Combining computer models to account for mass loss in stellar evolution
Combining computer models to account for mass loss in stellar evolution
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结合计算机模型来解释恒星演化中的质量损失
DOI：
10.1002/sam.11172
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
W. Jefferys
中科院分区：
文献类型：
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作者：
N. Stein;D. V. Dyk;T. Hippel;S. DeGennaro;E. Jeffery;W. Jefferys
复杂的计算机模型可用于描述天文学中复杂的物理过程，例如恒星的演化。与抽样分布一样，这些模型通常将观察到的数量预测为许多未知参数的函数。然而，将它们作为统计模型的组成部分会带来重大的建模、推理和计算挑战。在本文中，我们通过研究恒星随着年龄的增长而经历的质量损失来解决这些挑战。我们开发了一种新的贝叶斯技术来推断所谓的初始-最终质量关系（IFMR），即类太阳恒星的初始质量与其作为白矮星的最终质量之间的关系。我们的模型包含了针对恒星演化各个阶段的几个独立的计算机模型。我们将这些计算机模型与参数化 IFMR 连接起来，以便将它们嵌入到统计模型中。这一策略使我们能够充分利用强大的统计工具来构建、拟合、检查和改进统计模型及其计算机模型组件。与推断 IFMR 的传统技术相比（这种技术往往非常临时），我们可以估计拟合的不确定性并确保我们的模型组件内部一致。我们分析了来自三个星团的数据：NGC 2477、毕星团和 M35 (NGC 2168)。 NGC 2477 和 M35 的结果提出了关于中高质量范围 IFMR 的不同结论，为进一步的天文学工作提出了问题。我们还比较了恒星演化初级氢燃烧阶段的两种不同模型的结果。我们通过模拟表明，建模阶段的错误指定有时会对推断的白矮星质量产生严重影响。尽管如此，在处理观察到的数据时，我们的推论对这一进化阶段的模型选择并不是特别敏感。 © 2013 Wiley periodicals, Inc. 统计分析和数据挖掘 6: 34–52, 2013
Intricate computer models can be used to describe complex physical processes in astronomy such as the evolution of stars. Like a sampling distribution, these models typically predict observed quantities as a function of a number of unknown parameters. Including them as components of a statistical model, however, leads to significant modeling, inferential, and computational challenges. In this article, we tackle these challenges in the study of the mass loss that stars experience as they age. We have developed a new Bayesian technique for inferring the so‐called initial–final mass relation (IFMR), the relationship between the initial mass of a Sun‐like star and its final mass as a white dwarf. Our model incorporates several separate computer models for various phases of stellar evolution. We bridge these computer models with a parameterized IFMR in order to embed them into a statistical model. This strategy allows us to apply the full force of powerful statistical tools to build, fit, check, and improve the statistical models and their computer model components. In contrast to traditional techniques for inferring the IFMR, which tend to be quite ad hoc, we can estimate the uncertainty in our fit and ensure that our model components are internally coherent. We analyze data from three star clusters: NGC 2477, the Hyades, and M35 (NGC 2168). The results from NGC 2477 and M35 suggest different conclusions about the IFMR in the mid‐ to high‐mass range, raising questions for further astronomical work. We also compare the results from two different models for the primary hydrogen‐burning stage of stellar evolution. We show through simulations that misspecification at this stage of modeling can sometimes have a severe effect on inferred white dwarf masses. Nonetheless, when working with observed data, our inferences are not particularly sensitive to the choice of model for this stage of evolution. © 2013 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 6: 34–52, 2013