Abstract
We demonstrate a procedure to diagnose where gate faults occur in a circuit by using a hybridized quantum-and-classical machine-learning technique, using a diagnostic circuit and selected inputs. We numerically demonstrate an accuracy of over 90%.
© 2020 The Author(s)
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