A recipe for EFT uncertainty quantification in nuclear physics

TL;DR

This paper proposes a Bayesian-based recipe for quantifying uncertainties in nuclear physics calculations using effective field theory, addressing multiple sources of error for more reliable predictions.

Contribution

It introduces a systematic Bayesian framework to quantify and combine various sources of uncertainty in nuclear EFT calculations, enhancing predictive reliability.

Findings

Bayesian methods effectively model multiple uncertainty sources.

A toy model demonstrates the approach's potential.

Provides a practical recipe for uncertainty quantification.

Abstract

The application of effective field theory (EFT) methods to nuclear systems provides the opportunity to rigorously estimate the uncertainties originating in the nuclear Hamiltonian. Yet this is just one source of uncertainty in the observables predicted by calculations based on nuclear EFTs. We discuss the goals of uncertainty quantification in such calculations and outline a recipe to obtain statistically meaningful error bars for their predictions. We argue that the different sources of theory error can be accounted for within a Bayesian framework, as we illustrate using a toy model.