English

Entanglement Superactivation in Multiphoton Distillation Networks

Quantum Physics 2025-10-31 v1

Abstract

In quantum networks, after passing through noisy channels or information processing, residual states may lack sufficient entanglement for further tasks, yet they may retain hidden quantum resources that can be recycled. Efficiently recycling these states to extract entanglement resources such as genuine multipartite entanglement or Einstein-Podolsky-Rosen pairs is essential for optimizing network performance. Here, we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform, demonstrating entanglement superactivation phenomena which are unique to multipartite systems. We successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication, demonstrating superactivation of genuine multipartite entanglement. Furthermore, we extend our scheme to generate a three-photon state capable of extracting an Einstein-Podolsky-Rosen pair from two initial states lacking this capability, revealing a previously unobserved entanglement superactivation phenomenon. Our methods and findings offer not only practical applications for quantum networks, but also lead to a deeper understanding of multipartite entanglement structures.

Keywords

Cite

@article{arxiv.2510.26290,
  title  = {Entanglement Superactivation in Multiphoton Distillation Networks},
  author = {Rui Zhang and Yue-Yang Fei and Zhenhuan Liu and Xingjian Zhang and Xu-Fei Yin and Yingqiu Mao and Li Li and Nai-Le Liu and Otfried Gühne and Xiongfeng Ma and Yu-Ao Chen and Jian-Wei Pan},
  journal= {arXiv preprint arXiv:2510.26290},
  year   = {2025}
}

Comments

23 pages, 10 figures. A previous version of this manuscript was made publicly available via the Research Square platform under the URL: https://assets-eu.researchsquare.com/files/rs-3828402/v1_covered_578311cc-7b26-4ccb-87b6-c01421c44e0f.pdf. This arXiv submission constitutes the latest version

R2 v1 2026-07-01T07:13:29.460Z