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Quantum Entanglement Self-Adaptation Framework for Enhanced Quantum System Performance

Jincheng Zhang

Published Sep 1, 2026• 0 citations
Publisher

Abstract

Quantum entanglement offers a fundamentally new paradigm for computation and information processing, potentially surpassing classical approaches in certain areas. However, the inherent complexity of quantum systems necessitates sophisticated control and optimization strategies. This paper presents a novel framework for self-adaptive quantum system parameter adjustment, leveraging the unique properties of quantum entanglement. We introduce a "Quantum State Graph" concept to model quantum system dynamics, dynamically adjusting parameters based on entanglement correlations to enhance performance. This approach goes beyond traditional parameter optimization techniques, offering a potential pathway to significantly improve the capabilities of quantum systems. This work demonstrates the feasibility of automated optimization through entanglement-based self-adaptation, potentially unlocking new quantum algorithms and applications.

DOI
10.5281/zenodo.22220465

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