Quantum computers are beginning to provide real-world solutions to business challenges, A collaboration between a quantum pioneer and one of Europe’s largest independent energy companies offers one of the earliest applications of quantum machine learning to the energy sector – an important step forward in the utility of today’s Noisy Intermediate Scale Quantum (“NISQ”) processors.
Cambridge Quantum Computing (“CQC”) announced the results of their work with energy giant Aker BP in a company statement.
According to the statement, the collaboration between Oslo based, Aker BP and CQC saw the design and demonstration of a cutting-edge quantum machine learning (“QML”) algorithm to tackle a multiphase flow classification problem.
The team’s solution consisted of an instantaneous quantum polynomial-time circuit trained as a three-class classifier, implemented on an IBM quantum processor using CQC’s quantum software development platform – t|ket⟩TM. Tested on Aker BP data, the QML classifier only required a handful of qubits to match the performance of a classical Support Vector Machine (“SVM”) with nonlinear kernels.
Mattia Fiorentini, Head of Quantum Machine Learning at CQC said, “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.”
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