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 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 a quantum computing breakthrough.
In January, Mike Mayberry (managing director of Intel Labs) said:
“We expect it will be five to seven years before the industry gets to tackling engineering-scale problems, and it will likely require 1 million or more qubits to achieve commercial relevance.”
Three weeks later, the Financial Times reported that Google is still expected to demonstrate quantum supremacy in the near term, calling it an “impending milestone.” (You may recall Google projected achieving quantum supremacy by the end of 2017 until IBM moved the goalposts back on them.)
In that same Financial Times article, Todd Holmdahl, corporate vice president of Microsoft Quantum, said that Microsoft is “imminently close” to producing a working qubit. Holmdahl backs Microsoft’s self-imposed five-year deadline for producing a chip.
Dr. Kalai’s primary concern seems to be error correction. Microsoft’s qubit design tackles that issue directly. If they are successful in creating a topological qubit, they will theoretically build in a level of fault tolerance that would give them a competitive advantage. Holmdahl casually threw shade on the competition:
“They’ve got so many errors in them, they’re just going to tap out. Where they need 1,000 or 10,000 [qubits], we’ll only need one, because our error-correction is so much better than theirs.”
Holmdahl is a corporate veep, not a scientist. Part of his job is to project confidence. But just last week on the other side of the world, a team of Australian researchers at the University of Sydney made a theoretical breakthrough in error correction from a different angle.
David Tuckett, Stephen Bartlett, and Steven Flammia have found what Gizmodo is calling a “quantum hack” that improves error correction up to 400 percent (not a typo). By “tailoring [their] quantum decoder to match the properties of the noise experienced by the qubits,” the team projects a 4x increase in the error correction threshold, assuming ideal hardware.
I’m offering a counterpoint to Dr. Kalai’s claim. To be certain, there are challenges to overcome. But lots of wicked smart people backed by lots of research dollars are attacking them as I type. Sure, it’s going to be a while before Joe Average touches a quantum computer. But developers? Data scientists? Researchers in other scientific fields? For them, I believe, it’s not so far off. I read Microsoft’s Quantum Development Kit and IBM Q as signs we are closer than many suspect.
My money’s on three years in the office pool. You can call me nuts, but I have a feeling we’re going to get a lot of big news from the major players in 2018. And when we reach that inflection point, the quantum changes are going to pass you by quicker than Vin Diesel in Fast and Furious 27.
I’ll leave you with one more thought from Mr. Holmdahl:
“This is happening. It’s kind of like space exploration. We’re going to send people to the moon.”
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.
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, the physicist credited with the idea for a quantum computer, once quipped, “By golly, it’s a wonderful problem, because it doesn’t look so easy.”
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.