Quantum Information Modality Adaptive Algorithm Design

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum Information Modality (QIM) is a rapidly evolving field with immense potential for revolutionizing various computational tasks, including optimization, machine learning, and cryptography. QIM offers a fundamentally different approach to quantum computation compared to existing algorithms, leveraging the inherent dynamic nature of quantum states. This paper investigates the design of a novel QIM algorithm that employs adaptive modulation techniques to enhance algorithm efficiency and accuracy. We propose a dynamic modulation scheme based on a feedback loop, where the algorithm dynamically adjusts the quantum state to optimally address the input data. The core mechanism centers around the concept of "dynamic modulation," which allows the algorithm to adapt its state based on the input's characteristics, thereby enhancing its performance. This paper details the algorithm's architecture, explores its theoretical underpinnings, and presents preliminary experimental results demonstrating its effectiveness. The benefits of this adaptive approach are highlighted, offering a significant advancement in the design of QIM algorithms.

DOI: 10.5281/zenodo.22244269

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