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Mitigation and calibration schemes are central to maximize the computationalreach of today's Noisy Intermediate Scale Quantum (NISQ) hardware, but theseschemes are often specialized to exclusively address either coherent ordecoherent error sources. Quantifying the two types of errors hence constitutesa desirable feature when it comes to benchmarking error suppression tools. Inthis paper, we present a scalable and cycle-centric methodology for obtaining adetailed estimate of the coherent contribution to the error profile of a hardcomputing cycle. The protocol that we suggest is based on Cycle ErrorReconstruction (CER), also known as K-body Noise Reconstruction (KNR). Thisprotocol is similar to Cycle Benchmarking (CB) in that it provides acycle-centric diagnostic based on Pauli fidelity estimation [1]. We introducean additional hyper-parameter in CER by allowing the hard cycles to be foldedmultiple times before being subject to Pauli twirling. Performing CER fordifferent values of our added hyper-parameter allows estimating the coherenterror contributions through a generalization of the fidelity decay formula. Weconfirm the accuracy of our method through numerical simulations on a quantumsimulator, and perform proof-of-concept experiments on three IBM chips, namelyibmq_guadalupe, ibmq_manila, and ibmq_montreal. In all three experiments, wemeasure substantial coherent errors biased in Z.

Estimating Coherent Contributions to the Error Profile Using Cycle Error Reconstruction