An Algorithm for Obtaining Reliable Priors for Constrained-Curve Fits

TL;DR

The paper presents the Sequential Empirical Bayes Method, an adaptive approach to obtain reliable priors for constrained-curve fits, improving stability in lattice QCD data analysis at low quark masses.

Contribution

It introduces a new adaptive fitting procedure that enhances the stability and reliability of priors in constrained-curve fitting for lattice QCD data.

Findings

Effective stabilization of fits at low quark masses

Application to overlap fermion data on a quenched lattice

Demonstrated improved fit reliability in low-mass regime

Abstract

We introduce the ``Sequential Empirical Bayes Method'', an adaptive constrained-curve fitting procedure for extracting reliable priors. These are then used in standard augmented-chi-square fits on separate data. This better stabilizes fits to lattice QCD overlap-fermion data at very low quark mass where a priori values are not otherwise known. We illustrate the efficacy of the method with data from overlap fermions, on a quenched $16^3\times 28$ lattice with spatial size La=3.2 fm and pion mass as low as $\sim$ 180 MeV.