a handful of algorithms at this point that we know that take advantage of quantum phenomena, quantum computing principles in order to get some benefits.
The vast majority of the new algorithms, I am willing to be positive and think that they exist, but they have not been discovered yet. And the person who's gonna discover that is probably sitting in kindergarten somewhere today, and that's an extraordinarily exciting thought because it means that humanity as a whole is actually going to get better as long as we expose this paradigm of computing to the next generation and the generation that follows. And hopefully, while we have a single algorithm today to do just factoring of a large number, who knows what algorithms will come out with some smart whizz kid sitting somewhere. And who knows what profound implication that will have on humanity as a whole.
So there's a message of hope in here.
Oh, for sure. No, that's why we do the show. It's like we, and I agree. I agree. I think quantum, because we know so little still is just extremely exciting field to explore much further. But yeah, thanks John for your time. Thanks for being on the show. It was a pleasure
Oh, thank you for giving me the opportunity. Yeah. It's been a great pleasure. See you Lars.
Absolutely. So that's all for this time.
If you like this episode, consider subscribing to the show. We are available wherever you find good podcasts. Also give us a review, which will help others find the show as well. So tune in again next time for a conversation about what is technically possible.
5 keys to successful organizational design
How do you create an organization that is nimble, flexible and takes a fresh view of team structure? These are the keys to creating and maintaining a successful business that will last the test of time.Read more
Why your best tech talent quits
Your best developers and IT pros receive recruiting offers in their InMail and inboxes daily. Because the competition for the top tech talent is so fierce, how do you keep your best employees in house?Read more
Technology in 2025: Prepare your workforce
The key to surviving this new industrial revolution is leading it. That requires two key elements of agile businesses: awareness of disruptive technology and a plan to develop talent that can make the most of it.Read more