Quantum State Adaptive Data Mapping

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel quantum state adaptive data mapping algorithm designed to enhance signal processing efficiency. Traditional data mapping approaches often rely on static parameter adjustments, failing to adequately address dynamic environments. This work leverages the unique properties of quantum states, specifically dynamic self-organization, to establish a fundamentally new mapping mechanism. We detail the core mechanism, outlining how the algorithm dynamically adjusts mapping parameters based on input data, resulting in improved signal processing performance. The algorithm's potential benefits are discussed, focusing on its ability to handle complex scenarios and provide a more robust and adaptable approach to data mapping.

DOI: 10.5281/zenodo.22187854

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