A tool that performs the decomposition of a matrix into two matrices, one with orthonormal columns (Q) and an upper triangular matrix (R), facilitates a variety of mathematical and computational tasks. This process provides a way to express a given matrix as the product of these two specific matrix types.
This matrix decomposition is valuable in solving linear least squares problems, eigenvalue computations, and other numerical linear algebra applications. Historically, it has provided a robust and stable alternative to methods such as Gaussian elimination for solving systems of linear equations, particularly when dealing with ill-conditioned matrices or large datasets. Its numerical stability and well-defined procedure for orthogonalization make it suitable for many engineering and scientific applications.