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Quantum Entanglement-Based Multi-Agent Distributed Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations
Publisher

Abstract

This paper explores a novel approach to distributed optimization leveraging the unique properties of quantum entanglement. Traditional distributed optimization methods often suffer from communication bottlenecks and reliance on shared information, limiting scalability and efficiency, particularly in scenarios with geographically dispersed agents. This research proposes a framework where agents collaborate to solve complex optimization problems through the utilization of quantum entanglement, effectively creating a "quantum entanglement network". The core idea is to exploit the non-local correlations inherent in entangled states for instantaneous information exchange, bypassing the need for direct communication channels. We detail a communication protocol based on entangled state manipulation and describe how an optimization algorithm can utilize this network to guide local decisions toward a global optimum. The theoretical framework demonstrates the potential for enhanced scalability and efficiency in distributed optimization, representing a significant departure from conventional approaches. The proposed method addresses the inherent limitations of classical communication in complex distributed systems, offering a fundamentally different paradigm for collaborative problem-solving. ---

DOI
10.5281/zenodo.22200334

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