Dynamic Complexity Computation: A Quantum Entanglement-Based Theoretical Framework

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper presents a novel theoretical framework for dynamic complexity computation, leveraging the unique properties of quantum entanglement to enhance the assessment of complex system computational complexity. We propose a method that establishes a direct link between complexity metrics and entanglement, enabling the precise evaluation of computational stability and guiding algorithm optimization based on this understanding. The core mechanism involves associating complexity with entanglement's inherent characteristics, utilizing entanglement for stability assessment and algorithmic optimization. This approach offers a fundamentally different perspective on complexity, moving beyond traditional statistical methods and embracing the subtle yet powerful interplay of quantum mechanics. This research aims to provide a robust and potentially transformative tool for computational complexity analysis, particularly in the design and optimization of complex algorithms.

DOI: 10.5281/zenodo.22321381

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