Cambridge Quantum Computing (CQC) has recently announced its results after collaborating with Aker BP, one of the largest European independent companies.
Based in Oslo, Aker BP and CQC worked together on a sophisticated Quantum Machine Learning algorithm. The algorithm was designed to tackle a multiphase flow classification problem. The team used an instantaneous quantum polynomial-time circuit trained as a three-class classifier to solve the problem. Installed on an IBM quantum processor and using CQC’s t|ket⟩™ quantum software development platform, the scientists got to work. The classifier was tested on Aker BP-provided data and only a few qubits were required to match a classical Support Vector Machine with nonlinear kernels’ performance.
These results are proof that quantum machine learning is practical in the energy sector, especially when Noisy Intermediate Scale Quantum (NISQ) processors are involved.
‘We are pleased by the nature and results of our collaboration with Aker BP, demonstrating the early application of NISQ solutions to the energy sector. As both hardware and software continue to show significant developments, the impact of quantum technologies on many industry verticals is becoming increasingly clear.’
Dr Mattia Fiorentini, Head of Quantum Machine Learning at CQC
About Cambridge Quantum Computing
CQC was founded in 2014 and today is established as a global leader in quantum software and quantum algorithms. These products are designed to allow clients to use the most our of their powerful hardware. The company has offices in the UK, USA, and Japan.
About Aker BP
Aker BP is an exploration and production company based near Oslo at Fornebu. It is primarily active on the Norwegian Continental Shelf, and it is one of the largest independent oil companies in Europe based on production output. The company has offices in Stavanger, Trondheim, Harstad and Sandnessjøen.
