Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...
Let P1 and P2 be respectively m × m and n × n permutation matrices, with m ≥ n. Suppose the m × n sparse matrix Ā = P1 AP2 is reduced to upper trapezoidal form [ R 0 ] through the application of ...
A band Lanczos algorithm for the iterative computation of eigenvalues and eigenvectors of a large sparse symmetric matrix is described and tested on numerical ...
Eigenvalue problems are a cornerstone of modern applied mathematics, arising in diverse fields from quantum mechanics to structural engineering. At their heart, these problems seek scalar values and ...
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