Single and binary star population models

21世纪是大数据与天文学相遇的世纪。像欧洲空间局的盖亚这样的大型调查已经为我们提供了前所未有的大量关于银河系内外各种恒星的数据。其他的，像SDSS和galah，给出了这些恒星的化学信息。还有一些望远镜，比如泛星望远镜，可以探测到超新星和恒星合并等瞬态现象。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源的建模联系起来：恒星本身？恒星演化中存在许多问题，特别是与双星及其在Ia型超新星、恒星合并和作为引力波源中的关键作用有关的问题，这些问题将从大的调查数据中受益匪浅。该项目旨在通过采用最先进的统计技术，以一种可量化、可靠和快速的方式，将单星和双星种群模型与恒星种群的观测结果进行比较，从而开发出实现这一目标的工具。它将使用来自盖亚和其他大型巡天的公开数据来确定天体物理模型中长期存在的不确定性，这些不确定性将用于我们在萨里大学构建的恒星模型，包括单星和双星。其目的是为天文学界提供开发的工具，从而帮助提高萨里大学的国际声誉和学生的声誉。这是一个亟待解决的巨大天文统计问题！

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!