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This article was published on January 20, 2022

Nuclear quantum computing: It’s coming

Brought to you by the US Army


Nuclear quantum computing: It’s coming
Tristan Greene
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Tristan Greene

Editor, Neural by TNW

Tristan is a futurist covering human-centric artificial intelligence advances, quantum computing, STEM, physics, and space stuff. Pronouns: Tristan is a futurist covering human-centric artificial intelligence advances, quantum computing, STEM, physics, and space stuff. Pronouns: He/him

A trio of separate research teams from three different continents published individual papers indicating similar quantum computing breakthroughs yesterday. All three were funded in part by the US Army and each paper appears to be a slam dunk for the future of quantum computing.

But only one of them heralds the onset of the age of nuclear quantum computers.

It’s about damn time

Maybe it’s the whole concept of entanglement, but for a long time it’s felt like we were suspended in a state where functional quantum machines were both “right around the corner” and “decades or more away.”

But the past few years have seen a more rapid advancement toward functional quantum systems than most technologists could have imagined in their wildest dreams.

The likes of IBM, Microsoft, D-Wave, and Google putting hybrid quantum systems on the cloud coupled with the latter’s amazing time crystal breakthrough have made 2018-2021 the opening years of what promises to be a golden age for quantum computing.

Despite this amazing progress, there are still holdouts who believe we’ll never have a truly useful, fully-functional, qubit-based quantum computing system.

The main reason given by these cynics is usually because quantum systems are incredibly error-prone.

Not anymore?

The three new papers published yesterday (here, here, and here) should go a long way towards shutting those critics up because each of them manages to address the error-correction problem in quantum computing by, essentially, going back to the drawing board.

The first two teams, one from Tokyo and one from Los Angeles, went about the issue in a similar way while the Australian team decided to take a different approach.

In fact, it’s worth noting that all three teams shared various resources in order to help facilitate each other’s research.

The result is that each team was able to build a distinct, silicon-based, two-qubit quantum computing system capable of operating with greater than 99% accuracy.

So what?

That’s pretty cool, but dozens of quantum research centers including IBM’s, Google’s, and Microsoft’s have all developed functional quantum gate systems with dozens or even hundreds of qubits.

IBM and Google, for example, both claim they’ve reached “quantum advantage,” or the point where their quantum computing systems can do things that no regular classical computing system could.

But here in 2022 we’re not talking about being able to flip a switch and do quantum calculations. We’re talking about cutting-edge computation systems that require enormous resources to pull off incredibly specific feats.

You can’t just upload a neural network to a quantum computer and expect to act like it’s been supercharged. The algorithms we’re currently able to run on cutting-edge quantum systems are more like super-challenging math problems that can still be verified using classical means.

Unfortunately, the long and short of it is usually: the more qubits you have the more errors you get.

The new research hopes to alleviate that by creating a new way to handle qubit operations, thus allowing gate-based quantum computer systems to scale.

And, right now, scalability is the single largest hurdle standing in the technology’s way.

The solution?

It’s actually fairly simple. All three teams are trying to put qubits on a silicon chip. As Ars Technica’s John Timmer pointed out yesterday, this plays to our current engineering strengths:

That possibility is what makes several results being published yesterday interesting. While there are differences among the three results being announced, they all have one thing in common: high-quality qubits produced in silicon. After all, if there’s anything we know how to scale, it’s silicon-based technologies.

What we found most interesting however, is the mind-boggling way in which the Australian team managed to create a pair of nearly errorless qubits: they went nuclear.

In a press release from the University of New South Wales, Mateusz Madzik, a lead author on the Australian team’s research paper, described how entangling an electron with the nuclei of two phosphorous atoms allowed them to control them as qubits without losing information.

Per Madzik:

If you have two nuclei that are connected to the same electron, you can make them do a quantum operation.

While you don’t operate the electron, those nuclei safely store their quantum information. But now you have the option of making them talk to each other via the electron, to realize universal quantum operations that can be adapted to any computational problem.

Is that safe?

Sure it is. They’re not splitting atoms or fusing them, so there’s probably a pretty close to zero chance that nothing bad will happen. We exploit atoms to do all kinds of things that don’t involve blowing up entire cities.

In this case, the Australian team is exploiting a feature of entanglement that allows them to force communication between qubits that, normally, would either hoard their information or lose it too quickly for use.

It’s likely just as safe as using lasers to create qubits out of light, maybe even safer. But the researchers are hoping it’s the foundation for a paradigm that will be much easier to scale than other systems.

At the end of the day this is all exciting news. It’s rare to see a peer-reviewed quantum computing breakthrough because the field is incredibly challenging. Getting three in the same day is a eureka moment in its own right.

Of course, it could take a while for these early experiments to pan out and turn into full-fledged quantum computers. But, if we take these papers as a proof-of-concept for the future, things look incredibly bright.

You can read more about quantum computing, artificial intelligence, and the wacky world of physics and other mind-blowing future tech right here on Neural.

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