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CERN & IBM Exploring How Quantum Computing Can Analyze Data Produced on Large Hadron Collider

By IQT News posted 09 Apr 2020

(PhysicsWorld) An international collaboration is exploring how quantum computing could be used to analyse the vast amount of data produced by experiments on the Large Hadron Collider (LHC) at CERN. The researchers have shown that a “quantum support vector machine” can help physicists make sense out of the huge amounts of information generated at CERN.
CERN openlab and IBM started working together on quantum computing in 2018. Now, physicists at the University of Wisconsin led by Sau Lan Wu, CERN, IBM Research in Zurich and Fermilab near Chicago, are looking at how quantum machine learning could be used to identify Higgs boson events in LHC collision data.
The preliminary results of the experiment were very promising. Five quantum bits (qubits) on an IBM quantum computer and quantum simulators were applied to the data. “With our quantum support vector machine, we analysed a small training sample with more than 40 features and five training variables. The results come very close to – and sometimes even better than – the ones obtained using the best known equivalent classical classifiers and were obtained efficiently and in short time,” says Panagiotis Barkoutsos of IBM Research.

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Pasqal has partnered with Mila to further probe the intersections between quantum computing and generative AI.