Subtitles section Play video Print subtitles MALE SPEAKER: Good afternoon. Thanks, everybody, for coming from the remote sites to attend the talk by John Martinis about the design of a superconducting quantum computer. And we're very pleased to have John here with us, just a short ride from UC Santa Barbara. And the reason we are excited is John is considered one of the world, if not THE world authority, on superconducting qubits. So since the current machine we're working on is based on superconducting qubits, of course, his opinion and advice would be very important for the guidance of our project. So John got his PhD in physics in 1987 from UC Berkeley in California. But then went to France to the Commisiariat Energie Atomic in Saclay. Afterwards, he worked in NIST in Boulder. And then in 2004, he settled where he is right now, being full professor at UC Santa Barbara. And then in 2010, nice achievement, getting the AAAS Science Breakthrough of the Year award for his work on a quantum mechanic oscillator. So we are very curious to hear your-- JOHN MARTINIS: OK. Thank you very much. MALE SPEAKER: Oh, one last thing I should say is you remote sites, when the talks over, at this time you guys will be able to ummute, and then you can ask questions remotely. Thank you. JOHN MARTINIS: Thank you very much for the kind invitation to come here. I have a son who's a computer science major at UC Berkeley. And I don't know if you have kids. When you have kids and they're young, the parents can do no wrong. And then they turn into teenagers, and their esteem of you goes down. And then, as they get into the real world, you suddenly become more and more intelligent for some reason. So coming to Google, for my son, is totally cool. Makes me totally cool. So I'm at a much higher esteem today after doing this. I want to talk about our project now to work on superconducting qubits. And to talk about some recent, kind of amazing results here. This is maybe one of the first times we're talking about these results. The ideas of quantum computing have been around for 20, 25 years or so. The idea here is you can do some kind of calculations maybe much, much more powerfully than you can ever do with a classical computer, taking advantage of quantum states. But it's been 20 years or so. And you might ask, well, is it really possible to actually build a quantum computer? It's maybe a theorist's dream. Or I've heard one paper call it a physics nightmare to build a quantum computer. It's really hard. We've been going at it for 20 years. Are we really going to get there? Is it possible? And what I want to do is talk today about some theoretical understandings in the last few years, and some recent results in the last year. Really coming up to data-- I'm going to show data we've taken in the last few weeks. Where we really think we can build a fault-tolerant quantum computer. And we can start down a road to really harvest, to take advantage of the power of quantum computation. So I'm going to talk about the theory. I'm going to talk about our new superconducting qubits. Basically, here, with the theory for fault-tolerant quantum computer, you have to make your qubits well, with an error per step of about 1%. Then you can start building a quantum computer. I'm going to show here that, in fact, we've done that. To motivate this, I want to talk a little bit about D-Wave, because people at Google and elsewhere are thinking about that. And exponential computing power. And then a little bit more about the need for fault-tolerant computer computation to do this. So let's just start with the D-Wave Here's their machine. Beautiful blue picture here. They've been very clever in their market to solve optimization problems, essentially mapping it to physics of what's called a spin glass. And one of the big conjectures of the D-Wave machine is, because they're doing this energy minimization optimization, mapping it to this physics problem, maybe you don't have to build a quantum computer with much coherence at all. And in fact, their machine has about 10,000 times less coherence then the kind of devices we're talking here. So it's a different way of looking at it. And the nice thing is, once you make that conjecture and assumption, it's not too hard to go ahead and use standard Josephson junction fabrication and build a device to try to do that. So it's an interesting conjecture. The machine has superb engineering. It really is a very, very nice piece of work, with the low-temperature physics involved in all that. The problem is, well, although they think they could be useful, a lot of physicists are very skeptical of whether it will have exponential computing power. And I've been enjoying talking to people here at Google and other places, because they've said, well, what does nature have to say in this? So they've actually taken the machine and done some experiments. And I'm just going to review the experiments here. And this is basically the system size versus the time that it takes for the D-Wave machine to anneal to, effectively, the ground state. You're doing the spin glass problem with random couplings between the spins. And they're plotting a typical mean execution time. And with the D-Wave machine, initially for small numbers up to maybe 100, it was pretty flat. But now the latest results, up to 512. It's starting to grow exponentially. This exponential growth is actually matched by some quantum-simulated annealing-- both to stimulated, classical annealing and other methods. So the preliminary results here, maybe for this particular class of problems, it's no faster than classical code. Although people are looking at it. That's not a firm conclusion yet. And one has to do more work to see exactly what's going on in the D-Wave and can you use it. We're going to take an approach that's very, very different than this D-Wave machine. It's the conventional, classical approach where physicists have proved theoretically-- it's still only theory-- but they have a very strong belief they should be able to build a computer with exponential power. Let me just explain that briefly. It's easy to understand. You take a regular computer, and the classical computer scales linearly with, say, the speed of the processor or the number of processors. It's very well understood. The beauty of CMOS is that the growth of this power actually goes exponentially in time because of the technology improvements. But it's linearly with, say, speed or processor number. However, in the quantum computer, this power grows exponentially. And the basic way to see this is, in a quantum computer, it's not just a 0 or a 1 state. You can put it in a superposition of a 0 and 1 state. Just like you say that the electron is orbiting around an atom, and it can be on one side of the atom or the other. There's an electron cloud. At the same time, you can have these quantum bit states that are both 0 and 1 at the same time. So here, for example, we take three quantum bits, put it as a superposition, a 0 and 1. You write that out. You have 8 possible states that the initial state can be in. And you're in a quantum linear superposition