  The efficiency of Quantum Characterisation, Verification, and Validation
(QCVV) protocols highly hinges on the agreement between the assumed noise model
and the underlying error mechanisms. As a matter of fact, errors in Quantum
Processing Units (QPUs) incorporate various aspects of context-dependability
which are overlooked by the majority of the commonly used QCVV protocols. As
QCVV protocols are indispensable when it comes to characterizing and evaluating
quantum operations, there is a serious need for a detailed characterization
taking into account such aspects. In this work, we address these shortcomings
by designing a context-aware version of the gate set tomography (GST) protocol.
Our experiment selection approach is based on a polynomial quantification of
the accumulation of errors within the designed circuits. Using simulated QPUs,
we show that this technique enables a characterization with an inaccuracy
reaching $10^{-5}$. Furthermore, we use our proposed protocol to experimentally
infer context-dependent errors, namely crosstalk and memory effects, in a
publicly accessible cloud-based superconducting qubits platform. Our results
show that when the GST is upgraded to include such features of
context-awareness, a large coherence in the errors is observed. These findings
open up possibilities of drastically reducing the errors within the currently
demonstrated QPUs.
