Enhancing-Quantum-Error-Correction-Decoders-A-Graph-Based-Approach-on-FPGA

This research project aims to enhance Quantum Error Correction (QEC) decoders by integrating advanced graph-based algorithms on FPGA, addressing challenges like scalability and real-time adaptability. It focuses on using dynamic graph algorithms, matching and flow techniques, and reinforcement learning to improve error correction in stabilizer codes. The project will develop an FPGA-based prototype, demonstrating efficiency and adaptability in quantum computing scenarios. Expected outcomes include a novel, scalable QEC decoder and FPGA implementation showcasing improved performance and contributions to QEC methodologies, fostering progress toward reliable quantum computing.