TL;DR
The paper introduces the fiber product homotopy method, a novel approach for solving multiparameter eigenvalue problems that is more efficient, accurate, and better suited for singular problems than existing methods.
Contribution
It develops a new homotopy method that requires deforming fewer equations, is provably convergent for all eigenpairs, especially effective for singular problems, and outperforms existing methods in speed and accuracy.
Findings
Requires deformation of O(1) linear equations, unlike existing methods.
Achieves backward errors around 10^{-16} without extended precision.
Significantly faster and more accurate than previous methods, especially on larger and singular problems.
Abstract
We develop a new homotopy method for solving multiparameter eigenvalue problems (MEPs) called the fiber product homotopy method. For a -parameter eigenvalue problem with matrices of sizes , fiber product homotopy method requires deformation of linear equations, while existing homotopy methods for MEPs require nonlinear equations. We show that the fiber product homotopy method theoretically finds all eigenpairs of an MEP with probability one. It is especially well-suited for dimension-deficient singular MEPs, a weakness of all other existing methods, as the fiber product homotopy method is provably convergent with probability one for such problems as well, a fact borne out by numerical experiments. More generally, our numerical experiments indicate that the fiber product homotopy method significantly outperforms the standard Delta method in terms…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
