Mathematical Methods in Classical and Quantum Mechanics
Matrix factorization is the process of decomposing a matrix into a product of two or more matrices, simplifying complex data representations and revealing underlying structures. This technique is fundamental in linear algebra, particularly in finding eigenvalues and eigenvectors, which are crucial for understanding the behavior of linear transformations and systems. In many cases, matrix factorization enables diagonalization, allowing matrices to be expressed in a simpler form that is easier to manipulate for various applications such as solving differential equations or optimizing systems.
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