There is a shift coming in the very nature of computing which is being led by the likes of quantum physicist Michelle Simmons. Michelle wants you to put the binary world of ones and zeros on the shelf for a moment, as she introduces you to the idea of computing with atoms.
Every year computers get smaller and smaller, and faster and faster. Have you ever wondered when is it ever going to end? Well, one person that’s been looking at the miniturisation of computers over the last several decades has been Gordon Moore, and he was the co-founder of Intel back in the 1960s. And he noticed that the number of components on a silicon chip doubled roughly every 18 months to two years. Now, for this to happen, it means that the smallest feature size on a silicon chip has to decrease at the same rate. And he came up with something called Moore’s Law, and here it is represented on the screen. Now, this law has been going now for approximately four to five decades, and what started out as an observation by Moore has now become a law after his name, Moore’s Law. This actually continued in time.
The interesting thing is that the industry has now set this as their road map of how to make computers smaller and smaller, and faster and faster. So you have multi-trillion dollar industries, the semiconductor industries, pouring money in every year to try and beat that law. Until now, it’s become a self-fulfilling prophecy. See, if we have a look at where we are at the moment, here is a cross-sectional Scanning Electron Microscope image of a single transistor. Now, the smallest feature size in this transistor is the distance here between the source and the drain. It’s about 30 nanometres. It’s 5,000 times smaller than the width of a human hair. What’s amazing about that is if you look around you now, we all carry around our personal electronics. And within one silicon chip you have over three billion of these transistors. And they all have to work reliably so that your computer, your mobile phone, whatever you’ve got with you, actually works. That’s quite amazing. Just think about that now. Everybody in this audience has got billions of transistors. There are trillions of transistors in this room.
Well, one of the nice things about Moore’s Law is you can actually predict, with time, what’s going to happen. And eventually you’ll see out here, in roughly 2020, less than 10 years away from where we are now, the size of a transistor will get down to the size where it’s a single atom. That’s the smallest component of nature. It’s very difficult to imagine that you could make a transistor any smaller than that. But this is the world of digital information. So let’s just understand how that transistor works.
Here, we have a silicon substrate. That’s what the transistors are made of. And above that we have an insulating oxide and then a metal gate. And what we do is we apply a positive voltage to this top gate here, and that sucks up, it attracts all the electrons that are in the silicon up towards this gate but they can’t get there due to this insulating oxide. So they form this two-dimensional sheet which forms a conducting channel between source and drain, and that turns the transistor on. That is our ‘1’ of digital information. If we now put a negative voltage on this gate, we repel all the electrons down here and we push them away from that channel. So there is no conducting sheet and, as a consequence, you get the ‘0’ of digital information.
So that’s the ones and zeros as we go down. For everything that works around us now, everything is coded in either a ‘1’ or a ‘0’. And what happens as we go smaller and smaller in size is we actually cross over from what we call the ‘Classical Age’ to the ‘Quantum Age’. And there things really start to change. In the classical world we understand how things work. So if I had a tennis ball now and I was to throw it at a wall, it would hit the wall and bounce back and I’d understand and I’d see it and be able to write equations of motions to describe that. But as I miniaturise things down and imagine that tennis ball being the electron in my transistor, if I made it very, very small, and I threw that electron at the wall, instead of it bouncing back it actually behaves more like a wave than a particle, and it can tunnel through the wall and it can come out the other side. Now that’s something that’s quite scary. As we make our devices smaller and smaller, the wonderful world of quantum mechanics comes in. Electrons behave like waves and they no longer go in the computer where we want them to go.
So a lot of people have predicted that this would herald the end of Moore’s Law. But in reality, it’s the start of something new. We’re now transitioning to quantum mechanics. And if we control quantum physics, we could actually build computers in the quantum regime that are predicted to have exponential speed-up over classical computers.
So one of the questions that a lot of people ask me is: aren’t computers fast enough already? Can’t they do all the things that we need them to do? Well obviously everyone wants things to be faster all the time. But there are some problems out there that just cannot be solved efficiently using a classical computer. And one of those is called the travelling salesman problem. So here we have a salesman, we want him to travel to lots of different cities, and we want to work out where the shortest possible route is. That sounds like an easy problem. But it’s actually one of those intractable, exponentially hard problems. So here we have on the screen the number of possible routes that he can take as a function of the number of cities. It’s something that grows very, very quickly. So by the time you have 14 different cities, there are now already 1011 possible routes that he can take. So if I take a classical computer, it works in the gigahertz regimes, 109 operations per second. And it can work out the shortest possible route in about 100 seconds. Well that’s no big deal. But now what happens when I go to 22 cities? There are now 1019 possible routes that salesman can take. And with that same classical computer, it would take 1,600 years. This is amazing. And if you look, by 28 cities, it’s longer than the lifetime of the universe to work out what the shortest possible route is. I heard this problem many years ago and I just couldn’t quite believe it. But this is a real problem, it exists out there.
