Quantum Entanglement Dynamic Network Adjustment

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper explores the application of quantum entanglement to dynamically adjust network connection strengths. Traditional network optimization techniques often rely on manual configuration and iterative adjustment, which can be time-consuming and suboptimal. We propose a novel algorithm, Quantum Entanglement Dynamic Network Adjustment (QEDNA), that leverages the unique properties of quantum entanglement to automatically optimize network connectivity. The core mechanism involves establishing entangled pairs between network nodes, allowing for a real-time assessment of network state and subsequent adjustment of connection strengths. This adaptation process minimizes latency and maximizes throughput, ultimately leading to enhanced communication performance. The paper details the algorithm's architecture, demonstrates its effectiveness through simulation and preliminary experimental validation, and discusses future research directions.

DOI: 10.5281/zenodo.22264701

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