Quantum Entanglement Dynamic Parameter Adjustment and Optimization

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum entanglement, a bizarre phenomenon in quantum mechanics, offers a potentially revolutionary approach to optimization and algorithm development. This paper explores the application of quantum entanglement to dynamically adjust and optimize algorithms, leveraging the unique properties of entangled states. We propose a novel method utilizing entangled quantum states to guide the execution of complex algorithms, demonstrating improvements in performance compared to classical optimization techniques. The core mechanism focuses on exploiting entanglement's non-linearity to achieve a more efficient path toward optimal solutions. This work presents a framework for dynamically adjusting key parameters within an algorithm, potentially unlocking new possibilities for optimization across a broad range of computational tasks. We present preliminary results highlighting the efficacy of this approach, emphasizing the potential for significant performance gains through the integration of quantum entanglement.

DOI: 10.5281/zenodo.22279106

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