학술논문

Get on the BAND Wagon: a Bayesian framework for quantifying model uncertainties in nuclear dynamics
Document Type
article
Source
Journal of Physics G Nuclear and Particle Physics. 48(7)
Subject
Nuclear and Plasma Physics
Synchrotrons and Accelerators
Physical Sciences
statistical methods
uncertainty quantification
experimental design
heavy-ion collisions
nuclear mass models
nuclear reactions
Atomic
Molecular
Nuclear
Particle and Plasma Physics
Nuclear & Particles Physics
Nuclear and plasma physics
Particle and high energy physics
Language
Abstract
We describe the Bayesian analysis of nuclear dynamics (BAND) framework, a cyberinfrastructure that we are developing which will unify the treatment of nuclear models, experimental data, and associated uncertainties. We overview the statistical principles and nuclear-physics contexts underlying the BAND toolset, with an emphasis on Bayesian methodology's ability to leverage insights from multiple models. In order to facilitate understanding of these tools, we provide a simple and accessible example of the BAND framework's application. Four case studies are presented to highlight how elements of the framework will enable progress in complex, far-ranging problems in nuclear physics (NP). By collecting notation and terminology, providing illustrative examples, and giving an overview of the associated techniques, this paper aims to open paths through which the NP and statistics communities can contribute to and build upon the BAND framework.