  Mitigation and calibration schemes are central to maximize the computational
reach of today's Noisy Intermediate Scale Quantum (NISQ) hardware, but these
schemes are often specialized to exclusively address either coherent or
decoherent error sources. Quantifying the two types of errors hence constitutes
a desirable feature when it comes to benchmarking error suppression tools. In
this paper, we present a scalable and cycle-centric methodology for obtaining a
detailed estimate of the coherent contribution to the error profile of a hard
computing cycle. The protocol that we suggest is based on Cycle Error
Reconstruction (CER), also known as K-body Noise Reconstruction (KNR). This
protocol is similar to Cycle Benchmarking (CB) in that it provides a
cycle-centric diagnostic based on Pauli fidelity estimation [1]. We introduce
an additional hyper-parameter in CER by allowing the hard cycles to be folded
multiple times before being subject to Pauli twirling. Performing CER for
different values of our added hyper-parameter allows estimating the coherent
error contributions through a generalization of the fidelity decay formula. We
confirm the accuracy of our method through numerical simulations on a quantum
simulator, and perform proof-of-concept experiments on three IBM chips, namely
ibmq_guadalupe, ibmq_manila, and ibmq_montreal. In all three experiments, we
measure substantial coherent errors biased in Z.
