Title: Algorithmic Quantum Entanglement Mapping

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, presents a significant challenge in harnessing its potential for complex systems. Accurate and efficient mapping and analysis of entanglement patterns are crucial for progress in quantum information processing and quantum computing. This paper introduces Algorithmic Quantum Entanglement Mapping (AQEM), a novel algorithm designed to dramatically improve the efficiency of this task. AQEM leverages the dynamic updating of a quantum state map guided by entanglement gradients, employing a modified Quantum Gradient Descent algorithm and a novel metric for entanglement "mapping." The core claim is that AQEM can predict long-range correlations with unprecedented accuracy, offering a significant advancement in the field. This paper details the algorithm's architecture, methodology, and preliminary results demonstrating its effectiveness. We explore the implementation of the Quantum Gradient Descent and the novel entanglement mapping metric, providing a theoretical foundation for the algorithm's performance.

DOI: 10.5281/zenodo.22605203

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