自适应量子态的概率生成算法

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing holds immense promise for revolutionizing various fields, but its practical implementation faces significant challenges related to qubit stability and control. Quantum state generation is a critical step in quantum computation, and current approaches often rely on static strategies. This paper introduces a novel algorithm, "Quantum State Evolution and Adaptation" (QSEA), designed to address these limitations. QSEA dynamically adjusts the generation strategy based on predicted outcomes, optimizing quantum state generation for improved efficiency and accuracy. The core mechanism leverages a "Quantum State Evolution" process, iteratively refining the quantum state until a desired outcome is achieved. We present a comprehensive analysis of QSEA's performance across a range of quantum algorithms, demonstrating its potential to enhance quantum computing capabilities. This research contributes to the development of more robust and versatile quantum computation methodologies.

DOI: 10.5281/zenodo.22296377

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