Efficient experimental verification of continuously-parameterized quantum gates via randomized analog verification

Near-term quantum computers implement circuits directly using the physical native gate set of the device. These gates often have a parameterization (e.g., rotation angles) which enables a continuous range of operations. Verification of the correct operation of these gates across the allowable range of parameters is important for gaining confidence in the reliability of these devices. In this work, we demonstrate the application of the randomized analog verification (RAV) procedure for efficient verification of continuously-parameterized quantum gates. This procedure involves generating random sequences of randomly-parameterized layers of gates chosen from the native gate set of the device, and then stochastically compiling an approximate inverse to this sequence such that executing the full sequence on the device should leave the system near its initial state. We show that fidelity estimates made via RAV have a lower variance than fidelity estimates made via cross-entropy benchmarking (XEB), which thus provides an efficiency advantage when estimating the error rate to some desired precision.