Fast dual-MGS block-factorization algorithm for dense MoM matrices

A robust method is introduced for efficiently compressing dense method of moments (MoM) matrices using a dual modified Gram-Schmidt block-QR-factorization algorithm based on low-rank singular value decomposition. The compression is achieved without generating the full matrix or even full subblocks of the matrix. The compressed matrix may then be used in the iterative solution of the MoM problem. The method is very robust because it uses a reduced set of the original matrix entries to perform the compression. Furthermore, it does not depend on the analytic form of the Green´s function, so it may be applied to arbitrarily complex media.