论文标题
美元
${\rm S{\scriptsize IM}BIG}$: Mock Challenge for a Forward Modeling Approach to Galaxy Clustering
论文作者
论文摘要
基于仿真的星系推理（$ {\ rm s {\ scriptSize im} big} $）是一个前向建模框架，用于使用基于仿真的推断分析星系聚类。在这项工作中，我们介绍了$ {\ rm s {\ scriptSize im} big} $ forward模型，该模型旨在匹配观察到的SDSS-III BOSS CMASS GALAXY样本。正向模型基于高分辨率$ {\ rm q {\ scriptsize uijote}} $ $ $ $ n $ body-body模拟和灵活的光晕职业模型。它包括完整的调查现实主义和模型观察系统学，例如角膜掩盖和纤维碰撞。我们提出了“模拟挑战”，以使用$ {\ rm s {\ rm s {\ scriptsize im} big} $推断的后词的准确性，使用1,500个使用具有不同$ n $ n $ simulation，halo Finder和halo职业处方的前向模型构建的1,500个测试模拟。作为$ {\ rm s {\ scriptSize im} big} $的演示，我们将功率谱多摩尔分析为$ k _ {\ rm max} = 0.5 \，h/{\ rm mpc} $，并推断出$ CDM COSMOLICATIOG和HALO的后验。根据模拟挑战，我们发现我们对$ω_m$和$σ_8$的约束是公正的，但保守的。因此，模拟挑战表明，$ {\ rm s {\ scriptsize im} big} $提供了一个可靠的框架，用于从非线性尺度上的星系聚类中推断宇宙学参数，以及用于处理观测系统的完整框架。在随后的工作中，我们将使用$ {\ rm s {\ scriptSize im} big} $分析摘要统计信息，包括BISPECTRUM，标记的功率谱，偏斜频谱，小波统计量和现场级统计。
Simulation-Based Inference of Galaxies (${\rm S{\scriptsize IM}BIG}$) is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work, we present the ${\rm S{\scriptsize IM}BIG}$ forward model, which is designed to match the observed SDSS-III BOSS CMASS galaxy sample. The forward model is based on high-resolution ${\rm Q{\scriptsize UIJOTE}}$ $N$-body simulations and a flexible halo occupation model. It includes full survey realism and models observational systematics such as angular masking and fiber collisions. We present the "mock challenge" for validating the accuracy of posteriors inferred from ${\rm S{\scriptsize IM}BIG}$ using a suite of 1,500 test simulations constructed using forward models with a different $N$-body simulation, halo finder, and halo occupation prescription. As a demonstration of ${\rm S{\scriptsize IM}BIG}$, we analyze the power spectrum multipoles out to $k_{\rm max} = 0.5\,h/{\rm Mpc}$ and infer the posterior of $Λ$CDM cosmological and halo occupation parameters. Based on the mock challenge, we find that our constraints on $Ω_m$ and $σ_8$ are unbiased, but conservative. Hence, the mock challenge demonstrates that ${\rm S{\scriptsize IM}BIG}$ provides a robust framework for inferring cosmological parameters from galaxy clustering on non-linear scales and a complete framework for handling observational systematics. In subsequent work, we will use ${\rm S{\scriptsize IM}BIG}$ to analyze summary statistics beyond the power spectrum including the bispectrum, marked power spectrum, skew spectrum, wavelet statistics, and field-level statistics.
