  Current development in programmable analogue quantum simulators (AQS), whose
physical implementation can be realised in the near-term compared to those of
large-scale digital quantum computers, highlights the need for robust testing
techniques in analogue platforms. Methods to properly certify or benchmark AQS
should be efficiently scalable, and also provide a way to deal with errors from
state preparation and measurement (SPAM). Up to now, attempts to address this
combination of requirements have generally relied on model-specific properties.
We put forward a new approach, applying a well-known digital noise
characterisation technique called randomized benchmarking (RB) to the analogue
setting. RB is a scalable experimental technique that provides a measure of the
average error-rate of a gate-set on a quantum hardware, incorporating SPAM
errors. We present the original form of digital RB, the necessary alterations
to translate it to the analogue setting and introduce the analogue randomized
benchmarking protocol (ARB). In ARB we measure the average error-rate per time
evolution of a family of Hamiltonians and we illustrate this protocol with two
case-studies of analogue models; classically simulating the system by
incorporating several physically motivated noise scenarios. We find that for
the noise models tested, the data fit with the theoretical predictions and we
gain values for the average error rate for differing unitary sets. We compare
our protocol with other relevant RB methods, where both advantages (physically
motivated unitaries) and disadvantages (difficulty in reversing the
time-evolution) are discussed.
