Innovation Summer 2026

Dr. Martin Laforest (Quantacet)

Dr. Joseph Salfi, P.Eng. (UBC)

Dr. Thomas Baker (UVic)

ranging from energy storage to chemical processing. “Things like molecular simulation are enormously expensive on the classical computer to do accurately,” he said. Where he would ultimately like to see quantum computing pointed at is in helping develop solutions to combat the effects of climate change. “We’re writing a ton of grants about this right now,” Baker said. “If we can come to a quantum computer that’s useful and can drive this, you could start talking about carbon-capture techniques and better modelling of lithium-ion batteries.” Building hardware a challenge If quantum computers promise extraordinary capabilities, they are also extraordinarily difficult to build. Researchers and industry leaders agree the issue is not understanding quantum mechanics, but controlling it reliably outside the laboratory. And that is squarely an engineering problem. “Ninety-nine percent of all quantum scientists would agree that quantum hardware is the limitation,” Salfi said, adding that the heart of the problem is noise. “There’s a process in nature called decoherence,” Salfi explained. “That’s the number one enemy of quantum computation on hardware.” Any unwanted interaction with the environment can disturb a qubit’s fragile quantum state. “Those errors come from a ton of sources,” Laforest said, gesturing toward materials, electronics, vibration, and fabrication quality.

The consequence is not that quantum computers magically brute force every possible solution, but that they can encode and manipulate information in a fundamentally different mathematical space. “For the first time ever, we are building a computer with a completely different toolbox,” Laforest said. “That toolbox is proven physically and mathematically to be fundamentally more powerful than the old toolbox.” Powerful multi-variable problem solving Despite the headline-grabbing promise of quantum advantage, quantum computers will not completely replace classical ones. Generally, computational problems that scale linearly will still be best served by classical computers. Instead, quantum computers are expected to become powerful tools for specific tasks like multi-variable optimization problems, or simulating nature itself. “If we wanted to do an exact computational design of a material, a catalyst, or a pharmaceutical, that’s basically impossible on a classical computer,” Salfi said. Quantum systems, by contrast, operate using the same physical rules as the systems they model; instead of approximating their behaviour with huge amounts of math the way classical computers do, quantum computers can represent and “run” a version of the system using the same kinds of quantum interactions that happen in the real world. Baker highlighted additional opportunities in fields

Innovation Summer 2026

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