Dynamic Quantum Hidden Matrix (DQM)

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces the Dynamic Quantum Hidden Matrix (DQM) algorithm, a novel approach to quantum computation that dynamically adjusts matrix parameters based on input data. The DQM aims to enhance the efficiency and robustness of quantum algorithms by eliminating the need for fixed, pre-defined parameters. The algorithm's core mechanism involves iterative refinement of matrix elements, guided by a feedback loop that continuously optimizes for desired performance characteristics. This approach offers a potential paradigm shift in quantum computing, addressing limitations of traditional methods and opening up new avenues for algorithm design. This research explores the theoretical foundations, implementation details, and initial experimental results demonstrating the DQM's effectiveness in a specific quantum computing task.

DOI: 10.5281/zenodo.22290659

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