Randomized benchmarking in measurement-based quantum computing

TL;DR

This paper adapts randomized benchmarking protocols to measurement-based quantum computing, enabling efficient noise characterization of quantum gates in the measurement-based model using Clifford and non-Clifford 2-designs.

Contribution

It introduces a method to perform randomized benchmarking within measurement-based quantum computation, utilizing both Clifford and non-Clifford 2-designs for noise analysis.

Findings

Effective benchmarking of measurement-based quantum gates demonstrated.

Comparison between Clifford and non-Clifford 2-designs shows different noise insights.

The approach reveals the interplay of inherent randomness and benchmarking sequences.

Abstract

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.