So how can we make a computer that can somehow solve those kind of problems? We have to look at how a classical computer works. A classical computer is very fast. But it searches through all the possibilities one after the other, rather like a recipe. So if I was to write down a telephone number on a piece of paper and I’d forgotten whose telephone number it is, I’d get my classical computer to start looking through all the A’s, then all the B’s then all the C’s. And eventually it would find whose number it is and tell me. If I wanted to go faster, I could put two computers onto the problem. Get one searching between A to L, the other between M to Z, and it would go faster. To go faster, I’d have three computers. Well, that's the digital world. If you could make a quantum computer, the actual calculations are done in parallel. They’re all done simultaneously. Now, to try and understand this, I’m going to go back and describe what a classical computer looks like in my mind.
So I’m imagining I’m sitting at the centre of the Earth and I’m pointing towards the North Pole. We’ve already heard a talk about the North Pole this morning. That’s my ‘1’ of digital information. I could also be pointing at the South Pole. That’s the ‘0’ of digital information. But in the quantum world, I could be pointing to anywhere on the surface of the Earth. I could be pointing to London, or I can be pointing to Tokyo. And as a consequence, I’m in what’s called a superposition, partly up and partly down. And that’s an electron wave function. That’s the quantum world. I can be in both states at the same time. Now how does that help me in calculations? Well let’s look what happens as I increase the number of quantum bits or qubits. That’s what a transistor’s called in the quantum regime. So with just one qubit I’m in two possible states at the same time. If I now add another quantum bit, I can be in four possible states at the same time. If I add another quantum bit, I can be in eight possible states at the same time. So every time I add a quantum bit to a quantum computer, I double the computational power. So it’s been predicted that by having just a 30 qubit computer I’d be more powerful than the world’s most powerful supercomputer that exists. And if I could have 300 qubits, that would be more powerful than all computers in the world connected together. Now just stand back for a second. Three hundred quantum bits or qubits compared to three billion conventional transistors. That’s really the power of quantum computation.
So let’s consider some of the problems that quantum computers can solve for us. One of the first things that people realise is it could actually be useful for data encryption. Now, data encryption relies on working out what the prime factors of a large number are. Say we have two prime factors and, to remind you, a prime factor is a number that can only be divisible by itself or one. If I times these two numbers together, it’s a very easy problem for a computer. You can work out the answer on your calculator in seconds. But if I want to work out what the prime factors of a large number are, it’s actually a very difficult problem, rather like the one I’ve just showed you. This underlies … the difficulty of the problem underlies data encryption. So what we do is we encode our information in a very large number. And we give somebody one of the prime factors as a key, so they can decode the information on the other side. If they don’t have the key, though, they have to work out what the prime factors are, and that’s very difficult. So to give you an example, very recently they’ve broken the code in 2010 of RSA-768. That’s a 768-bit number. And it took them three years using the most powerful classical computers that existed. Now what they’re encoding is a 1,024-bit number. And using their same classical computers, it will take 3,000 years. If you had a quantum computer, it could solve it in minutes. So there’s an example of how quantum computers, when they’re realised, are going to change the way that we do computing.
Let’s look at some other examples. So I’ve talked about data security. Another thing that quantum computers are great at is searching databases, large amounts of information. Or for modelling systems where there’s lots of variables. So you can start to imagine climate modelling. Modelling of the economic system. We can start to imagine how chemicals form, how reactions form. How new things start to evolve. How the human body forms. Where quantum computation will take us is something that we just don’t know. But it has huge potential. As a consequence, there’s a massive international race to build a quantum computer. And I’m proud to say that here in Australia, we’ve decided to do this in silicon. Now the reason why we’ve chosen silicon is silicon is one of those great materials. The industry’s been using it for years. If we want to make a quantum computer in silicon, we have to engineer single atoms. But not just single atoms, but the individual electron on a single atom, in silicon, and encode our information in that quantum bit or qubit.
Now silicon’s great because the industry has been working on it for years. But it means we’re going to be pushing the end of Moore’s Law to make those single-atom transistors. Silicon’s also great because it’s a material that doesn’t interact with the electrons. It’s a nice, pure host material to protect that fragile quantum state. But to realise this quantum computer, we have to put these individual atoms in position within a silicon crystal, and then we have to align electrodes to that single atom, which means everything has to be incredibly small.
