Fundamental Cosmology in the Era of Surveys: A Multi-scale Numerical Campaign

我们很幸运地生活在宇宙学特别令人兴奋的时代。未来十年将预示着对星系的几次大规模调查的开始，旨在回答宇宙学中一些最紧迫、最突出的问题的最终目标：暗物质的性质是什么？推动宇宙加速膨胀的根本物理因素是什么？有超越标准模型的物理学证据吗？解决这些根本问题需要一次星系普查--换句话说，一张宇宙大尺度结构的地图--无论是在数量上还是在数据的精确度上，这都远远超出了我们目前所能获得的。幸运的是，像暗能量光谱仪(DESI)、遗留时空调查(LSST)、欧几里德和南希·格雷斯·罗曼太空望远镜等计划中的探测正是为这些需求量身定做的。为了理解这些庞大而昂贵的数据集，有必要在同样复杂的理论模型的背景下考虑它们。我的计划位于宇宙学、粒子物理学和高性能计算的结合点，将解决这一需求，以下是三个广泛的科学问题：在标准理论之外探索宇宙学的新前沿是什么？在我们最好的宇宙模型中，暗物质和暗能量被认为占主导地位，但我们对它们的本质的理解仍然令人遗憾地不完整。我将开发新的技术来探索暗物质和引力的不同理论，这些技术利用即将变得可行的新观测方法。其中一个例子是一种被称为“强度测绘”的方法，它通过测绘从宇宙中发出的原始辐射来表征宇宙中第一批星系的分布。使用最先进的辐射流体力学模拟，我的研究将第一次描述暗物质粒子性质的不同假设下这种辐射的统计特性，为约束这些理论提供一个潜在的非常强大的探测器。暗物质和重子(“普通”)物质之间的相互作用可能如何影响我们从未来的星系调查中推断出的东西？我们希望从即将到来的调查中测量的许多现象直接映射到描述我们宇宙的基本宇宙学模型。另一方面，这些推论在考虑到星系形成物理学对物质聚集的“反馈”后，可能会发生重大变化。目前，只模拟暗物质的模拟是用于比较理论和观测的标准数据集，无法解释这些重子效应。理解重子过程在推断宇宙学参数时所带来的系统偏差，在为下一代调查做准备时至关重要。我的研究将产生的新一代模拟将创建一个独特的框架，以检验到目前为止已经做出的标准假设。从我们自己的银河系后院，我们能从宇宙中了解到什么？围绕银河系运行的暗淡星系是宇宙历史上形成的第一代结构；被银河系引力摧毁的这些星系子集留下的潮汐碎片散落在夜空中，可以作为我们银河系形成历史的追踪器。了解银河系为我们提供了一个独特的机会来确定早期星系形成的不确定物理。我的研究还将专注于对第一批星系的形成进行建模，并将开发一种新的方法来跟踪它们在银河系引力场中的后续演化。通过UKRI FLF，我将开发一项长期、多尺度的数值模拟活动，将提供一个无与伦比的理论框架，以与未来的调查进行比较。

We are fortunate to live in a particularly exciting time for cosmology. The next decade will herald the onset of several large-scale surveys of galaxies, designed for the ultimate goal of answering some of the most pressing, outstanding problems in cosmology: What is the nature of the dark matter? What is the underlying physics that drives the accelerated expansion of the Universe? Is there evidence for physics beyond the Standard Model? Addressing these fundamental questions requires a census of galaxies -- in other words, a map of the large-scale structure of the Universe -- that exceeds far beyond what we have available to us at the moment, both in its volume and the precision of the data. Fortunately, planned surveys like the Dark Energy Spectroscopic Instrument (DESI), the Legacy Survey of Space and Time (LSST), Euclid and The Nancy Grace Roman Space Telescope are purpose-built for exactly these demands. In order to make any sense of these large -- and expensive -- data sets, it is necessary to consider them in the context of equally sophisticated theoretical models. My programme, which lies at the nexus of cosmology, particle physics and high-performance computing, will address this need, following three broad scientific questions: What are the new frontiers for probing cosmologies beyond the standard theory? In our best models of the Universe, dark matter and dark energy are thought to dominate, yet our understanding of their nature remains woefully incomplete. I will develop new techniques for probing different theories of dark matter and gravity which take advantage of new observational methods that will soon become feasible. One such example is a method known as "intensity mapping", which characterises the distribution of the first galaxies that formed in the cosmos by mapping the primordial radiation emanating from them. Using state-of-the-art radiation hydrodynamics simulations, my research will, for the first time, characterise the statistics of this radiation under different assumptions for the nature of the dark matter particle, offering a potentially very powerful probe for constraining these theories.How might the interplay between dark and baryonic ("ordinary") matter affect what we infer from future galaxy surveys? Many of the phenomena we expect to measure from upcoming surveys map directly to the underlying cosmological model describing our Universe. On the other hand, these inferences may be altered significantly after accounting for 'feedback' from galaxy formation physics on the clustering of matter. Simulations that model dark matter only are, at present, the standard data sets used to compare theory with observation, and are unable to account for these baryonic effects. Understanding the systematic biases imparted by baryonic processes on the inference of cosmological parameters is of paramount importance in the build-up to next generation surveys. The new generation of simulations my research will produce will create a unique framework to test the standard assumptions that have been made until now. What can we learn about the Universe from our own Galactic backyard? The faint galaxies orbiting the Milky Way are amongst the first generations of structures formed in cosmic history; the tidal debris left over by the subset of these galaxies that have been destroyed by the gravity of the Milky Way lay strewn across night sky, and can be used as tracers of the formation history of our Galaxy. Understanding the Milky Way provides us with a unique opportunity to pin down the uncertain physics of early galaxy formation. My research will also focus on modelling the formation of the first galaxies and will develop a novel approach for tracing their subsequent evolution in the gravitational field of the Milky Way.With the UKRI FLF, I will develop a long-term, multi-scale campaign of numerical simulations that will present an unrivalled theoretical framework to compare against future surveys.