Artificial Intelligence Defined Quantum Networks

CATALOG

    Objectives

    1. Leverage existing network infrastructure for building Quantum networks
    2. Bring controllability into quantum network hardware.
    3. Detect corrupted Photons in fiber networks and quantum memory
    4. Protect quantum networks from intrusion/interception
    5. Improve network resource utilization
    6. Improve the quality of quantum entanglement

    Design Software Defined Quantum Networks from SDN (ONOS)

    Software Defined Network (SDN)

    Software-defined networking technology is an approach to network management that enables dynamic, programmatically efficient network configuration in order to improve network performance and monitoring. SDN is meant to address the fact that the static architecture of traditional networks is decentralized and complex while current networks require more flexibility and easy troubleshooting. SDN attempts to centralize network intelligence in one network component by disassociating the forwarding process of network packets (data plane) from the routing process (control plane). The control plane consists of one or more controllers, which are considered the brain of the SDN network where the whole intelligence is incorporated.

    ONOS

    The Open Network Operating System (ONOS) project is an open source community hosted by The Linux Foundation. The goal of the project is to create a software-defined networking (SDN) operating system for communications service providers that is designed for scalability, high performance and high availability.

    Artificial Intelligence Defined Quantum Networks

    AI for Managing and Controlling Networks and automation

    Challenge: complex operations in quantum networks

    • Reduce human-in-the-loop。
    • Deep Reinforcement Learning in managing network infrastructure.
    • Reduce the steep learning curve in network administration knowledge and expertise.
    • Work in Real-time to setup and manage end-to-end quantum networks for entanglement distributions.
    • Enhance robustness in a dynamic environment with network interruptions, and automatically move affected traffic to alternative resources.
    • Introduce different rewards in AI-based optimization strategy and adapt to different environments, including long-term Quantum memory and short-term Quantum memory.

    Pattern Recognition In Detecting Photon Propagation and Storage Errors

    Challenge: High percentage Photon Failure Rate in Entanglement Establishment

    • Identify the optical signatures of photon entanglement and predict Photon Failures and Bell state measurement (BSM).
    • Proactively Introduce mitigation strategy (resending entanglement pairs, modifying the duty cycles of photon sources).
    • Decision making in timing and controlling Bell statement measurement to enhance the success rate.

    References

    1. https://en.wikipedia.org/wiki/Software-defined_networking
    2. https://wiki.onosproject.org/display/ONOS/The+Network+Configuration+Service