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Rolls-Royce, Riverlane partner on materials simulation project (QuaMaD)

By Dan O'Shea posted 19 Dec 2023

British aerospace firm Rolls-Royce, among the earliest commercial users of quantum technology, is now partnering with fellow U.K. company Riverlane on a new chemistry project–a first for Rolls-Royce–aimed at creating better tools to simulate large, complex materials on quantum computers. 

The Quantum Accelerator for Materials Design (QuaMaD) project, which also involves England’s National Quantum Computing Centre and is funded by Innovate UK, will leverage existing Riverlane algorithms to work on reducing the number of qubits required for such materials simulations. 

Riverlane also will have much to gain from the results of the project, as tools and knowledge developed during the project will be integrated into Riverlane’s Deltaflow Quantum Error Correction Stack for quantum computers. 

Earl Campbell, VP Quantum Science at Riverlane, said the QuaMaD project addresses the challenges posed by trying to simulate new materials on classical computers. “It will allow materials design experts to benefit sooner from quantum computers and brings together industry experts in the NQCC and Rolls-Royce, who will help us gain deep insights into use cases valuable for the materials industry,” he said

Leigh Lapworth, Rolls-Royce Fellow in Computational Science, added “With internal air temperatures reaching 2000oC, beyond the melting point of the materials we use, jet engines are a hostile environment for its components. Our current state-of-the-art materials have taken many years to develop, and we continually seek improvements in their properties to deliver more efficient engines.” 

Rolls-Royce was among the earliest commercial firms to start experimenting with quantum computing, and in the past has worked with Nvidia and Classiq on projects.

Dan O’Shea has covered telecommunications and related topics including semiconductors, sensors, retail systems, digital payments and quantum computing/technology for over 25 years.

Categories: quantum computing

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