Packet-switching quantum key distribution

    公开(公告)号:US12238208B2

    公开(公告)日:2025-02-25

    申请号:US18175807

    申请日:2023-02-28

    Abstract: A network element in a quantum network receives a hybrid frame including a classical header and a quantum payload. The network element processes the classical header for a length of time and generates a new classical header. The network element drops a portion of the quantum payload based on the length of time spent processing the classical header and updates the hybrid frame to include the new classical header and the quantum payload without the dropped portion.

    PACKET-SWITCHING QUANTUM KEY DISTRIBUTION
    2.
    发明公开

    公开(公告)号:US20240291641A1

    公开(公告)日:2024-08-29

    申请号:US18175807

    申请日:2023-02-28

    CPC classification number: H04L9/0855 H04L9/0858

    Abstract: A network element in a quantum network receives a hybrid frame including a classical header and a quantum payload. The network element processes the classical header for a length of time and generates a new classical header. The network element drops a portion of the quantum payload based on the length of time spent processing the classical header and updates the hybrid frame to include the new classical header and the quantum payload without the dropped portion.

    CHANNEL CODING OVER QUANTUM CHANNELS

    公开(公告)号:US20250096906A1

    公开(公告)日:2025-03-20

    申请号:US18466889

    申请日:2023-09-14

    Abstract: A method of managing communication over a quantum channel. The method includes generating a first set of quantum channel codes configured to encode a message to obtain a quantum encoded message, supplying the first set of quantum channel codes to an encoder, generating a second set of quantum channel codes configured to decode the quantum encoded message, and supplying the second set of quantum channel codes to a decoder that is configured to operate with encoder across a channel, wherein the first set of quantum channel codes and the second set of quantum channel codes are derived using a machine learning model.

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