Quantum Entanglement Adaptive Algorithm for Complex System Optimization

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum entanglement presents a unique opportunity for novel optimization algorithms. This paper explores the design of a quantum entanglement-based adaptive algorithm for complex system optimization. We leverage the inherent properties of entanglement to enable global search and adaptive behavior, resulting in enhanced efficiency. The core mechanism centers around utilizing entangled states to guide the search process, enabling a fundamentally different approach to optimization compared to classical algorithms. We present a theoretical framework and preliminary experimental results demonstrating the potential of this algorithm for complex systems.

DOI: 10.5281/zenodo.22609428

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