Rolls-Royce, Riverlane, and Xanadu have won a joint Canada-UK quantum computing bid, securing over £400,000 in grant funding from Innovate UK and an additional CAD $500,000 from the National Research Council of Canada Industrial Research Assistance Program. The project, named CATALYST, aims to develop applications for quantum computers to model air flow through jet engines.
The partnership will create a hybrid quantum-classical framework, allowing Rolls-Royce to evaluate and implement new quantum algorithms more efficiently. The project aligns with the UK Government’s National Quantum Strategy Missions and is expected to bring significant efficiencies to future product design processes.
Quantum Computing Collaboration Secures Funding for Jet Engine Modelling
Rolls-Royce, Riverlane, and Xanadu have successfully obtained a grant exceeding £400,000 from Innovate UK. This funding is intended to expedite the development of applications that will enable quantum computers to simulate the flow of air through jet engines. An additional CAD $500,000 has been awarded by the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP), reflecting the growing collaboration between the UK and Canada in the field of quantum computing technology and expertise.
The project, named CATALYST, aims to create a hybrid quantum-classical framework. This framework will allow conventional computers to instruct quantum computers, providing Rolls-Royce with the capability to swiftly evaluate and implement new quantum algorithms. This could reduce the time taken for such processes from several hours to mere minutes, potentially bringing significant efficiencies to future product design processes. This project aligns with the UK Government’s recently announced National Quantum Strategy Missions.
Quantum Computing Companies Collaborate on CATALYST Project
Riverlane, a UK-based quantum error correction company, and Xanadu, a quantum computing company based in Ontario, Canada, are existing collaborators with Rolls-Royce on other projects. They share the belief that only error-corrected quantum computers will provide a sustainable quantum advantage.
Leigh Lapworth, a Rolls-Royce Fellow in Computational Science, stated that this is the first quantum computing research and development collaboration led by a large industry partner rather than smaller start-ups. He expressed optimism that the techniques developed in this project will enable them to benefit from the UK’s quantum pathway of a million error-corrected quantum operations in 2028; a billion in 2032; and a trillion in 2035.
Unique Expertise of Each Partner in CATALYST Project
The CATALYST project leverages the unique expertise of each partner: Rolls-Royce brings industrial applications; Riverlane contributes quantum algorithms; and Xanadu provides hybrid quantum-classical compilation.
Steve Brierley, CEO and Founder of Riverlane, stated that the CATALYST project unites leading quantum computing companies and industry experts from the UK and Canada to enhance the quality of the quantum algorithms. He believes that by developing superior quantum algorithms, they can reduce the number of quantum operations required to unlock transformative applications.
Quantum Software Technical Stack and Future Ambitions
Josh Izaac, Director of Product at Xanadu, emphasized the need to re-think the quantum software technical stack as quantum hardware continues to grow in both scale and capabilities. He expressed that working alongside Rolls-Royce and Riverlane, leaders in algorithm development and quantum error correction, will guide the design and development of Catalyst, their just-in-time quantum compilation framework. This will unlock the ability to explore larger, more complex, and more dynamic quantum algorithms.
Rolls-Royce’s largest research models solve equations with several billion variables and its ambition is to reach a trillion and beyond. It is anticipated that it will be a decade or more before quantum computers achieve these scales. However, the journey from here to there requires many problems to be solved, each one depending on the solution of its predecessor. Accelerating the time taken to do this will enable users to investigate more demanding test cases and develop the tools and software needed to demonstrate industrial advantage.
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