基于量子纠缠的自适应计算框架

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel computational framework based on quantum entanglement, designed to achieve adaptive computation, offering enhanced efficiency and precision, particularly in the processing of high-dimensional data. Traditional computation relies on fixed parameters, while entanglement allows for dynamic adjustment of computation processes. This research explores the potential of leveraging quantum entanglement to dynamically tailor computational parameters, optimizing performance in scenarios where traditional algorithms struggle. The core mechanism focuses on establishing and maintaining entangled states to facilitate real-time adjustments to the computation process. We detail the framework's architecture, the implementation of entanglement-based adjustment strategies, and preliminary results demonstrating its effectiveness in a specific computational task. The paper concludes by highlighting the potential of this approach to revolutionize computation, especially in areas demanding high precision and scalability.

DOI: 10.5281/zenodo.22264907

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