  Quantum utility has been severely limited in superconducting quantum hardware
until now by the modest number of qubits and the relatively high level of
control and readout errors, due to the intentional coupling with the external
environment required for manipulation and readout of the qubit states.
Practical applications in the Noisy Intermediate Scale Quantum (NISQ) era rely
on Quantum Error Mitigation (QEM) techniques, which are able to improve the
accuracy of the expectation values of quantum observables by implementing
classical post-processing analysis from an ensemble of repeated noisy quantum
circuit runs. In this work, we focus on a recent QEM technique that uses Fuzzy
C-Means (FCM) clustering to specifically identify measurement error patterns.
For the first time, we report a proof-of-principle validation of the technique
on a 2-qubit register, obtained as a subset of a real NISQ 5-qubit
superconducting quantum processor based on transmon qubits. We demonstrate that
the FCM-based QEM technique allows for reasonable improvement of the
expectation values of single- and two-qubit gates based quantum circuits,
without necessarily invoking state-of-the-art coherence, gate, and readout
fidelities.
