AI 中文总结
本研究构建基于宇宙网形态的标记相关函数，结合模拟仿真器提升宇宙学约束精度，连续标记可使FoM较标准2PCF提升约8.6倍，为大尺度结构巡天提取额外宇宙学信息提供新框架。
AI 中文摘要
宇宙网包含的形态依赖信息无法被标准两点统计量完全捕获。我们通过使用\textsc{Nexus}算法识别出的宇宙网形态，为暗物质晕分配标记，构建了基于形态学的标记相关函数（MCFs）。利用涵盖129个$w_0w_a$CDM宇宙学模型的\textsc{Kun}模拟套件，我们构建了作为宇宙学参数和示踪剂偏置函数的MCFs高斯过程仿真器。随后我们将这些仿真器应用于来自独立的\textsc{Jiutian}模拟的模拟暗物质晕星表，并开展联合似然分析以量化由此得到的宇宙学约束。我们考虑了两种标记选择：离散形态标记和连续形态强度标记。连续标记的品质因数（FoM）相较于标准两点相关函数（2PCF）提升了约8.6倍，且将$σ_8$的1σ不确定度降低了约5倍。离散标记带来的FoM提升幅度较小，约为17%。我们进一步通过将暗物质晕质量阈值改变约4.5倍，测试了示踪剂选择的影响。即使在最低质量阈值下，连续标记仍保持无偏，且实现的FoM约为单独使用2PCF时的3.4倍。这些结果表明，基于形态学的MCFs结合基于模拟的仿真，为从大尺度结构巡天中提取额外宇宙学信息提供了有用的框架。
英文摘要
The cosmic web contains morphology-dependent information that is not fully captured by standard two-point statistics. We construct morphology-based marked correlation functions (MCFs) by assigning marks to halos according to the cosmic-web morphology identified with the \textsc{Nexus} algorithm. Using the \textsc{Kun} simulation suite, which spans 129 $w_0w_a$CDM cosmologies, we build Gaussian-process emulators for the MCFs as functions of cosmological parameters and tracer bias. We then apply the emulators to mock halo catalogues from the independent \textsc{Jiutian} simulation and perform a joint likelihood analysis to quantify the resulting cosmological constraints. We consider two marker choices: a discrete morphology marker and a continuous morphology strength marker. The continuous marker improves the Figure of Merit (FoM) by a factor of $\sim 8.6$ relative to the standard 2PCF and reduces the $1σ$ uncertainty on $σ_8$ by a factor of $\sim 5$. The discrete marker gives a more modest FoM improvement of $\sim 17\%$. We further test the impact of tracer selection by varying the halo mass threshold by a factor of $\sim 4.5$. Even for the lowest mass threshold, the continuous marker remains unbiased and achieves a FoM about $\sim 3.4$ times higher than that of the 2PCF alone. These results show that morphology-based MCFs, combined with simulation-based emulation, provide a useful framework for extracting additional cosmological information from large-scale structure surveys.
Comments18 pages, 13 figures
