Quantum Topological Optimization of H-Matrix: A Novel Approach to Enhanced Quantum Computing Performance

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing is rapidly advancing, and the development of robust and efficient quantum algorithms is crucial for realizing its full potential. Quantum mechanics introduces inherent complexities in the manipulation of quantum states, demanding sophisticated optimization techniques. This paper introduces a novel dynamic topological optimization algorithm designed to enhance the computational efficiency and stability of quantum hidden-matrix representations, ultimately contributing to improved quantum computing performance. We explore a framework that automatically adjusts parameters to minimize error propagation, thereby optimizing the matrix's structure for faster calculations. The core mechanism leverages dynamic topological transformations to achieve this optimization, offering a significant advancement over existing methods. This research focuses on a practical implementation and thorough analysis of the algorithm's effectiveness, demonstrating its potential to address critical challenges in quantum computation.

DOI: 10.5281/zenodo.22204237

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