自适应量子拓扑的并行计算框架

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing holds immense potential, but realizing this potential requires sophisticated algorithms and efficient computational architectures. This paper introduces a novel parallel computing framework based on self-adaptive quantum topology, designed to automatically adjust computational parameters to optimize performance. We propose a mechanism that leverages the inherent properties of quantum topology to dynamically adapt parallel execution strategies, leading to enhanced efficiency compared to traditional approaches. The framework's core concept is the ability to dynamically optimize the parallelism by intelligently adjusting the quantum circuit's parameters based on the system's state. This addresses the limitations of static parallelization methods, offering a potentially transformative approach to quantum computation. We present a theoretical model and preliminary implementation demonstrating the framework's capabilities. The paper concludes with a discussion of future research directions and potential applications of this innovative approach.

DOI: 10.5281/zenodo.22196301

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