MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202641093545 A) filed by Mrs. N. Kavitha; Mr. Madhava Rao Karri; Dr. Pragati Deogharka; Mr. Ashis Datta; Dr. R. Raja Sudharsan; and Dr. Jami Venkata Suman on August 01, 2026, for Ai-Driven Adaptive Quantum Hardware Optimization And Resource Management System Using Intelligent Multi-Layer Learning Models.
Inventors include Mrs. N. Kavitha; Mr. Madhava Rao Karri; Dr. Pragati Deogharka; Mr. Ashis Datta; Dr. R. Raja Sudharsan; and Dr. Jami Venkata Suman.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: The present invention relates to an AI-driven adaptive quantum hardware optimization and resource management system for intelligent optimization of quantum computing hardware. The system acquires operational telemetry from quantum processors, preprocesses heterogeneous hardware information, and employs hybrid artificial intelligence models including deep learning, reinforcement learning, Bayesian optimization, graph neural networks, and predictive analytics to estimate future hardware behavior and generate adaptive optimization strategies. A digital twin simulation framework validates optimization decisions prior to deployment on physical hardware. An intelligent controller dynamically adjusts calibration parameters, microwave pulse characteristics, cooling resources, workload scheduling, gate execution, and qubit allocation while continuously learning from hardware feedback. The invention improves qubit fidelity, coherence time, computational accuracy, energy efficiency, hardware reliability, predictive maintenance capability, and long-term scalability of quantum computing infrastructure. Accompanied Drawing [FIGS. 1-2]
Disclaimer: Curated by HT Syndication.
