  Distilling precise estimates from noisy intermediate scale quantum (NISQ)
data has recently attracted considerable attention. In order to augment digital
qubit metrics, such as gate fidelity, we discuss analog error mitigability,
i.e. the ability to accurately distill precise observable estimates, as a
hybrid quantum-classical computing benchmarking task. Specifically, we
characterize single qubit error rates on IBM's Poughkeepsie superconducting
quantum hardware, incorporate control-mediated noise dependence into a
generalized rescaling protocol, and analyze how noise characteristics influence
Richardson extrapolation-based error mitigation. Our results identify regions
in the space of Hamiltonian control fields and circuit-depth which are most
amenable to reliable noise extrapolation, as well as shedding light on how
low-level hardware characterization can be used as a predictive tool for
uncertainty quantification in error mitigated NISQ computations.
