Quantum Volume for Photonic Quantum Processors

TL;DR

This paper develops a framework to adapt quantum volume and other metrics for measurement-based photonic quantum processors, specifically analyzing GKP-encoded continuous-variable cluster states to evaluate their performance.

Contribution

It introduces a method to map physical noise in MBQC to logical errors, enabling the use of existing quantum metrics for photonic quantum computing.

Findings

Derived logical gate error channels for GKP-encoded states

Calculated quantum volume based on squeezing and photon loss

Provided a framework applicable to near-term photonic quantum devices

Abstract

Defining metrics for near-term quantum computing processors has been an integral part of the quantum hardware research and development efforts. Such quantitative characteristics are not only useful for reporting the progress and comparing different quantum platforms, but also essential for identifying the bottlenecks and designing a technology roadmap. Most metrics such as randomized benchmarking and quantum volume were originally introduced for circuit-based quantum computers and were not immediately applicable to measurement-based quantum computing (MBQC) processors such as in photonic devices. In this paper, we close this gap by presenting a framework to map physical noises and imperfections in MBQC processes to logical errors in equivalent quantum circuits, whereby enabling the well-known metrics to characterize MBQC. To showcase our framework, we study a continuous-variable cluster state based on the Gottesman-Kitaev-Preskill (GKP) encoding as a near-term candidate for photonic quantum computing, and derive the effective logical gate error channels and calculate the quantum volume in terms of the GKP squeezing and photon loss rate.