  Randomized benchmarking is routinely used as an efficient method for
characterizing the performance of sets of elementary logic gates in small
quantum devices. In the measurement-based model of quantum computation, logic
gates are implemented via single-site measurements on a fixed universal
resource state. Here we adapt the randomized benchmarking protocol for a single
qubit to a linear cluster state computation, which provides partial, yet
efficient characterization of the noise associated with the target gate set.
Applying randomized benchmarking to measurement-based quantum computation
exhibits an interesting interplay between the inherent randomness associated
with logic gates in the measurement-based model and the random gate sequences
used in benchmarking. We consider two different approaches: the first makes use
of the standard single-qubit Clifford group, while the second uses recently
introduced (non-Clifford) measurement-based 2-designs, which harness inherent
randomness to implement gate sequences.
