Dynamic Quantum Adaptive Algorithms

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper introduces a novel dynamic quantum adaptive algorithm designed to optimize quantum computation by dynamically adjusting quantum system parameters in response to input data. The core mechanism relies on a quantum self-adaptation process, allowing the system to evolve and refine its state based on the characteristics of the data being processed. We present a detailed theoretical analysis and preliminary implementation demonstrating the algorithm's effectiveness in adapting to varying input sequences, resulting in improved performance compared to static quantum algorithms in specific scenarios. The algorithm's success lies in its ability to continuously refine the quantum state, mitigating the limitations of traditional approaches.

DOI: 10.5281/zenodo.22509335

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