Well, how do we image or manipulate atoms? The only technology that exists out there is a scanning tunnelling microscope. This is something that has a very fine metal tip that it brings down to your atom’s surface. When you bring it down very, very close you apply a voltage and you get a current. And what you try and do is keep that current constant and move the tip over the atom. And as it moves, it deflects in height. And from that, you can actually image the atoms on a surface. And then you raster-scan it, rather like a television screen. And you can build up an image of what the atoms look like on the surface. Now, I’m blown away by this image. These are individual atoms here of silicon sitting on the silicon surface that transistors are made on. That’s really phenomenal.
Now you might imagine the machinery you use to actually image these atoms is very small, just a very small tip. But in reality, this is what it looks like. They’re very large systems, they take up about the size of a room. They’re basically huge chunks of stainless steel with a very high vacuum inside, rather like the vacuum you find in outer space. And within that vacuum you put your samples in and you control the atoms and you have mechanical control, pumping control and electronic control to be able to image those atoms on the surface. But you can also connect them here with crystal growth systems where you can actually put different atoms down on the surface. So you can actually start to create new materials that just don’t exist in nature. And to give you an idea of one of those, here’s the world’s smallest logo. These are xenon atoms on a copper surface. It was done in the 1990s by the IBM group by Don Eigler. And literally they used that tip to pick up individual atoms and put them down to form the world’s smallest logo.
Well, what we want to do now is to make devices in silicon using this technology. But it’s not as easy as just manipulating those atoms on the surface. There’s two key problems. The first one is that you can only see the device inside these systems, inside these microscopes. You can’t see them once you take them outside. So we’ve had to develop that technology. The second one is that you can’t just manipulate atoms in silicon very easily. They actually bond very strongly together. So as a consequence, we had to come up with a radical strategy to build these devices.
The first thing we do is we have to make a marker in the silicon substrate before we put it into those systems. We then take it in there and we put down a layer of hydrogen on the surface. And this layer of hydrogen acts as a mask. We’re going to come along with our scanning probe tip and dissolve some hydrogen, thereby exposing the silcon underneath. And this is how we’re going to bring our atoms in. We dose with phosphine, that brings our phosphorus atoms in. These are going to be our qubits. And they only go in the regions that we’ve depassivated. We then incorporate them into the surface, we encapsulate them with silicon so they’re nice and robust, and we can actually go back and image them at this point to show that they haven’t moved. Then once we’ve done this, we take it out of the vacuum system and we use those registration markers to bring down metal contacts to the device.
So when we first presented this proposal about 10 years ago, a lot of people said, ‘Look, none of that’s been realised. Each one of those stages is incredibly hard to do’. But I’m pleased to say that in Australia over the last 10 years we’ve actually started making these devices. And systematically building, bit by bit, those components of a quantum computer. We’ve made very narrow conducting wires, one atom tall and four atoms wide. They’re very similar to the copper wires that you have in conventional transistors. We’ve made the smallest precision transistors, where we’ve been able to watch individual electrons hop on and off an island of phosphorus atoms. We’ve been able to move to three-dimensional architectures, and for me this is amazing. All the transistors we have at the moment, all the electrons travel in one two-dimensional plane. We don’t use the Z direction at all. So we’ve found a way that we can actually make vertical transistors. And this is something we’re going to use for our quantum computer architecture. And also very recently we’ve been able to isolate a few of these phosphorus atoms and we’ve atually used another transistor pattern nearby to actually measure the electrons’ spins, so we can read out the quantum states in our quantum computer.
But perhaps one of the most difficult challenges for us today has been to isolate a single atom in a device. And just last year we were able to form the world’s first precision single atom transistor. So that really is an individual phosphorus atom sitting in the silicon substrate. We’ve aligned these electrodes to it, taken it out of the vacuum system and made contact to it. And we can actually measure the electronic signature of that single atom directly.
So rather like the human beings in this audience, we each have a well-defined identifiable fingerprint, a single atom also has a well-defined identifiable fingerprint. And this is what the electronic fingerprint of that single atom is. The amazing thing about this is we could change the atom, we’d get a completely different fingerprint. So it really is unique.
So what we’ve demonstrated over the last decade, and we’re leading this field in Australia, is we can make devices out of single atoms. This has taken us all the way down to the end of Moore’s Law. So the question now is: is that the end of computing? And what I’d like to leave you with today is the thought that it’s not the end, it’s just the beginning. So instead of miniaturising transistors over the last 50 years, we’re now going to start from the bottom, and we’re now going to start to build quantum computers where we add individual qubits one at a time. Every time we add a qubit, we double the computational power. So that’s the international race, to try and build a large-scale quantum computer that can do calculations you simply cannot do with a classical computer. And I’d like to leave you with the outstanding group of people that I’ve got working with me in Australia to achieve this dream. So, thank you.