1. Bayesian parameter estimation for effective field theories
- Author
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Richard Furnstahl, Arbin Thapaliya, Daniel R. Phillips, S. Wesolowski, and Natalie Klco
- Subjects
Physics ,EFTS ,Nuclear and High Energy Physics ,Chiral perturbation theory ,Nuclear Theory ,010308 nuclear & particles physics ,Estimation theory ,FOS: Physical sciences ,Probability and statistics ,Overfitting ,01 natural sciences ,Nuclear Theory (nucl-th) ,Bayesian statistics ,High Energy Physics - Phenomenology ,High Energy Physics - Phenomenology (hep-ph) ,Physics - Data Analysis, Statistics and Probability ,0103 physical sciences ,Prior probability ,Effective field theory ,Applied mathematics ,Nuclear Experiment (nucl-ex) ,010306 general physics ,Nuclear Experiment ,Data Analysis, Statistics and Probability (physics.data-an) - Abstract
We present procedures based on Bayesian statistics for estimating, from data, the parameters of effective field theories (EFTs). The extraction of low-energy constants (LECs) is guided by theoretical expectations in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools are developed that analyze the fit and ensure that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems, including the extraction of LECs for the nucleon mass expansion in SU(2) chiral perturbation theory from synthetic lattice data., Comment: 40 pages, 40 figures. Final version to appear in JPhysG
- Published
- 2016
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