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.

我们描述了贝叶斯核动力学分析 (BAND) 框架，这是我们正在开发的一种网络基础设施，它将统一对核模型、实验数据和相关不确定性的处理。我们概述了 BAND 工具集背后的统计原理和核物理学背景，重点是贝叶斯方法论利用来自多个模型的见解的能力。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。介绍了四个案例研究，以强调该框架的要素将如何推动核物理 (NP) 中复杂、范围广泛的问题取得进展。通过收集符号和术语，提供说明性示例，并概述相关技术，