Randomized benchmarking of many-qubit devices

Quantum information processors incorporating 5 - 10s of qubits are now commonplace, but the standard method for benchmarking quantum gates - Clifford randomized benchmarking - is infeasible to implement on more than a few qubits in any near-term devices. In this talk, we present a series of modifications to Clifford randomized benchmarking that enable truly holistic benchmarking of entire devices. Importantly, these new techniques are adaptable based on experimental goals. They can be made highly robust or more scalable as needed, and they can be used to estimate, e.g., two-qubit gate error rates or the magnitude of crosstalk errors. Moreover, our methods allow for the benchmarking of universal gates, and continuously parameterized gates. We demonstrate our techniques on current systems, with experimental results on up to 16 qubits.