Quantum Information Entropy Adaptive Computing

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

This paper presents a novel quantum information entropy algorithm designed for adaptive computation. The core idea is to dynamically adjust the entropy calculation process based on the inherent distribution of input data. Traditional entropy calculations are typically static, offering limited adaptability to varying data characteristics. This approach leverages a mechanism to continuously refine the algorithm, optimizing computational speed and accuracy by adapting to the data's unique patterns. The algorithm's design aims to surpass the limitations of fixed entropy calculations, offering a more responsive and potentially more efficient method for various information processing tasks.

DOI: 10.5281/zenodo.22158632

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