collaborators

5 papers

math.NA2026

A Theory of Relaxation-Based Algebraic Multigrid

Rayan Moussa, Karsten Kahl

Algebraic multigrid (AMG) methods derive their optimal efficiency from the interplay between a relaxation process and a corresponding coarse grid correction. In many standard formu…

math.NA2026

Nodal Coarsening and Sparse Ideal Interpolation for H(curl) Problems in Algebraic Multigrid

Taoli Shen, James Brannick, Robert Falgout +2

We propose a sparse interpolation construction and a practical coarsening algorithm for the algebraic multigrid (AMG) method, tailored towards H(curl). Building on the generalized…

math.NA2025

Nodal AMG Coarsening and Interpolation for PDE Systems

James Brannick, Robert Falgout, Karsten Kahl +2

We present an approach to constructing a practical coarsening algorithm and interpolation operator for the algebraic multigrid (AMG) method, tailored towards systems of partial dif…

math.NA2025

Generalized Optimal AMG Convergence Theory for Stokes Equations Using Smooth Aggregation and Vanka Relaxation Strategies

Ahsan Ali, James J. Brannick, Karsten Kahl +4

This paper discusses our recent generalized optimal algebraic multigrid (AMG) convergence theory applied to the steady-state Stokes equations discretized using Taylor-Hood elements…

math.NA2025

Generalized Optimal AMG Convergence Theory for Nonsymmetric and Indefinite Problems

Ahsan Ali, James Brannick, Karsten Kahl +3

Algebraic multigrid (AMG) is known to be an effective solver for many sparse symmetric positive definite (SPD) linear systems. For SPD systems, the convergence theory of AMG is wel…