Quantum Entanglement Accelerated Distributed Inference

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper proposes a novel approach to distributed inference leveraging the unique properties of quantum entanglement. The core concept involves constructing a quantum entanglement network where nodes are interconnected through entangled states. This allows for the parallel execution of independent inference steps, directly addressing the limitations imposed by classical communication bottlenecks. We demonstrate that by exploiting the instantaneous correlation inherent in entanglement, the system can achieve inference speeds significantly exceeding those attainable through traditional distributed computing methods. The theoretical framework outlines the key components of this architecture, including entanglement generation, distribution, and measurement protocols. We present a mathematical model describing the system's performance, highlighting the potential for accelerating complex probabilistic models. The primary focus is on the theoretical advancement, with no experimental validation presented. The system's efficiency is directly tied to the quality and number of entangled pairs utilized. Further research will explore practical implementations and scalability challenges.

DOI: 10.5281/zenodo.22334363

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