基于自适应的量子态的自适应映射

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel approach to quantum state mapping leveraging adaptive parameter adjustment. Traditional quantum state mapping methods are often static, offering limited flexibility and hindering optimization. We propose a system that dynamically adjusts quantum state parameters based on input data, enabling a more efficient mapping process. The core mechanism involves a feedback loop that continuously refines the quantum state to achieve the desired outcome. This adaptive approach offers a significant improvement over existing techniques, particularly in scenarios requiring complex mappings and dynamic parameter adjustments. The proposed method demonstrates improved performance through rigorous analysis and simulations, highlighting its potential for advancing quantum computing.

DOI: 10.5281/zenodo.22263682

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