AI 中文总结
本论文开发了Sahyadri N体模拟、纤维重建校准框架、傅里叶空间平滑方法及Skeletor纤维 finder等工具，用于研究非线性宇宙网的几何、层级与动力学，为精确宇宙学研究提供支撑。
AI 中文摘要
宇宙大尺度结构（LSS）形成了由节点、纤维、片层和空洞构成的复杂网络，即宇宙网。随着当前及未来的星系巡天越来越多地探测结构形成的准线性和非线性区域，理解其几何结构与动力学对精确宇宙学至关重要。其中，在宇宙网中输运物质的宇宙纤维是这些动力学过程的核心。本论文开发了用于研究非线性宇宙网的数值工具：首先，引入了Sahyadri系列高分辨率宇宙学N体模拟，为精确研究LSS及其宇宙学依赖性提供了框架；随后，利用可控纤维样本开发了纤维重建的校准框架，可系统研究重建偏差，量化了纤维曲率和重建噪声对推断纤维属性的影响，并提出了一种新颖的傅里叶空间平滑方法以改善轮廓恢复；此外，本论文还提出了Skeletor，一种基于Voronoi的纤维 finder，可直接从离散示踪剂中识别纤维结构，同时明确纳入宇宙网的层级特性，并开发了一种新颖的亚纤维结构分类框架。将这些工具应用于宇宙学模拟后，揭示了纤维亚结构的独特属性，提供了纤维相空间的详细视图，包括相干流入、多流和类焦散特征。这些进展共同为研究非线性宇宙网的几何结构、层级性和动力学提供了框架，更广泛地为超越传统聚类度量、建立基于物理的非线性宇宙网理解的持续努力做出了贡献。
英文摘要
The Large-Scale Structure (LSS) of the Universe forms a complex network of nodes, filaments, sheets, and voids known as the Cosmic Web. As current and upcoming galaxy surveys increasingly probe the quasi-linear and non-linear regimes of structure formation, understanding its geometry and dynamics is essential for precision cosmology. In particular, cosmic filaments, which channel matter across the web, are central to these dynamical processes. This thesis develops numerical tools to study the non-linear cosmic web. First, the Sahyadri suite of high-resolution cosmological $N$-body simulations is introduced, providing a framework for precision studies of LSS and its cosmological dependence. A calibration framework for filament reconstruction is then developed using controlled filament realizations, enabling systematic investigation of reconstruction biases. The effects of filament curvature and reconstruction noise on inferred filament properties are quantified, and a novel Fourier-space smoothing approach is introduced to improve profile recovery. The thesis further presents Skeletor, a Voronoi-based filament finder that identifies filamentary structures directly from discrete tracers while explicitly incorporating the hierarchical nature of the cosmic web. A novel framework for classifying sub-filamentary structure is developed. Applying these tools to cosmological simulations reveals distinct properties of filament substructure and provides a detailed view of filament phase space, including coherent inflows, multistreaming, and caustic-like features. Together, these developments provide a framework for studying the geometry, hierarchy, and dynamics of the non-linear cosmic web. More broadly, they contribute to the ongoing effort to build a physically motivated understanding of the non-linear cosmic web beyond traditional measures of clustering.
Comments172 pages, PhD thesis
