Riverlane joins £7.5 million consortium to build error corrected quantum processor
- Date written
- 22 Dec, 2021
- Read time
- 2 minutes
Riverlane is the lead software partner in a consortium that has been awarded £7.5 million to build an error corrected quantum processor, working with a range of UK partners, including Rolls Royce, to apply this toward new applications in the aerospace industry. The funding comes via the UK government’s National Quantum Technologies Programme.
The project, led by quantum computer manufacturer Universal Quantum, will call on Riverlane’s software and expertise to tackle quantum error correction on a trapped-ion quantum computer. Error correction is a crucial step in unlocking the promise of ‘fault tolerant’ quantum computers capable of a range of transformative applications, and is at the core of everything Riverlane does.
The work with Rolls Royce will explore how quantum computers can develop practical applications toward the development of more sustainable and efficient jet engines.
This starts by applying quantum algorithms to take steps to toward a greater understanding of how liquids and gases flow, a field known as ‘fluid dynamics’. Simulating such flows accurately is beyond the computational capacity of even the most powerful classical computers today.
The consortium also includes: academic researchers from Imperial College London and the University of Sussex; the Science and Technology Facilities Council (STFC) Hartree Centre; supply chain partners Edwards, TMD Technologies and Diamond Microwave; and commercialisation and dissemination experts Sia Partners and Qureca.
Fluids behave according to a famous set of partial differential equations called the Navier-Stokes equations, the solutions to which are important for aircraft and engine design, as well as understanding ocean currents and predicting the weather. Classical computers can take months or even years to solve some types of these equations, but recent research has shown that quantum computers could find the solutions much more quickly.