English

The Sequential Empirical Bayes Method: An Adaptive Constrained-Curve Fitting Algorithm for Lattice QCD

High Energy Physics - Lattice 2007-05-23 v1

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-χ2\chi^2 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 a0a_0 where ghost states (a quenched artifact) must be dealt with, and elaborate on the details of fits of the Roper resonance and S11(N1/2)S_{11}(N^{1/2-}) previously presented elsewhere. The data are from overlap fermions on a quenched 163×2816^3\times 28 lattice with spatial size La=3.2fmLa=3.2 {\rm fm} and pion mass as low as 180MeV\sim 180 {\rm MeV}.

Keywords

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