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Techquantum computing

U.K. startup’s breakthrough could aid quantum computers in the hunt for exotic materials

Jeremy Kahn
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Jeremy Kahn
Jeremy Kahn
Editor, AI
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Jeremy Kahn
By
Jeremy Kahn
Jeremy Kahn
Editor, AI
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December 10, 2020, 11:00 AM ET
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A small U.K. startup has developed an algorithm that significantly reduces the level of quantum computing power needed to run a calculation that could pave the way for the development of exotic new materials.

Scientists from the company, Phasecraft, along with researchers from the University of Bristol, showed that an important problem from quantum physics—one that is too difficult to solve on today’s supercomputers—could be within the reach of quantum computers within three years, given current rates at which the technology is developing. That is much sooner than most experts had previously forecast.
 
Quantum computers are machines that harness the peculiar properties of quantum physics to run their calculations. This makes them potentially much more powerful than today’s fastest supercomputers.

Many companies are beginning to experiment with quantum computers, which are being offered through cloud computing interfaces from companies such as IBM, Honeywell, and Google, as well as a number of startups. But so far, most businesses have only run proof-of-concept projects on these machines, which are not yet powerful enough to simulate many complex systems, such as the modeling of subatomic or molecular level interactions.

Last year, Google claimed it had achieved a milestone called “quantum supremacy,” using a quantum computer to run a calculation that a conventional computer could not crunch in a reasonable time span. Last week, a group of Chinese researchers said they had achieved a similar breakthrough using a different kind of quantum computer.

“Toy problems”

But in both cases, the particular problems that the quantum computers solved were what John Morton, a Phasecraft cofounder and professor of quantum physics at University College London, calls “toy problems”—calculations formulated solely to show that the quantum computer could do something a regular supercomputer can’t. They weren’t problems with clear implications for real world applications, such as figuring out how to create more efficient fertilizer manufacturing processes or better batteries.

What Phasecraft shows in a peer-reviewed paper published today in the academic journal Physical Review B, published by the American Physical Society, is different. It involves a problem called the Fermi-Hubbard model, which describes the behavior of a class of subatomic particles known as fermions—a group that includes electrons—as they hop around within a solid. Being able to compute this model is an important step toward creating materials that will exhibit superconducting properties without the need to keep them at ultra-freezing temperatures. But doing so for a system with more than a few tens of particle positions is beyond the reach of today’s conventional supercomputers.

The Phasecraft researchers proved that a kind of algorithm that combines quantum and classical elements could be used to solve the Fermi-Hubbard model for a large solid using a quantum computer with about 8,000 gates, a term that refers to the number of logical operations a quantum computer can perform. That is a tenth of the number of quantum gates that were previously thought necessary to solve the model.

“Their work suggests that surprisingly low-depth circuits could provide useful information about this model, making it more accessible to realistic quantum hardware,” Andrew Childs, a computer scientist at the University of Maryland, said of the research.

Existing quantum computers already have enough quantum processing units—known as qubits—to in theory perform this number of logical operations, but so far scientists have not figured out how to build circuits of that size. Google’s quantum supremacy experiment, which it performed on its 54-qubit Sycamore quantum processor, used a circuit consisting of 430 two-qubit gates and 1,113 single qubit gates.

IBM has already announced its plans to have a 1,000-qubit quantum computer available by 2023. With a quantum computer of that size, it is possible scientists will be able to build a circuit with enough gates to solve the Fermi-Hubbard model using the algorithm Phasecraft demonstrated. “We think it is plausible to do exciting things in the next two- to three-year period,” Ashley Montanaro, one of Phasecraft’s cofounders and directors, as well as a quantum computer researcher at the University of Bristol, said.

Funding deal

Phasecraft, which has partnerships with Rigetti, a California-based startup building quantum computers, and Google, is focused on working with materials science and chemical companies to design quantum algorithms that will allow them to start solving complex problems using quantum computers.

The startup, which currently employs about 10 people, also announced on Thursday that it has received $5 million in seed funding in a financing round led by LocalGlobe, a London venture capital firm, with participation from Episode 1, another London venture firm specializing in early stage investment. Ian Hogarth, the former cofounder of concert discovery app Songkick and now a prominent angel and seed investor, is joining Phasecraft’s board as chairperson.

The new investment brings the total Phasecraft has raised, in both venture funding and research grants, since its founding in 2018, to $7.4 million. The company had received prior funding from the UCL Technology Fund and Parkwalk Advisors and grants from Innovate UK.

About the Author
Jeremy Kahn
By Jeremy KahnEditor, AI
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Jeremy Kahn is the AI editor at Fortune, spearheading the publication's coverage of artificial intelligence. He also co-authors Eye on AI, Fortune’s flagship AI newsletter.

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