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.
Work with Rafael N. Alexander and Stephen D. Bartlett.