Quantum Entanglement-Driven Distributed Computing Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper proposes a novel approach to distributed computing optimization leveraging the principles of quantum entanglement. The core claim is that entanglement can facilitate instantaneous information transfer and coordinated optimization across distributed computing nodes, drastically improving the efficiency of complex computations. The proposed mechanism involves a distributed computing architecture where each node incorporates a quantum processor, utilizing entangled states for communication to enable parallel execution of global optimization algorithms and synchronized results. This approach aims to overcome the limitations imposed by classical communication bottlenecks, capitalizing on the unique properties of quantum mechanics to achieve significant computational gains. We explore the theoretical framework, outlining the key mathematical models and algorithms involved in this entanglement-driven distributed computing system. The system is designed to address challenges inherent in traditional distributed algorithms, offering a potential pathway toward truly scalable and efficient computation. The presented model focuses on the core principles and provides a foundation for future research and development within this emerging field.

DOI: 10.5281/zenodo.22188288

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