Using a $1 million federal grant, Yale and the University of Connecticut will develop a proposal for a national “engine” for quantum technology and jobs.
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Quantum computing continues to advance at a rapid pace, but one challenge that holds the field back is mitigating the noise that plagues quantum machines.
A new technique identifies parameterized quantum circuits that are more robust to noise. The work could improve the accuracy of quantum machine learning and quantum chemistry tasks, while using less computational resources in the circuit design process.