11 questions for Geordie D. Wave

Dr. Geordie Rose is the founder and Chief Technology Officer of D-Wave Systems, a Canadian start-up that recently demonstrated – to a mixed response from the media and the scientific community – a prototype quantum processor based upon superconducting technology. Geordie recently stopped by Room 408 to chat about stealing cars, Metallica and his newfound love of wrestling on the train.

Do you feel that you are responsible for educating the public about quantum computing and, in particular, about the distinction between a system like Orion and a universal quantum computer?

The short answer is yes, although this is a tough question. In the early days of the company, I spent a lot of my time meeting with smart people who’d never heard of QC, and trying to explain what it was and why people were excited about it. Generally these people were potential investors and sometimes people we’d targeted to hire. I have explained the premise, promise & limitations of QCs to about 50 of the top VCs in the bay area. In order to be successful in financing a project like this you have to be brutally honest with your investors and the people you work with. I have always attempted to be clear about the limitations of the approach we’ve taken, without underselling the future promise. I think that many noisy qubits are a prerequisite for any future universal QC.

Another important point is that the answer to your question depends on the definition of “public”. In the early days, the audience we focused on were potential investors. Now that we have a working prototype, our focus has shifted to potential corporate partners & potential applications developers who can help us take the technology to the next stage. We are too small to have any educational ambitions outside of this limited group.

Microsoft are gaining market share with the Xbox 360. Will you also be releasing a HD-DVD add-on for Orion?

It would totally kick ass if we could find a way to use this machine to help with games. There are actually some potential scheduling-type applications for on-line games.

Can you outline the main technical challenges that must be overcome before a system such as Orion is scalable and universal?

There are several aspects of the current design that aren’t scalable to the levels we want to be able to achieve (thousands to millions of qubits). The next processor generation, which we’ll release Q4/2007, has planned fixes to all of these. Whether or not the redesigned processor elements do the job of course remains to be seen.

Re. universality, the Hamiltonian of the current system isn’t universal, in the sense that arbitrary states can’t be encoded in its ground state. The Hamiltonian is of the form X+Z+ZZ. It’s known that adding another type of coupling device to give something like X+Z+ZZ+XZ (for example) allows for universal state encoding in the ground state.

Of course this isn’t enough. Making the system we’ve got now universal is of course very hard. The question is whether or not it’s worth trying to do this. Ultimately this question resolves down to the potential value of applications requiring resources the current type of chip can’t provide. It could be that for certain quantum chemistry applications the value of modifying the chip design to get closer to universal QC might be worth the effort, although I see a big opportunity just sticking to discrete optimization problems.

Steve Jobs is now claiming that quantum computing was his idea all along. Any comments?

Everybody knows that Al Gore invented quantum computing.

We noticed in the demo that you were running Windows XP. Is that because Orion did not meet the hardware requirements to run Vista?

We can’t afford Vista.

At what point did you feel that the field of quantum computing was sufficiently mature that a commercial organization would be more well placed than a university to develop the technology and its applications?

It’s always been clear to me that any serious effort to build real large-scale quantum computers has to start in a start-up. Universities and research institutes can’t provide enough infrastructural support to their researchers to give them a chance. A start-up can plan and finance a 10-15 year project and hand-pick the best possible staff for all of the multitude of tasks that need to occur to build something so complicated. I actually talk a little bit about this in one of my blog posts (see here) although that focuses more on the big company vs. start up question.

Looking toward the future now, will Grand Theft Auto 4 be exclusive to Orion?

This reminds me of a comment someone made about online QCs solving optimization problems. It went something like this:

* programmer: QC, please solve traveling salesman problem.
* QC: All cities terminated. Problem solved.

The point being that as long as these systems can’t actually start jacking cars we should be OK.

Given the unabated advancement of classical computing technology, and given that Orion doesn’t appear to enable the efficient solution of problems that can’t already be solved efficiently by a classical computer, for what problem size do you expect that a system such as Orion will be able to outperform the fastest classical computer? When do you expect to achieve this?

This is a real hard question to answer. Our best guess is that the ability to solve 256-variable integer programming problems in hardware will be close to break even for certain instance classes.

There are two tough problems to solve in developing a predictive model to answer performance questions. The first is that since this type of system is a “hardware heuristic” there will definitely be instance-dependence and we don’t know what the types of instances that will be best suited to the system look like yet. The second is that there’s no way to predict the scaling advantage from having the system be quantum mechanical. You can look at general arguments to ascertain bounds on performance, but how the machine will function in practice is an entirely different problem. Our attitude is that it’s at least as tough to try to develop realistic models and solve them as it is to actually build real hardware, so we focus on building real hardware and having very fast redesign cycles.

I think also that because the approach we’ve taken can be taken far past the projected cross-over point (up to say a million qubits, which should be able to encode 10s of thousands of variables), even if we’re wrong on where the cross-over point is we can continue building bigger and bigger systems.

Will the next generation computer be called One or Master of Puppets?

Master of Puppets is an awesome name. I will suggest it.

In hindsight, and given the difficulty and the complexity of what you are trying to achieve, are there any mistakes or boobies that have been made along the way?

Too many to list. The biggest one was not paying enough attention to all of the different computational models from the beginning. I think that the gate model–at least for superconducting systems–is probably the most difficult of all of them to enable. AQC is very well suited to superconducting implementations, I wish we’d realized that a few years earlier.

And finally, what do D-Wave employees do on the train to work now that you can all solve sudoku puzzles with an exponential speed up?

No exponential speed up unfortunately.

I can’t speak for everybody else, but lately I have been obsessed with the fact that I drop my right elbow when I throw my right hook. I keep getting hammered over the top whenever I spar with conventional fighters who are taller than I am.

Geordie, best of luck and thank you for your time.

You’re welcome!