Quantum Entanglement-Based Distributed Neural Network Synchronization

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper explores a novel approach to neural network synchronization leveraging the phenomenon of quantum entanglement. We propose a distributed neural network architecture where synchronization is achieved instantaneously through entanglement, bypassing the limitations imposed by the speed of light and the inherent delays in conventional neural network communication. The core concept involves integrating quantum processors and classical processors within each neuron. Quantum processors, utilizing entangled states, provide real-time synchronization of other neurons, while classical processors manage classical information exchange and feedback. The proposed method represents a significant departure from existing synchronization techniques, which rely on finite-speed signal transmission. This research has the potential to revolutionize both biological and computational neural networks by enabling truly instantaneous synchronization. We present a detailed theoretical framework and explore the key components of this system, focusing on the operational mechanisms and potential challenges. The ultimate goal is to demonstrate a viable pathway for constructing a synchronized distributed neural network based on the fundamental principles of quantum mechanics.

DOI: 10.5281/zenodo.22270919

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