自适应几何拓扑的计算 - 基于量子纠缠的计算范式

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper introduces a novel computational framework, termed "Adaptive Geometry Topology" (AGT), leveraging the unique properties of quantum entanglement to optimize complex computations. We propose a method where the core algorithm is dynamically restructured to exploit entanglement, allowing for significant improvements in computational efficiency and the exploration of complex optimization problems. The core mechanism centers around the transformation of core algorithms into quantum entanglement-based representations, enabling a fundamentally different approach to problem-solving. The research explores the potential of AGT in diverse optimization scenarios, highlighting its advantages in handling non-linear systems and intricate geometric structures. The paper provides a detailed explanation of the AGT framework, its theoretical underpinnings, and preliminary experimental results demonstrating its effectiveness in a simplified example. We conclude by discussing the future directions for this research, including scalability and wider applicability to real-world problems.

DOI: 10.5281/zenodo.22219665

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