A multi-tracer empirically-driven approach to line-intensity mapping lightcones

TL;DR

This paper introduces SkyLine, a simulation framework for realistic line-intensity mapping observations, enabling better understanding of signals, contaminants, and cross-correlations to enhance future large-scale structure studies.

Contribution

It presents SkyLine, a novel computational tool for generating realistic mock LIM observations with observational features and foregrounds, aiding analysis and strategy development.

Findings

Simulated LIM maps for multiple emission lines and their cross-correlations.

Quantified the impact of foregrounds, interlopers, and noise on LIM signals.

Explored cross-correlations with extragalactic tracers like CIB and tSZ.

Abstract

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-$\alpha$, 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.