(Approximate) Low-Mode Averaging with a new Multigrid Eigensolver

TL;DR

This paper introduces a multigrid eigensolver for low-modes of the Hermitian Wilson Dirac operator, enabling faster computations and improved low-mode averaging techniques in lattice QCD.

Contribution

A novel multigrid eigensolver compatible with Hermitian and non-Hermitian operators, significantly speeding up low-mode calculations and enhancing low-mode averaging methods.

Findings

Achieves over tenfold speed-up compared to PARPACK.

Enables low-accuracy eigenvectors to reduce computational costs.

Improves statistical accuracy in lattice QCD calculations.

Abstract

We present a multigrid based eigensolver for computing low-modes of the Hermitian Wilson Dirac operator. For the non-Hermitian case multigrid methods have already replaced conventional Krylov subspace solvers in many lattice QCD computations. Since the $\gamma_5$-preserving aggregation based interpolation used in our multigrid method is valid for both, the Hermitian and the non-Hermitian case, inversions of very ill-conditioned shifted systems with the Hermitian operator become feasible. This enables the use of multigrid within shift-and-invert type eigensolvers. We show numerical results from our MPI-C implementation of a Rayleigh quotient iteration with multigrid. For state-of-the-art lattice sizes and moderate numbers of desired low-modes we achieve speed-ups of an order of magnitude and more over PARPACK. We show results and develop strategies how to make use of our eigensolver for calculating disconnected contributions to hadronic quantities that are noisy and still computationally challenging. Here, we explore the possible benefits, using our eigensolver for low-mode averaging and related methods with high and low accuracy eigenvectors. We develop a low-mode averaging type method using only a few of the smallest eigenvectors with low accuracy. This allows us to avoid expensive exact eigensolves, still benefitting from reduced statistical errors.