Insider Brief

  • A Canadian-led research team from TRIUMF and the Perimeter Institute has developed a quantum-assisted AI model to simulate particle collisions more efficiently, addressing global computational challenges.
  • The study demonstrates that combining deep learning with quantum computing—using technology from D-Wave—can significantly reduce the time and cost of high-energy physics simulations.
  • Published in npj Quantum Information, the work supports future upgrades to CERN’s Large Hadron Collider and underscores Canada’s growing leadership in quantum and AI-driven scientific research.

PRESS RELEASE — In a landmark achievement for Canadian science, a team of scientists led by TRIUMF and the Perimeter Institute for Theoretical Physics have unveiled transformative research that – for the first time – merges quantum computing techniques with advanced AI to model complex simulations in a fast, accurate and energy-efficient way.

“This is a uniquely Canadian success story,” said Wojciech Fedorko, Deputy Department Head, Scientific Computing at TRIUMF. “Uniting the expertise from our country’s research institutions and industry leaders has not only advanced our ability to carry out fundamental research, but also demonstrated Canada’s ability to lead the world in quantum and AI innovation.”

Traditional simulations of particle collisions are already both time-consuming and costly, often running on massive supercomputers for weeks or months. By leveraging quantum processes and technology made possible by California-based D-Wave Quantum Inc., the researchers were able to create a new “quantum-assisted” generative model capable of running simulations and open new opportunities to cost-effectively analyze rapidly growing data sets.

The research, published today in npj Quantum Information, is part of a worldwide effort to create the tools needed to accommodate upgrades to CERN’s particle accelerator, the Large Hadron Collider (LHC), and alleviate a computational bottleneck that would impact researchers all over the world.

“Our method shows that quantum and AI technologies developed here in Canada can solve real-world scientific bottlenecks,” said Javier Toledo-Marín, joint appointee at TRIUMF and Perimeter Institute. “By combining deep learning with quantum technology, we are forging a new path for both theoretical experimentation and technological application.”

In addition to TRIUMF and Perimeter, contributions to the published research came from the National Research Council of Canada (NRC), the University of British Columbia and the University of Virginia, showcasing not only the wealth of research talent and scientific ingenuity across the country, but also the international collaboration that places Canada at the forefront of worldwide scientific innovation.


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