Quantum Entanglement-Driven Algorithm Design

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the potential of quantum entanglement to revolutionize algorithm design, specifically focusing on the development of a novel algorithm paradigm centered on subtle correlations. We propose a 'Quantum Momentum' modifier, leveraging entanglement to guide the evolution of a solution space, offering significantly enhanced convergence speeds compared to traditional optimization techniques. The core mechanism hinges on the principle that entangled particles can subtly influence the system's trajectory, enabling faster and more efficient optimization. This research investigates the theoretical underpinnings of this approach, outlines the proposed algorithm architecture, and discusses potential applications across various optimization domains. The paper concludes with a preliminary assessment of the feasibility and impact of this quantum-inspired optimization strategy.

DOI: 10.5281/zenodo.22188150

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