Multipartite state generation in quantum networks with optimal scaling

TL;DR

This paper presents a scalable quantum network scheme for distributing large multipartite entangled states efficiently, outperforming bipartite methods in storage and performance, applicable to various topologies and graph states.

Contribution

It introduces a novel multipartite repeater scheme based on measurement-based hashing for efficient, scalable entanglement distribution in quantum networks.

Findings

Achieves constant overhead per node regardless of distance

Offers storage advantages over bipartite approaches

Applicable to arbitrary network topologies and graph states

Abstract

We introduce a repeater scheme to efficiently distribute multipartite entangled states in a quantum network with optimal scaling. The scheme allows to generate graph states such as 2D and 3D cluster states of growing size or GHZ states over arbitrary distances, with a constant overhead per node/channel that is independent of the distance. The approach is genuine multipartite, and is based on the measurement-based implementation of multipartite hashing, an entanglement purification protocol that operates on a large ensemble together with local merging/connection of elementary building blocks. We analyze the performance of the scheme in a setting where local or global storage is limited, and compare it to bipartite and hybrid approaches that are based on the distribution of entangled pairs. We find that the multipartite approach offers a storage advantage, which results in higher efficiency and better performance in certain parameter regimes. We generalize our approach to arbitrary network topologies and different target graph states.