On the Subspace Projected Approximate Matrix method
Jan H. Brandts, Ricardo Reis da Silva

TL;DR
This paper provides a detailed analysis of the SPAM iterative method for eigenvalue computation, revealing its connections to Lanczos and Jacobi-Davidson methods, and illustrating its potential as a transitional approach.
Contribution
It explains the SPAM method, shows its equivalence to known methods for specific cases, and interprets it as a boosted Lanczos or preconditioned Jacobi-Davidson variant.
Findings
SPAM can be mathematically equivalent to known eigenvalue methods.
Certain choices of $A_0$ turn SPAM into a boosted Lanczos method.
SPAM acts as a transition between Lanczos and preconditioned Jacobi-Davidson.
Abstract
We provide a comparative study of the Subspace Projected Approximate Matrix method, abbreviated SPAM, which is a fairly recent iterative method to compute a few eigenvalues of a Hermitian matrix . It falls in the category of inner-outer iteration methods and aims to save on the costs of matrix-vector products with within its inner iteration. This is done by choosing an approximation of , and then, based on both and , to define a sequence of matrices that increasingly better approximate as the process progresses. Then the matrix is used in the th inner iteration instead of . In spite of its main idea being refreshingly new and interesting, SPAM has not yet been studied in detail by the numerical linear algebra community. We would like to change this by explaining the method, and to show that for certain special choices for ,…
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Taxonomy
TopicsMatrix Theory and Algorithms · Electromagnetic Scattering and Analysis · Advanced Numerical Methods in Computational Mathematics
