Contextual Characterization of the Cross-Resonance Gate on a Multi-Qubit Superconducting Quantum Processor*

The performance of algorithms on quantum processors is determined by the error rates of the single- and two-qubit gates composing the algorithm. However, in multi-qubit processors, the presence of both intrinsic and control-induced crosstalk limits the efficacy of traditional gate error metrics for determining algorithmic performance. Determining the nature of and reducing the errors that occur on spectator qubits when gates are applied is essential. In this work, we use contextual benchmarks to characterize the performance of cross-resonance gates in a superconducting quantum processor. We describe an iterative method where we determine specific errors on a multi-qubit processor due to cycles containing cross-resonance gates, and account for those errors using virtual gates and dynamical decoupling. Finally, we explore the utilization of the cross-resonance effect for multi-qubit gates.