New Developments in Matrix and Tensor Theories with Applications

Dear Colleagues,

Matrix and tensor theories serve as fundamental mathematical tools in modern linear and multilinear algebra, playing indispensable roles in theoretical innovation and interdisciplinary application across mathematics, engineering, and information science. In recent decades, rapid advancements in computational mathematics, quantum information, control engineering, and data science have continuously promoted the development of matrix and tensor research, including the investigation of various matrix equations, generalized matrix inverses, tensor decomposition theories, noncommutative algebraic structures, and their extended qualitative and quantitative properties. Nevertheless, numerous theoretical challenges and practical application problems require further exploration, especially the novel structural characteristics, efficient numerical algorithms, and interdisciplinary extensions of complex matrix and tensor systems under generalized and nonstandard conditions.

This Topic aims to collect original, high-quality research articles and comprehensive reviews focusing on the latest theoretical progress, innovative numerical methods, and practical applications of matrix and tensor theories. We welcome studies covering matrix equation solving, tensor analysis, algebraic structural properties, and computational algorithms and their applications in quantum computing, intelligent control, data processing, and engineering modeling. The findings presented in this Topic will provide new insights and effective theoretical support for the further development of linear and multilinear algebra and its interdisciplinary fields.

Prof. Dr. Qing-Wen Wang
Prof. Dr. Yang Zhang
Topic Editors