Nonlinear Topological Structures and Matrices: Dynamic Adjustment

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the application of nonlinear topological structures to matrices, proposing a dynamic adjustment mechanism that allows the matrix to adapt its internal structure and computational capabilities in response to changing input data and environmental conditions. Traditional matrix operations often involve pre-calculation of each element, which becomes inefficient for high-dimensional complex problems. Our work introduces a novel "quantum matrix" concept, leveraging simulated quantum systems to dynamically adjust matrix weights, thereby enhancing computational efficiency. The core mechanism centers on the formation and manipulation of these quantum matrices, offering a significant advancement over conventional approaches. This paper explores the potential of this approach for enhancing complex numerical computation, specifically focusing on its impact on efficiency and adaptability.

DOI: 10.5281/zenodo.22185234

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