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    Scalable and Modular Generation of W-State Entanglements via Memory-Enhanced Fusion

    Jixuan Shi1,*, Sheng Zhang1,*, Yukai Wu1,2,*, Yuedong Sun1, Yibo Liang1, Hai Wang3,4,†, Yunfei Pu1,2,‡, and Luming Duan1,2,§

    • 1Center for Quantum Information, IIIS, Tsinghua University, Beijing 100084, People’s Republic of China
    • 2Hefei National Laboratory, Hefei 230088, People’s Republic of China
    • 3The State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Opto-Electronics, Shanxi University, Taiyuan 030006, China
    • 4Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China

    • *These authors contributed equally to this work.
    • †Contact author: wanghai@sxu.edu.cn
    • ‡Contact author: puyf@tsinghua.edu.cn
    • §Contact author: lmduan@tsinghua.edu.cn

    Phys. Rev. Lett. 135, 150802 – Published 7 October, 2025

    DOI: https://doi.org/10.1103/w4w4-lf6r

    Abstract

    Efficient generation of large-scale multipartite entangled states is a critical but challenging task in quantum information processing. Although generation of multipartite entanglement within a small set of individual qubits has been demonstrated, further scale-up in system size requires the connection of smaller entangled states into a larger state in a scalable and modular manner. Here, we achieve this goal by implementing memory-enhanced fusion of two multipartite entangled states via photonic interconnects. Through asynchronous preparation of two tripartite W-state entanglements in two spatially separated modules of atomic quantum memories and on-demand fusion via single-photon interference, we demonstrate the creation of a four-partite W-state entanglement shared by two remote quantum memory modules in a heralded way. We also demonstrate memory-enhanced scaling in efficiencies in the entanglement fusion. The demonstrated scalable generation and fusion of multipartite entangled states pave the way toward realization of large-scale distributed quantum information processing in the future.

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