Measurably advancing quantum-classical computer hybrids
In a paper published on June 1 in Physical Review Letters, a team including Perimeter Associate Faculty member Christine Muschik outlines a new approach to hybridizing classical and quantum computers. Her technique draws on elements of two famously incompatible physics frameworks to produce more robust, powerful problem-solving technologies.
“Hybrid computing offers exciting possibilities,” says Muschik, who is also an Assistant Professor with the Institute for Quantum Computing at the University of Waterloo. “Companies and scientists around the world are exploring how to use hybrid systems to make new discoveries in materials science, fundamental physics, chemistry, and drug design.”
This potential relies on bridging the macroscopic realm of classical physics and the subatomic world that is dominated by quantum mechanics. While each of these systems is powerful in its own right, they have never been combined into a single theoretical framework – despite the fact that they clearly co-exist in reality.
While theoretical physicists continue to work to understand how quantum and classical physics relate to one another, technology that takes advantage of both is advancing at an accelerating pace.
Muschik and her co-authors propose using a uniquely quantum property known as “entanglement” in a new way to improve information processing.
Entangled particles share an inextricable physical state, which means their properties can only be described as part of the same whole. Entanglement is essential to all quantum computing, but in their paper, “Measurement-Based Variational Quantum Eigensolver,” the authors describe a new method of sequentially measuring entangled states that makes hybrid quantum-classical computing more powerful and robust, and provides major advantages over existing circuit-based approaches.
“While the circuit-based and measurement-based models both allow for universal quantum computation … they are intrinsically different,” the authors write. “For certain applications, the required coherence times and error thresholds are much less demanding for [measurement-based quantum computing].”
“This takes us closer to the things researchers dream about: creating new medicines, discovering lighter, stronger materials for airplanes, improving atmospheric carbon capture.”
In other words, this new approach allows a small quantum computer to complete more difficult tasks.
Muschik, a theoretical physicist with an active interest in proof-of-concept experiments, says this approach can be used to run quantum simulations and solve highly complex optimization problems.
“Our method is extremely resource efficient: it can use small quantum states because we custom-tailor them to specific types of problems. And our optimisation-feedback loop method has no analogy in the traditional circuit-based model,” she says.
“This takes us closer to the things researchers dream about: creating new medicines, discovering lighter, stronger materials for airplanes, improving atmospheric carbon capture. There are so many possibilities.”
The measurement method provides higher error tolerance than circuit-based approaches – a key benefit for today’s quantum computers. The current state of the art is known by its limitations: the acronym NISQ applies to today’s “noisy, intermediate-scale quantum” computers.
“Quantum computers are still in their infancy. They’re experimental and fragile,” Muschik says. “By using a measurement-based approach in a feedback loop with a regular computer, we invented a new way of overcoming these limitations to tackle harder problems.”
Her approach should lead to the development of new applications, including better optimization algorithms. Measurement-based programs can also run on more types of quantum computers, including photonic-based systems, which are potentially powerful, but largely incompatible with circuit-based systems.
Muschik says this advance comes at a key inflection point in the progress of quantum computing, as the technology increasingly transitions from experimental research to practical application.
“We’re right on the edge, I would say,” she says. “Companies like Google and IBM are pumping a lot of money into quantum technologies. This is why we see this explosion of hardware. Everybody is hunting for a useful quantum advantage. I believe we’re just on the verge of finding it.”
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