In this unique case study, we compare four variational quantum heuristics that can optimize a manufacturing process used by Japan’s Nippon Steel Corporation.
Results from running those algorithms on IBM quantum hardware show that CQ’s recent filtering variational quantum eigensolver (F-VQE) converges faster and samples the global optimum more frequently than the other algorithms, including the quantum approximate optimization algorithm (QAOA). In our experiments, F-VQE readily solved problem sizes using up to 23 qubits thus confirming that F-VQE can accelerate the pace at which current quantum hardware can solve optimization problems of industrial scale.
David Amaro, Matthias Rosenkranz, Nathan Fitzpatrick, Koji Hirano, Mattia Fiorentini
Founded in 2014, CQC is a global leader in quantum software and quantum algorithms that help our clients get the best out of existing and developing quantum computers. Over the past several years, our team has grown to 70 + accomplished scientists focused on creating the best quantum software and enabling systems in the world.
Our technologies help the world’s most innovative chemical, energy, financial and material science companies to harness the transformative impact of quantum computing.
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