Single and binary star population models

21世纪是大数据与天文学相遇的世纪。像欧洲航天局的GAIA这样的大型探测已经为我们提供了有关银河系内外各种恒星的史无前例的海量数据。其他的，如SDSS和Galah，提供了关于这些恒星的化学信息。其他的，如泛星，仍然探测到了超新星和恒星合并等瞬变现象。考虑到所有这些信息，我们如何最好地将其与宇宙中大多数光的来源：恒星本身的模型联系起来？在恒星演化中有许多问题，特别是关于双星及其在Ia型超新星、恒星合并和作为引力波源中的关键作用，这些都将从大调查数据中受益。该项目旨在开发工具，通过使用最先进的统计技术，以可量化、可靠和快速的方式，将单星和双星群星群模型与恒星群星群观测进行比较。它将使用盖亚和其他双星测量的公开数据来确定长期争论的天体物理模型中的不确定性，这些模型纳入了我们在萨里大学建造的单星和双星模型。目的是为天文学社区提供开发的工具，从而帮助提高萨里的国际声誉和这名学生的声誉。这是一个巨大的天体统计学问题，亟待解决！

The 21st century is where big data meets astronomy. Grand surveys, like the European Space Agency's Gaia are alreadyproviding us with unprecedented volumes of data on every type of star in our Galaxy and beyond. Others, like SDSS andGalah, give chemical information on these stars. Others still, such as Pan-STARRS, detect transient phenomena such assupernovae and stellar merging. Given all this information, how do we best link it to the modelling of the sources of most ofthe light in the Universe: the stars themselves? There are many problems in stellar evolution, in particular relating to binarystars and their key role in type Ia supernovae, stellar merging and as gravitational wave sources, which will benefit hugelyfrom big survey data. This project aims to develop the tools to do this by employing state-of-the-art statistical techniques tocompare single and binary star population models to observations of populations of stars, in a quantifiable, reliable and fastway. It will use publicly available data from Gaia and other bi g surveys to pin down long-debated uncertainties in theastrophysical models that go into our models of stars, both single and binary, as constructed at the University of Surrey.The aim is to provide the tools developed for the astronomical community, thus helping to enhance both Surrey'sinternational reputation and that of the student. This is a huge astrostatistical problem which needs addressing urgently!