MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202621077125 A) filed by Kavita Sanjay Singh; Dr. G. Rohini; Dr. Manish Kumar; Pradheeba P; Dr. Priya Paneru; and Dr. Vidhi Goyal on June 22, 2026, for Machine Learning Optimized Quantum Network Routing For Dynamic Link Stabilization.
Inventors include Kavita Sanjay Singh; Dr. G. Rohini; Dr. Manish Kumar; Pradheeba P; Dr. Priya Paneru; and Dr. Vidhi Goyal.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: The present invention discloses a machine learning optimized quantum network routing system for dynamic link stabilization in quantum communication networks. The system is designed to enhance the reliability and efficiency of quantum data transmission by intelligently selecting and adapting communication paths based on real- time network conditions. The invention continuously monitors critical quantum link parameters such as entanglement fidelity, photon loss rate, quantum bit error rate (QBER), and channel noise characteristics. These parameters are analyzed using a machine learning-based routing engine, which predicts link stability and determines optimal routing paths across quantum nodes. The system employs advanced machine learning techniques, including reinforcement learning and graph-based neural networks, to dynamically assign weights to network links and select the most reliable communication routes. In the event of link degradation, the system performs automatic rerouting to ensure uninterrupted quantum communication and improved entanglement distribution. A feedback-driven learning mechanism enables continuous model improvement based on actual network performance, allowing the system to adapt to changing environmental and operational conditions. The proposed invention significantly enhances transmission fidelity, reduces quantum information loss, and improves the scalability and robustness of quantum communication networks.
Disclaimer: Curated by HT Syndication.
