Constraining cosmological and galaxy formation models from galaxy surveys

观测结果似乎表明，宇宙不仅在膨胀，而且在以加速的速度膨胀。对此有两种解释：(I)加速膨胀是由某种形式的‘暗能量’(包括一个宇宙常数)引起的，或者(Ii)爱因斯坦的引力定律需要在宇宙尺度上进行修正。许多调查一直试图测量暗能量的状态方程w；到目前为止，所有的结果都符合w=-1，正如预期的宇宙学常数。在这个项目中，学生将探索利用现有和未来的星系调查来限制宇宙学和星系形成模型的替代方法。其目标是设计能够区分不同模型的观察性测试，并通过数值模拟进行验证。这些测试可能包括星系动力学，如从星系团信号的红移空间扭曲、最佳加权星系样本的相互关联以及与其他观测的相互关联，例如中性氢的射电观测。然后，学生将把这些测试应用于现有的测量数据，如星系和质量组装测量(GAMA；http://www.gama-survey.org/)，)，并告知未来将使用主要新设施进行的测量的设计，如4米多目标光谱望远镜(4MOST；https://www.4most.eu/J)和大型天气观测望远镜(LSST；https://www.lsst.org).这个项目将给学生在数值模拟和最先进的观测数据集方面的经验，以及密切参与主要的新调查。

Observations appear to show that the Universe is not only expanding, but that it is doing so at an accelerating rate. Two explanations have been proposed to understand this: (i) the accelerated expansion is caused by some form of 'dark energy' [including a cosmological constant), or (ii) Einstein's law of gravity {GR) needs to be modified on cosmological scales. Many surveys have been attempting to measure the equation of state, w, of dark energy; all results so far are consistent with w = -1, as expected for a cosmological constant. In this project the student will explore alternative ways of constraining cosmological and galaxy formation models utilising existing and future galaxy surveys. The goal Is to design observational tests that can distinguish between different models, verified using numerical simulations. These tests might include galaxy dynamics, as Inferred from redshift-space distortions of the clustering signal, cross-correlation of optimally-weighted galaxy samples, and cross-correlation with other surveys, such as radio surveys for neutral hydrogen. The student will then apply these tests to existing survey data, such as the Galaxy and Mass Assembly survey (GAMA; http://www.gama-survey.org/), and inform the design of future surveys to be carried out with major new facilities such as the 4-metre Multi-Object Spectroscopic Telescope (4MOST; https://www.4most.eu/J and the Large Synoptic Survey Telescope (LSST; https://www.lsst.org). This project will give the student experience in numerical simulations and state of the art observational data-sets as well as getting closely involved in major new surveys.