A scalable entanglement distribution framework for hybrid quantum networks
Abstract
The realization of a scalable quantum network (QN) hinges on the efficient distribution of entanglement across heterogeneous hardware platforms. While traditional QN frameworks are often restricted to single-encoding schemes, relying exclusively on either discrete (DV) or continuous (CV) variables, such segregated architectures limit the capacity and interoperability of large-scale systems. Here, we propose a scalable hybrid entanglement distribution scheme that bridges these domains by mapping hybrid entanglement swapping and concentration at DV-CV interfaces onto a unified set of series and parallel graph rules. We demonstrate that our hybrid approach exhibits a potential performance advantage over traditional point-to-point generation of maximally entangled states, achieving enhanced end-to-end entanglement within series-parallel topologies. These results provide a robust theoretical foundation for designing resource-efficient, interpretable architectures for the future quantum internet.
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BibTeX
@misc{zhao2026scalable,
title = {{A scalable entanglement distribution framework for hybrid quantum networks}},
author = {Yaqi Zhao and Kan He and Jinchuan Hou and Yongtao Zhang and Nicolò Lo Piparo and Xiangyi Meng},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.25571},
eprint = {2609.25571},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.25571},
}
RIS
TY - UNPB
TI - A scalable entanglement distribution framework for hybrid quantum networks
AU - Yaqi Zhao
AU - Kan He
AU - Jinchuan Hou
AU - Yongtao Zhang
AU - Nicolò Lo Piparo
AU - Xiangyi Meng
PY - 2026
DA - 2026/09/22
PB - arXiv
DO - 10.48550/arxiv.2609.25571
UR - https://arxiv.org/abs/2609.25571
AB - The realization of a scalable quantum network (QN) hinges on the efficient distribution of entanglement across heterogeneous hardware platforms. While traditional QN frameworks are often restricted to single-encoding schemes, relying exclusively on either discrete (DV) or continuous (CV) variables, such segregated architectures limit the capacity and interoperability of large-scale systems. Here, we propose a scalable hybrid entanglement distribution scheme that bridges these domains by mapping hybrid entanglement swapping and concentration at DV-CV interfaces onto a unified set of series and parallel graph rules. We demonstrate that our hybrid approach exhibits a potential performance advantage over traditional point-to-point generation of maximally entangled states, achieving enhanced end-to-end entanglement within series-parallel topologies. These results provide a robust theoretical foundation for designing resource-efficient, interpretable architectures for the future quantum internet.
ER -