登上BAND Wagon:量化核动力学模型不确定性的贝叶斯框架

D. Phillips, R. Furnstahl, U. Heinz, T. Maiti, W. Nazarewicz, F. Nunes, M. Plumlee, M. Pratola, S. Pratt, F. Viens, Stefan M. Wild
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引用次数: 47

摘要

我们描述了核动力学贝叶斯分析(BAND)框架,这是一个我们正在开发的网络基础设施,它将统一处理核模型、实验数据和相关的不确定性。我们概述了BAND工具集的统计原理和核物理背景,重点介绍了贝叶斯方法利用多个模型的洞察力的能力。为了便于理解这些工具,我们提供了一个简单易懂的BAND框架应用示例。提出了四个案例研究,以突出该框架的要素如何能够在核物理学中复杂而广泛的问题上取得进展。通过收集符号和术语,提供说明性示例,并概述相关技术,本文旨在开辟核物理学界和统计学界可以为BAND框架做出贡献并以此为基础的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Get on the BAND Wagon: a Bayesian framework for quantifying model uncertainties in nuclear dynamics
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 insight 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 on complex, far-ranging problems in nuclear physics. 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 nuclear physics and statistics communities can contribute to and build upon the BAND framework.
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