标题： 对附近年轻恒星系统的年龄采用贝叶斯方法 I. 膨胀率方法 显示英文标题

标题： Going Bayesian on the ages of nearby young stellar systems I. The expansion rate method

摘要： 背景。 确定年轻恒星系统的年龄对于检验和验证当前的恒星形成理论至关重要。 目标。 我们旨在开发一种贝叶斯版本的膨胀率方法，该方法结合了关于恒星系统年龄的先验知识，并解决了传统频率论方法的一些局限性。 方法。 我们升级了一个现有的贝叶斯分层模型，添加了额外的参数层次结构，其中包括系统的年龄。对于后者，我们提出了受文献工作启发的先验分布。 结果。 我们在一组广泛的模拟数据集上验证了我们的方法，这些模拟数据集模仿了真实恒星系统的性质。在10到40百万年之间且距离不超过150秒差距的恒星协会中，误差小于10%。在距离可达400秒差距的恒星形成区域中，误差在3百万岁时可能高达80%，但随着年龄的增长迅速减小。 结论。 我们在这里提出的贝叶斯膨胀率方法在多个方面优于传统的频率论版本。特别是，贝叶斯年龄估计器比常用的频率论估计器更稳健可信。这个新的贝叶斯膨胀率方法作为免费开源代码Kalkayotl的一个模块公开提供。 显示英文摘要

摘要： Context. Determining the ages of young stellar systems is fundamental to test and validate current star-formation theories. Aims. We aim at developing a Bayesian version of the expansion rate method that incorporates the a priori knowledge on the stellar system's age and solves some of the caveats of the traditional frequentist approach. Methods. We upgrade an existing Bayesian hierarchical model with additional parameter hierarchies that include, amongst others, the system's age. For this later, we propose prior distributions inspired by literature works. Results. We validate our method on a set of extensive simulations mimicking the properties of real stellar systems. In stellar associations between 10 and 40 Myr and up to 150 pc the errors are <10%. In star forming regions up to 400 pc, the error can be as large as 80% at 3 Myr but it rapidly decreases with increasing age. Conclusions. The Bayesian expansion rate methodology that we present here offers several advantages over the traditional frequentist version. In particular, the Bayesian age estimator is more robust and credible than the commonly used the frequentist ones. This new Bayesian expansion rate method is made publicly available as a module of the free and open-source code Kalkayotl.