A Google Faculty Research Award propels quantum machine learning forward.
The Physics of Information lab, led by Professor Achim Kempf, was awarded one of the 2018 Google Faculty Research Awards. Kempf’s lab focuses on the physics of information, a wide research field that ranges from general relativity and quantum theory to information theory and artificial intelligence (AI).
The Kempf lab received the Google award for a project in quantum machine learning. Kempf’s PhD student Guillaume Verdon and his Master’s student Evan Peters, with help from undergraduate student Michael Broughton pioneered this project which sits at the interface of quantum theory and deep learning. The research focuses on how artificial intelligence-like algorithms on a quantum computer can be paired, or hybridized, with artificial intelligence on a classical computer. The team caught Google’s attention with substantial papers, such as A Universal Training Algorithm for Quantum Deep Learning in 2018, which details how quantum dynamics can be used to optimize classical and quantum neural networks.
“I took a risk two years ago jumping into this new field of quantum machine learning when nobody had any clue of what it was going to be,” said Verdon. Adding: “I thought that machine learning and quantum machine learning was an area of application that could propel near-term quantum computers forward. Ultimately, I believe that, someday, quantum computers could even help us test our various models of theoretical physics and quantum gravity, thus extending our computational reach and our capabilities for modelling and understanding how the universe works.”
Richard Feynman first proposed quantum computers for the purpose of simulating the world at the quantum level to better understand quantum mechanics. A quantum computer could, for example, simulate chemical reactions which produce new molecules with potentially valuable uses from materials design to drug design. Since chemistry is fundamentally quantum, quantum simulation and the new quantum AI developed in this project should eventually significantly help explore, understand, and refine simulated chemical reactions for materials and drug design.
“It is now believed that the power of quantum computers will reach much beyond chemistry simulations to revolutionize tasks such as artificial intelligence, data search, combinatorial optimization or quantum automated control, just to name a few, well beyond the power of classical computers,” said Kempf.
Within less than a year, researchers predict that quantum computers will reach the critical size beyond which a classical computer can model. Within about two to three years, quantum computers could provide calculational spaces that possess 10^100 dimensions or more. This challenges researchers to now develop the first concrete applications for this upcoming quantum hardware.
To meet this challenge, Kempf and his lab recently teamed up with the research groups of Professors David Gosset, Michele Mosca, Christine Muschik, and Alex Wong. The team, currently considering a further and larger collaboration with Google, is part of the highly developed ecosystem for quantum and computer science at the University of Waterloo. Collaborations like this one continue to further the University of Waterloo’s position as the leading centre for cross-disciplinary quantum research.
First published under Applied Mathematics news.