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The efficiency of Quantum Characterisation, Verification, and Validation(QCVV) protocols highly hinges on the agreement between the assumed noise modeland the underlying error mechanisms. As a matter of fact, errors in QuantumProcessing Units (QPUs) incorporate various aspects of context-dependabilitywhich are overlooked by the majority of the commonly used QCVV protocols. AsQCVV protocols are indispensable when it comes to characterizing and evaluatingquantum operations, there is a serious need for a detailed characterizationtaking into account such aspects. In this work, we address these shortcomingsby designing a context-aware version of the gate set tomography (GST) protocol.Our experiment selection approach is based on a polynomial quantification ofthe accumulation of errors within the designed circuits. Using simulated QPUs,we show that this technique enables a characterization with an inaccuracyreaching $10^{-5}$. Furthermore, we use our proposed protocol to experimentallyinfer context-dependent errors, namely crosstalk and memory effects, in apublicly accessible cloud-based superconducting qubits platform. Our resultsshow that when the GST is upgraded to include such features ofcontext-awareness, a large coherence in the errors is observed. These findingsopen up possibilities of drastically reducing the errors within the currentlydemonstrated QPUs.

A context-aware gate set tomography characterization of superconducting qubits