Abstract: The present invention relates to a quantum computing system incorporating an advanced neural network for predictive error correction and system optimization. The neural network utilizes machine learning techniques, including deep learning and reinforcement learning, to analyze real-time data from a monitoring system comprising photonic sensors. The system dynamically adjusts high-frequency laser parameters and cryogenic cooling to maintain qubit coherence and prevent decoherence events. The neural network also integrates predictive models based on historical data and time-series analysis, enabling preemptive correction of potential errors during quantum operations. By refining its predictive capabilities and control over quantum operations, the system enhances computational accuracy and operational stability, making it particularly suitable for high-precision quantum applications.