Classical computers. I don’t often give them their due on this blog, but classical is still king. And apparently, not interested in giving up the crown without a fight. I think we’ll soon see a quantum computer demonstrate quantum supremacy in a way that we can all take to the bank. However, physicists and engineers in labs around the world are still struggling to overcome the hardware challenges. Quantum software applications might as well be an endangered species. Richard Feynman once quipped, “By golly, it’s a wonderful problem, because it doesn’t look so easy.”
Compounding the challenges of encouraging private investment in quantum technologies and driving quantum adoption, quasi-quantum classical algorithms keep raising the threshold for quantum supremacy. In fact, some people have built their reputations on responding to quantum computing claims by engineering more efficient classical solutions.
I kid, but this is a semi-serious issue in the industry. For a mainstream CIO to invest in quantum technology, we need to be able to show that it isn’t a windmill we’re tilting at. We need to collaborate to create quantum computing solutions to problems that are relevant to the Fortune 500, or whatever group of influencers you look to. CIOs aren’t going to invest unless they can see the ROI.
Helmut Katzgraber is one of the big brains that’s been keeping quantum honest for the last few years, and a friend of superposition.com. He was nice enough to provide a quote on the subject:
Over the last few years we have been developing state-of-the-art classical heuristics to raise the bar for any quantum (and especially quantum annealing) technologies. Not only is this of importance when new hardware claims are made, it also pushes classical optimization into a new era where physics plays a pivotal role. Quantum-inspired algorithms have resulted in very powerful methods to solve hard discrete optimization problems in industry. We are currently working with industrial partners—sometimes even using specialized hardware—to tackle the hardest problems out there. An important byproduct of these developments is the continuous merging of classical and quantum. Near and medium-term quantum devices will likely be co-processors in the cloud. Research for hybrid systems is therefore key for a successful deployment of quantum devices to tackle the hardest problems humanity currently faces.
For Helmut, this pattern is old news. And I agree, it’s great that quantum is pushing classical optimization to new heights. I just wonder when we get to cross the streams.
The good news is, we’re making progress on this issue on multiple fronts. We know that Google had a plan to achieve quantum supremacy with 49 qubits, only to have IBM move the threshold to 57 qubits. But what I haven’t previously discussed, is the research that gave Google confidence that quantum supremacy was near-term achievable. I’ve written a couple of posts recently that touched on the error correction challenge. The fear is that errors will increase exponentially as the number of qubits increases.
With nine superconducting qubits, Google researchers demonstrated last year that:
“. . . errors do not scale rapidly in [Google’s] superconducting chips. Instead . . . errors increase slowly in a way that should allow the meaningful superposition of up to 60 qubits.”
That research is still promising, it’s just going to take 57 qubits instead of 49 for quantum supremacy. More importantly, in collaboration with the NASA Ames Research Center, the University of Technology Sydney, and the University of California, Santa Barbara, Google researchers have also shown that its possible under the right conditions to demonstrate quantum supremacy using quantum devices without error correction.
On the practical application front, I think we could take some cues from D-Wave’s approach to collaborating with users in the scientific community. Each generation of D-Wave’s hardware features improvements drawn directly from researcher’s feedback. Not only does this accelerate the pace at which we’ll demonstrate a practical application, but it also drives user excitement. (D-Wave is working on a model that will provide more complex connections between qubits.)
‘Changing the underlying connectivity is going to be a game-changer,’ says Mark Novotny, a physicist at Charles University in Prague, who is exploring a D-Wave machine’s applications to cybersecurity. ‘I’m basically drooling hoping for it. It’s very exciting.’
Every company wants to generate that kind of anticipation. I think the major players are all moving in the right direction, giving online access to early chips, simulators, and development kits. Ultimately, it’s a symbiotic relationship. In the long term, pushing the classical envelope will drive quantum achievement. And I still believe the foundation is there to achieve quantum supremacy soon, maybe even this year.
Listen, I have to take a short break from the quantum commentary to address the rumors, e-mails, Facebook messages, tweets, and InMail (and that one snap chat someone sent; you know who you are). You all know by now I’m fascinated with quantum computing, because I never shut up about it. I figure it’s time to do something about that. Which is why I’m taking a couple weeks off to launch my own entry into the quantum computing fray.
Last week I shared with you that mathematician Gil Kalai doesn’t believe quantum computing is possible. He says the math just isn’t there to ever achieve reliable, practical error correction. Not that Dr. Kalai is alone in this belief, but there sure are a lot of major players that seem to think we’re on the verge of one of the biggest shifts in computing in the last 100 years.
If there’s one thing I love, it’s seeing talented young people get involved and take charge of the future. Especially when it’s quantum computing they’re getting involved in. Patrick Rall and Bryce Fuller are definitely involved, teaching future developers at the University of Texas about quantum algorithms.