Multipartite Entanglement for Multi-node Quantum Networks

TL;DR

This paper reviews methods for creating multipartite entanglement in quantum networks, emphasizing single-step schemes that overcome limitations of bipartite-based approaches for scalable quantum communication and computation.

Contribution

It analyzes various single-step multipartite entanglement schemes, comparing their effectiveness and applicability across different quantum network platforms.

Findings

Single-step schemes can generate multipartite entanglement more efficiently.

Different schemes produce states with varying fidelity and rates.

Applicability varies across experimental platforms.

Abstract

Scaling the number of entangled nodes in a quantum network is a challenge with significant implications for quantum computing, clock synchronisation, secure communications, and quantum sensing. In a quantum network, photons interact with matter qubits at different nodes, flexibly enabling the creation of remote entanglement between them. Multipartite entanglement among multiple nodes will be crucial for many proposed quantum network applications, including quantum computational tasks and quantum metrology. To date, experimental efforts have primarily focused on generating bipartite entanglement between nodes, which is widely regarded as the fundamental quantum resource for quantum networks. However, relying exclusively on bipartite entanglement to form more complex multipartite entanglement introduces several challenges. These include the need for ancillary qubits, extensive local entangling operations which increases the preparation latency, and increasingly stringent requirements on coherence times as the number of nodes grows. Here, we analyse various schemes that achieve multipartite entanglement between nodes in a single step, bypassing the need for multiple rounds of bipartite entanglement. We demonstrate that different schemes can produce distinct multipartite entangled states, with varying fidelity and generation rates. Additionally, we discuss the applicability of these schemes across different experimental platforms, highlighting their primary advantages and disadvantages.