Eigenspectrum Noise Subtraction Methods in Lattice QCD

TL;DR

This paper introduces eigenspectrum subtraction, a novel noise reduction technique leveraging low eigenmodes to improve lattice QCD calculations, especially at low quark masses, outperforming perturbative methods.

Contribution

The paper presents a new eigenspectrum subtraction method that uses low eigenmode information to reduce noise in lattice QCD computations, offering advantages over existing perturbative approaches.

Findings

Eigenspectrum subtraction effectively suppresses statistical noise.

The method shows improved accuracy over perturbative subtraction.

Results demonstrate benefits for calculations involving disconnected loops.

Abstract

We propose a new noise subtraction method, which we call "eigenspectrum subtraction", which uses low eigenmode information to suppress statistical noise at low quark mass. This is useful for lattice calculations involving disconnected loops or all-to-all propagators. It has significant advantages over perturbative subtraction methods. We compare unsubtracted, eigenspectrum and perturbative error bar results for the scalar operator on a small Wilson QCD matrix.