Scalable Randomized Benchmarking of Quantum Computers Using Mirror Circuits

The performance of quantum gates is often assessed using some form of randomized benchmarking. However, the existing methods become infeasible for more than approximately five qubits. Here we show how to use a simple and customizable class of circuits-randomized mirror circuits-to perform scalable, robust, and flexible randomized benchmarking of Clifford gates. We show that this technique approximately estimates the infidelity of an average many-qubit logic layer, and we use simulations of up to 225 qubits with physically realistic error rates in the range 0.1%-1% to demonstrate its scalability. We then use up to 16 physical qubits of a cloud quantum computing platform to demonstrate that our technique can reveal and quantify crosstalk errors in many-qubit circuits.

Automated summary

In this study, a simple and customizable class of circuits called randomized mirror circuits is shown to enable scalable, robust, and flexible randomized benchmarking of Clifford gates. Through simulations and experiments, the feasibility and scalability of the technique are demonstrated, and its capability of detecting and quantifying crosstalk errors in many-qubit circuits is validated.