Astrophysics at the University of Nottingham 2020-2023

我们在诺丁汉的主要研究重点是了解星系是如何形成的，以及它们是如何随着时间的推移演变成我们今天所看到的丰富多样的结构的。我们通过一些补充方法来解决这些问题。一种方法是研究相对较近的星系，我们可以更详细地观察到这些星系。在诺丁汉，我们参与了一个大型国际项目(漫画)，旨在解剖数以千计的本星系，并提取比以前可能获得的更多信息。在另一个极端，我们还专门研究非常遥远的星系，观察它们在数十亿年前的形成和转变过程中的行为。由于光速有限，当我们观察非常遥远的星系时，我们也在回顾遥远的时间，这使我们能够观察到宇宙历史上不同阶段的星系演化。我们研究的另一个目的是了解“先天”和“后天”在塑造星系演化中的作用，特别是它们如何受到所处环境的影响。我们使用世界上和太空中一些最大的望远镜，结合理论研究和计算机模拟，使用观察技术的组合来解决这些不同的和具有挑战性的问题。有了最新的超级计算机，我们可以创建模型来模拟星系的形成和宇宙结构的增长。许多最有趣的发现发生在我们用最新数据与我们的模型对峙时，以直接测试我们对塑造宇宙的关键过程的理解。我们还使用了引力透镜，这是一种新技术，它利用了大质量物体对时空的扭曲，使我们能够非常精确地绘制宇宙中物质和结构的分布。最后，我们还在开发新的“机器学习”工具，以帮助天文学界分析现在由天文观测和模拟常规产生的大量数据。

The main focus of our research in Nottingham is to understand how galaxies form and how they evolve through time to produce the rich variety of structures we see today. We tackle these problems with a number of complementary approaches. One approach is to study relatively nearby galaxies, which we can observe in greater detail. In Nottingham we are involved in a large international project (MaNGA), designed to dissect thousands of local galaxies and extract far more information than was previously possible. At the other extreme, we also specialise in studying very distant galaxies, observing them in the act of formation and transformation many billions of years ago. Due to the finite speed of light, when we observe very distant galaxies we are also looking far back in time, allowing us to observe galaxy evolution at different stages throughout the history of the Universe. Another aim of our research is to understand the roles of "nature" versus "nurture" in shaping galaxy evolution, and in particular how they are influenced by the environments in which they reside. We tackle these varied and challenging problems using a combination of observational techniques, using some of the largest telescopes in the world and in space, combined with theoretical studies and computer simulations. With the latest supercomputers we can create models to simulate the formation of galaxies and the growth of cosmic structures. Many of the most interesting discoveries occur when we confront our models with the latest data, to directly test our understanding of the key processes shaping the Universe. We also use gravitational lensing, a novel technique that exploits the warping of space time by massive objects, which allows us to map the distribution of matter and structure in the Universe to great precision. Finally, we are also developing new "machine learning" tools to help the astronomical community analyse the vast amounts of data that are now routinely produced by astronomical observations and simulations.