Quantum Hidden Matrix Adaptive Computation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Hidden Matrix (QHM) theory presents a paradigm shift in quantum computation, offering the potential for highly efficient algorithms and enhanced error correction. This paper introduces an adaptive computation framework predicated on QHM principles, aiming to accelerate the calculation and prediction of quantum system states and facilitate quantum error correction. We detail the core mechanism, leveraging the inherent adaptability of QHM matrices to achieve significant computational speedups and improved error resilience. The paper outlines the fundamental concepts, the proposed framework's architecture, and the expected benefits of this approach. The research emphasizes the potential for transformative advancements across various quantum computing applications.

DOI: 10.5281/zenodo.22204060

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