利用流体动力学模拟构建宇宙模型
Building models of the Universe with hydrodynamic simulations
AI总结：
本研究围绕流体动力学宇宙模拟展开，介绍模拟的生成方法与代码性能，探究星系团rkSZ效应、熵分布观测与模拟的矛盾及熵剖面的宇宙学演化，为宇宙结构研究与未来观测提供支撑。
摘要：
流体动力学模拟在现代宇宙学中已成为探索复杂系统、作出预测以引导未来观测的不可替代的工具。在第1章中，我们首先从哲学层面讨论了模拟在科学中的作用，提出模拟能够弥合经验知识与基础知识之间的鸿沟，而模拟的验证工作强调了在可信度与质疑态度之间取得平衡的重要性。随后，第2章介绍了结构形成的相关内容，以及合成数据与观测数据的对比。第3章阐述了用于模拟单个天体的zoom-in（缩放放大）模拟的生成流程，以及用于缓解已知缺陷的新方法。我们还评估了SWIFT代码的弱可扩展性，发现它是并行效率最高的流体动力学代码之一。第4章中，我们基于MACSIS模拟研究了大质量星系团的转动动力学苏尼亚耶夫-泽尔多维奇（rkSZ）效应，发现最大信号超过100μK，比自相似模型的早期预测强30倍，为未来的探测工作开辟了前景。第5章中，我们解决了观测测得的熵分布与星系群和星系团模拟预测结果之间的矛盾。我们发现，大多数最新的流体动力学模拟系统性地高估了熵剖面，高估幅度最高可达一个数量级，导致得到的剖面比观测到的类幂律熵剖面更平缓、数值更高。我们利用EAGLE模型的变体讨论了不同流体动力学参数和子网格参数的影响。第6章探究了熵剖面随宇宙时间的演化，报告称两类天体在高红移下均呈现类幂律熵剖面，但在晚期会形成熵平台并改变剖面的形状。
英文摘要：
Hydrodynamic simulations have become irreplaceable in modern cosmology for exploring complex systems and making predictions to steer future observations. In Chapter 1, we begin with a philosophical discussion on the role of simulations in science. We argue that simulations can bridge the gap between empirical and fundamental knowledge. The validation of simulations stresses the importance of achieving a balance between trustworthiness and scepticism. Next, Chapter 2 introduces the formation of structures and comparisons between synthetic and observational data. Chapter 3 describes the production pipeline of zoom-in simulations used to model individual objects and novel methods to mitigate known shortcomings. Then, we assessed the weak scaling of the SWIFT code and found it to be one of the hydrodynamic codes with the highest parallel efficiency. In Chapter 4, we study the rotational kinetic Sunyaev-Zeldovich (rkSZ) effect for high-mass galaxy clusters from the MACSIS simulations. We find a maximum signal greater than 100 $μ$K, 30 times stronger than early predictions from self-similar models, opening prospects for future detection. In Chapter 5, we address a tension between the distribution of entropy measured from observations and predicted by simulations of groups and clusters of galaxies. We find that most recent hydrodynamic simulations systematically over-predict the entropy profiles by up to one order of magnitude, leading to profiles that are shallower and higher than the power-law-like entropy profiles that have been observed. We discuss the dependence on different hydrodynamic and sub-grid parameters using variations of the EAGLE model. Chapter 6 explores the evolution of the profiles as a function of cosmic time. We report power-law-like entropy profiles at high redshift for both objects. However, at late times, an entropy plateau develops and alters the shape of the profile.
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