RUI: Asteroseismology of pulsating Subdwarf B stars via observational mode identification and modeling

随着对脉动亚矮星B （sdB）恒星研究的深入，一个重要的问题出现了：它们是否在节点线数量大于3的高阶模式下脉动？模型需要包括这样的模式来解释观测到的脉动数量，但由于恒星表面的几何抵消，它们不太可能被观测到。这限制了模型推断sdB恒星内部条件的有效性。关于高阶模式这个有争议的问题目前还没有答案，但是多色测光法和时间序列光谱学等技术可以提供这个答案。为了解决这些问题，该项目将1)获得至少6颗脉动sdB星的高速多色观测；2)获取至少两颗恒星的时间序列光谱数据；3)生成扰动大气模式来解释观测结果；4)生成匹配约束模式的演化模型，并测试sdB恒星内部的物理特性。多色光度法对高阶模式特别敏感，但可以从中等大小的望远镜获得。这项工作将通过确定预测的高阶模态是否存在来严格测试当前的模型，并将产生包含最新理论的模型来匹配观测结果。提高sdB模型的准确性将增加对大多数水平分支恒星内部核心的理解，质量约束将测试进化场景。这项研究涉及本科生，他们将获得、减少和分析数据，并在会议和论文中传播结果。

As the study of pulsating subdwarf B (sdB) stars has developed, one overriding question has emerged: do they pulsate in high-degree modes where the number of nodal lines is greater than three? Models need to include such modes to account for the observed number of pulsations, but they are less likely to be observed because of geometric cancelation across the stellar surface. This has constrained the usefulness of the models for inferring the interior conditions of sdB stars. There is currently no answer to this controversial question about high-degree modes, but techniques such as multicolor photometry and time-series spectroscopy can be applied to provide that answer. To address these issues, this project will 1) obtain high-speed multicolor observations of at least six pulsating sdB stars; 2) obtain time-series spectroscopic data of at least two stars; 3) generate perturbed atmospheric models to interpret the observations; and 4) generate evolutionary models to match constrained modes and test the physics within sdB stars. Multicolor photometry is especially sensitive to high-degree modes, yet can be obtained from modest-sized telescopes. This work will critically test the current generation of models by determining if the predicted high-degree modes exist, and will produce models incorporating the latest theories to match the observations.Increasing the accuracy of sdB models will increase understanding of the cores inside most horizontal branch stars, and mass constraints will test evolution scenarios. The research involves undergraduate students, who will obtain, reduce, and analyze data and disseminate the results at conferences and in papers.