论文标题
上车货车：用于量化核动力学模型不确定性的贝叶斯框架
Get on the BAND Wagon: A Bayesian Framework for Quantifying Model Uncertainties in Nuclear Dynamics
论文作者
论文摘要
我们描述了我们正在开发的网络基础设施的贝叶斯分析（BARD）框架，该框架将统一核模型，实验数据和相关不确定性的处理。我们概述了频带工具集的统计原理和核形理环境，重点是贝叶斯方法学利用多个模型的见解的能力。为了促进对这些工具的理解，我们提供了一个简单易访问的频段框架应用程序的示例。提出了四个案例研究，以强调该框架的要素如何在核物理学中复杂，范围内的问题上取得进展。通过收集符号和术语，提供说明性示例并概述相关技术，本文旨在开放核物理和统计社区可以为乐队框架做出贡献和建立的道路。
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.
