Quantum Entanglement Information Search Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel information search algorithm leveraging quantum entanglement to enhance data discovery in large datasets. Traditional search methods often struggle with the complexity of identifying subtle correlations, limiting their effectiveness in scenarios with substantial data volumes. We propose a quantum-inspired approach that exploits the unique properties of quantum entanglement to establish a dynamic, probabilistic search framework. The core mechanism involves constructing a 'entanglement-aware' search space, enabling rapid pattern identification and improved matching efficiency. This algorithm is designed to outperform classical search techniques by focusing on higher-dimensional correlations and minimizing the computational cost associated with exhaustive search. The paper details the algorithm's design, analysis of its performance, and potential applications in data analysis and pattern recognition. The focus is on demonstrating the practical benefits of quantum entanglement in a search context, specifically addressing challenges related to scale and speed.

DOI: 10.5281/zenodo.22201505

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