The Sequential Empirical Bayes Method: An Adaptive Constrained-Curve Fitting Algorithm for Lattice QCD
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- fits on separate data. This better stabilizes fits to lattice QCD overlap-fermion data at very low quark mass where {\it a priori} values are not otherwise known. Lessons learned (including caveats limiting the scope of the method) from studying artificial data are presented. As an illustration, from local-local two-point correlation functions, we obtain masses and spectral weights for ground and first-excited states of the pion, give preliminary fits for the where ghost states (a quenched artifact) must be dealt with, and elaborate on the details of fits of the Roper resonance and previously presented elsewhere. The data are from overlap fermions on a quenched lattice with spatial size and pion mass as low as .
Cite
@article{arxiv.hep-lat/0405001,
title = {The Sequential Empirical Bayes Method: An Adaptive Constrained-Curve Fitting Algorithm for Lattice QCD},
author = {Ying Chen and Shao-Jing Dong and Terrence Draper and Ivan Horvath and Keh-Fei Liu and Nilmani Mathur and Sonali Tamhankar and Cidambi Srinivasan and Frank X. Lee and Jianbo Zhang},
journal= {arXiv preprint arXiv:hep-lat/0405001},
year = {2007}
}
Comments
37 pages, 16 figures, uses apsrev.bst