Constraining Stellar Evolution Models using Observations of Stars in Nearby Galaxies

菲利普·罗森菲尔德被授予NSF天文学和天体物理学博士后奖学金，在哈佛-史密森天体物理中心开展研究和教育计划。他计划的重点是利用哈勃太空望远镜对其他星系中数万颗恒星的观测来改进恒星演化模型。大质量恒星在很大程度上负责调节宇宙时间段内星星形成的强度。几乎任何解释星系观测的尝试都需要了解大质量恒星。尽管它们很重要，但目前的大质量恒星模型与目前的观测结果并不相符。从历史上看，大质量恒星模型的校准仅限于在类似环境中形成的相对较少的恒星，其他环境中的大质量恒星模型主要是外推。随着最近揭示更遥远星系中单个恒星的大型调查的激增，天文学家现在拥有必要的数据来显着改进各种环境中的大质量星星模型。该教育计划旨在通过帮助学生创建和展示自己的数字天文馆节目，提高波士顿中学学生学习天文学的信心和热情。该计划的主要目标是系统地校准广泛使用的最先进的恒星演化模型的不确定方面，使用最好的数据作为最广泛的金属丰度范围内的约束条件。所有新模型都将公开传播，Rosenfield将与人口综合建模人员密切合作，以确保模型能够快速轻松地纳入其分析程序。为了评估哪一个是最有可能的恒星演化模型，Rosenfield将计算跨越不确定模型参数空间以及数据金属丰度范围的大量恒星模型。然后将每组数据与观察数据进行统计学比较。通过要求所有金属丰度和质量的可接受拟合，不仅将知道最佳拟合参数，而且将揭示参数之间的任何简并性。对于教育计划，罗森菲尔德将与志愿者和教师合作，准备波士顿中学的学生给他们的同龄人数字天文馆显示。

Philip Rosenfield is awarded an NSF Astronomy and Astrophysics Postdoctoral Fellowship to carry out a program of research and education at the Harvard-Smithsonian Center for Astrophysics. The focus of his program is to improve models of stellar evolution using observations from the Hubble Space Telescope of tens of thousands of stars in other galaxies. Massive stars are largely responsible for regulating the intensity of star formation over cosmic stretches of time. Nearly any attempt to interpret observations of galaxies requires understanding the massive stars. Despite their importance, current models of massive stars do not match current observations. Historically, calibrations of massive stars models are limited to a relatively small number of stars formed in similar environments, and models of massive stars in other environments are largely extrapolations. With the recent surge in large surveys that reveal individual stars in more distant galaxies, astronomers now have the necessary data to significantly improve massive star models in a diverse set of environments. The educational program aims to increase the confidence and enthusiasm in learning astronomy of Boston Middle School students by preparing students to create and present their own digital planetarium shows. The primary goal of this program is to systematically calibrate the uncertain aspects of widely used, state-of-the-art stellar evolution models, using the best possible data as constraints across the widest range of metallicity. All new models will be publicly disseminated and Rosenfield will work closely with population synthesis modelers to ensure the models can quickly and easily be incorporated into their analysis routines. To assess which is the most probable stellar evolution model given the observational constraints, Rosenfield will calculate large sets of stellar models spanning the uncertain model parameter space as well as the metallicity range of the data. Each set will then be statistically compared to observational data. By requiring acceptable fits across all metallicities and masses, not only will the best fitting parameters become known, but any degeneracies between parameters will be revealed. For the educational program, Rosenfield will work with volunteers and teachers to prepare Boston Middle School students to give digital planetarium shows to their peers.