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A Toronto startup with roots at U of T hopes to catch the next big wave in computing

More than a dozen physicists at Xanadu have links with the Department of Physics. Some are former graduate students, undergraduate students, or postdoctoral fellows. Others are current graduate students involved in Xanadu’s research. And Professor John Sipe is one of the company’s technical advisors.
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For decades, quantum computing research largely happened in university laboratories, where the field’s tremendous theoretical potential contrasted with the reality of slow, incremental progress. Today, though, startups and established tech companies are helping to drive advances in the field, bringing quantum computing into the mainstream.

One Toronto-based startup, Xanadu, is betting on a branch of quantum computing known as “photonics,” which harnesses particles of light, or photons, to manipulate quantum information. In its lab on the 29th floor of a downtown Toronto office tower, the company’s scientists work at dust-free tables chock-a-block with lenses, mirrors and fibre-optic cables, manipulating light at the quantum level to encode and process information. (Outside the lab’s entrance, the scientists have stationed a carton of disposable “booties,” which must be worn inside to keep the space pristine). In all, the company employs 50 people to design, test, refine and sell its light-based quantum computing system.

Adjacent to the lab, the company’s offices bear the telltale signs of startup culture: An open-plan workspace abuts a glassed-in room with a bright blue ping-pong table. Staff sometimes stick around after work to play board games or challenge each other on an arcade machine that runs classic games like Pac-Man and Space Invaders. “More than half of our employees moved to Toronto to join the company,” says Zachary Vernon (BSc 2012, PhD 2017), who works at Xanadu as a physicist. “The office has become like a second home.”

Growing interest in the potential for quantum computing to usher in a new era of digital advances has prompted a race for talent – and investors. Last October, Nature reported that, in recent years, private funders have sunk hundreds of millions of dollars into dozens of quantum technology startups. At the same time, some of the world’s largest tech companies, such as Google and IBM, have ramped up their own investments.

Xanadu, which was founded in 2016, recently secured $32 million in Series A financing, is developing both hardware and open-source software. Unlike many traditional computing businesses, though, the company has no immediate plans to sell devices or enter the consumer market. Instead, it will charge organizations for access to its photonics-based quantum computers through the cloud.

Who will buy? Some of the most obvious clients are those requiring advanced computation, such as banks and pharmaceutical companies. But Xanadu envisions selling a wide range of computing tools for use in fields that require certain kinds of complex calculations, such as drug development. “We see quantum chemistry as a key area,” says Nathan Killoran (MSc 2007), who works on software development for Xanadu. “We try to simulate the properties of a chemical system and then optimize the model to get better and better predictions.” Materials scientists could use these simulations to develop new materials, such as superconductors and industrial chemicals.

How quantum computers work is notoriously difficult to explain. They store and process information in atomic and subatomic particles or other ambiguous entities called “quantum objects.” The laws of physics at this incredibly minute scale should eventually enable quantum computers to outperform the world’s most powerful existing computers on certain tasks. Both startups and established tech companies are racing to achieve this milestone, which is known in the industry as “quantum supremacy.”

The term is ambiguous: last October, Google claimed supremacy for its quantum computer, named Sycamore, which in less than five minutes generated random numbers in a way the company said would take the world’s most powerful computers more than 10,000 years. But critics have argued that traditional machines could have done the calculations much more quickly than Google estimated, and that the task Google selected for Sycamore was too specific and esoteric to be meaningful.

For the full article from The University of Toronto Magazine can be found here: