Quantum Bayesian Inference for Complex Control Systems

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum Bayesian Inference (QBI) offers a promising avenue for enhancing complex control systems, particularly in the face of noisy environments. This paper explores the application of QBI to estimate the system's state and plan actions, leveraging Bayesian inference to mitigate uncertainty and improve robustness. We propose a novel quantum-inspired Bayesian estimation scheme designed to reduce uncertainty and provide enhanced control capabilities. The core mechanism focuses on utilizing quantum-like principles to refine system state estimation, thereby improving overall system performance. This research addresses the limitations of classical Bayesian methods by introducing a fundamentally more efficient approach.

DOI: 10.5281/zenodo.22481982

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