一种面向线强度映射光锥的多示踪剂经验驱动方法
A multi-tracer empirically-driven approach to line-intensity mapping lightcones
AI总结：
研究提出SkyLine计算框架，结合MultiDark Planck 2模拟和UniverseMachine模型生成包含观测特征与污染的真实线强度映射（LIM）光锥，并量化了多种发射线及河外示踪剂的功率谱与互相关，为未来LIM巡天信息提取与污染控制提供关键模拟工具。
摘要：
线强度映射（LIM）是一种探测宇宙大尺度结构的新兴技术。通过观测特定谱线的积分强度，它捕获来自所有源的辐射，并对驱动星系演化的天体物理过程十分敏感。将这些过程与潜在的暗物质分布联系起来会带来观测和理论上的挑战，如观测污染和高度非高斯场，这促使人们使用模拟来更好地表征信号。在本研究中，我们提出了 SkyLine，这是一个用于生成真实模拟 LIM 观测的计算框架，包含观测特征、前景污染以及各种自洽的示踪剂目录。我们应用该框架，结合 MultiDark Planck 2 模拟和 UniverseMachine 星系形成模型，生成了 LIM 地图的实现。我们通过探究体素强度分布以及 21 cm、CO、CII 和 Lyman-$α$ 等发射线的功率谱、它们之间的互相关，以及与星系团集的互相关，展示了该方案的潜力。我们还额外展示了 LIM 与亚毫米河外大尺度结构示踪剂（如宇宙红外背景和热 Sunyaev-Zel'dovich 效应）之间的互相关，并量化了银河系前景、谱线干扰源和仪器噪声对 LIM 观测的影响。这些模拟产物对于在未来十年量化 LIM 巡天及其互相关的真实信息含量，以及制定克服污染物影响并最大化 LIM 实验科学回报的策略至关重要。
英文摘要：
Line-intensity mapping (LIM) is an emerging technique to probe the large-scale structure of the Universe. By targeting the integrated intensity of specific spectral lines, it captures the emission from all sources and is sensitive to the astrophysical processes that drive galaxy evolution. Relating these processes to the underlying distribution of matter introduces observational and theoretical challenges, such as observational contamination and highly non-Gaussian fields, which motivate the use of simulations to better characterize the signal. In this work we present SkyLine, a computational framework to generate realistic mock LIM observations that include observational features and foreground contamination, as well as a variety of self-consistent tracer catalogs. We apply our framework to generate realizations of LIM maps from the MultiDark Planck 2 simulations coupled to the UniverseMachine galaxy formation model. We showcase the potential of our scheme by exploring the voxel intensity distribution and the power spectrum of emission lines such as 21 cm, CO, CII, and Lyman-$α$, their mutual cross-correlations, and cross-correlations with galaxy clustering. We additionally present cross-correlations between LIM and sub-millimeter extragalactic tracers of large-scale structure such as the cosmic infrared background and the thermal Sunyaev-Zel'dovich effect, as well as quantify the impact of galactic foregrounds, line interlopers and instrument noise on LIM observations. These simulated products will be crucial in quantifying the true information content of LIM surveys and their cross-correlations in the coming decade, and to develop strategies to overcome the impact of contaminants and maximize the scientific return from LIM experiments.
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