Bayesian analysis of the dynamic Universe

过去十年在观测宇宙学方面取得的惊人进步，以前所未有的精确度检验了我们的标准宇宙图景的有效性。现在，研究宇宙大尺度结构的不均一性带来了挑战，其中可能包含关于现代宇宙学面临的一些主要问题的大量未被驯服的信息：暗能量的性质、中微子的质量、推动宇宙膨胀的过程以及引力波的存在。理想情况下，调查和宇宙模型之间的联系应该通过探索数百万维的参数空间，在一个全面的贝叶斯框架内进行。近年来，针对这一想法，几种算法和软件包取得了一些成功。这个项目的目的是利用这些结果来加深我们对宇宙学和基础物理学的理解。拟议的工作包括使用计算技术预测和提取物理信号，应用于合成和真实星系和透镜调查，以及与互补的天文数据集的相互关联。作为该方法的自然结果，该项目将提供对局部和极端尺度宇宙中动态宇宙网的前所未有的详细特征。潜在的应用包括从超新星推断哈勃膨胀率，包括获得特殊速度分布的知识；研究细丝的动力学Sunyaev-Zel‘dovich效应；探索星系属性之间的关联，如内在排列，以及物质分布和潮汐场，以进一步了解星系的形成过程。

The spectacular progresses of the last decade in observational cosmology have tested the validity of our standard picture of the Universe at unprecedented accuracy. Challenges now arise from studying the inhomogeneities of the cosmic large-scale structure, which may contain a wealth of untamed information on some of main problems facing modern cosmology: the nature of dark energy, the masses of neutrinos, the processes driving cosmic inflation, and the presence of gravitational waves. Ideally, the connection between surveys and cosmological models should be made in a full-scale Bayesian framework, by exploring the multi-million dimensional parameter space. Tackling this idea, several algorithms and software packages have met some success in recent years. This project aims at exploiting these results to further our understanding of cosmology and fundamental physics. The proposed work includes the use of computational techniques to predict and extract physical signals, the application to synthetic and real galaxy and lensing surveys, and the cross-correlation with complementary astronomical data sets. As natural outcomes of the approach, the project will provide unprecedentedly detailed characterisations of the dynamic cosmic web in the local and extreme-scale Universe. Potential applications include inferring the Hubble expansion rate from supernovae, including the derived knowledge of the peculiar velocity distribution; investigating the kinetic Sunyaev-Zel'dovich effect from filaments; exploring correlations between galaxy properties, such as intrinsic alignments, and the matter distribution and tidal fields, to further the understanding of the galaxy formation process.