A complete continuous-variable quantum computation architecture based on the 2D spatiotemporal cluster state

TL;DR

This paper proposes a comprehensive, scalable architecture for continuous-variable quantum computation using a 2D spatiotemporal cluster state, incorporating state generation, gate implementation, error correction, and fault tolerance.

Contribution

It introduces a novel scheme for generating large-scale 2D continuous-variable cluster states via multiplexing in space and time, enabling complete fault-tolerant quantum computation.

Findings

Schematic for large-scale 2D cluster state generation

Implementation of gate teleportation with noise considerations

Fault-tolerance achieved with 12.3 dB squeezing threshold

Abstract

Continuous-variable measurement-based quantum computation, which requires deterministically generated large-scale cluster state, is a promising candidate for practical, scalable, universal, and fault-tolerant quantum computation. In this work, based on our compact and scalable scheme of generating a two-dimensional spatiotemporal cluster state, a complete architecture including cluster state preparation, gate implementations, and error correction, is proposed. First, a scheme for generating two-dimensional large-scale continuous-variable cluster state by multiplexing both the temporal and spatial domains is proposed. Then, the corresponding gate implementations by gate teleportation are discussed and the actual gate noise from the generated cluster state is considered. After that, the quantum error correction can be further achieved by utilizing the square-lattice Gottesman-Kitaev-Preskill (GKP) code. Finally, a fault-tolerant quantum computation can be realized by introducing bias into the square-lattice GKP code (to protect against phase-flip errors) and concatenating a repetition code (to handle the residual bit-flip errors), with a squeezing threshold of 12.3 dB. Our work provides a possible option for a complete fault-tolerant quantum computation architecture in the future.