LIMFAST. II. Line Intensity Mapping as a Probe of High-redshift Galaxy Formation

Abstract

The epoch of reionization (EoR) offers a unique window into the dawn of galaxy formation, through which high-redshift galaxies can be studied by observations of both themselves and their impact on the intergalactic medium. Line intensity mapping (LIM) promises to explore cosmic reionization and its driving sources by measuring intensity fluctuations of emission lines tracing the cosmic gas in varying phases. Using LIMFAST, a novel seminumerical tool designed to self-consistently simulate LIM signals of multiple EoR probes, we investigate how building blocks of galaxy formation and evolution theory, such as feedback-regulated star formation and chemical enrichment, might be studied with multitracer LIM during the EoR. On galaxy scales, we show that the star formation law and the feedback associated with star formation can be indicated by both the shape and redshift evolution of LIM power spectra. For a baseline model of metal production that traces star formation, we find that lines highly sensitive to metallicity are generally better probes of galaxy formation models. On larger scales, we demonstrate that inferring ionized bubble sizes from cross-correlations between tracers of ionized and neutral gas requires a detailed understanding of the astrophysics that shape the line luminosity–halo mass relation. Despite various modeling and observational challenges, wide-area, multitracer LIM surveys will provide important high-redshift tests for the fundamentals of galaxy formation theory, especially the interplay between star formation and feedback by accessing statistically the entire low-mass population of galaxies as ideal laboratories, complementary to upcoming surveys of individual sources by new-generation telescopes.

LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths

“…There are other packages available for modeling the LIM signal, similar to LIMpy. One such package is the seminumerical tool LIMFAST (Mas-Ribas et al 2022;Sun et al 2023), which can be used to model various signals including [O II], [O III], Lyα, Hα, Hβ, and 21 cm. Apart from that, the THESAN simulation suite models the various line intensity maps on a large volume box during the epoch of reionization (Kannan et al 2022).…”

“…These methods incorporate observational data to infer the parameters that best describe the underlying astrophysical processes. mechanisms that govern the star formation process in galaxies and their dependence on halo mass and redshift is crucial for developing a comprehensive picture of galaxy formation and evolution (Sun et al 2023). For simplicity and optimization purposes, we use the mean SFR-M halo relation to estimate the multiline luminosities, ignoring the dependencies of other astrophysical parameters related to the complex SFH in halos.…”

“…Detecting the power spectra of fine structure lines, such as [C II] and [O III], at high redshift (z  6) has the potential to reveal the sources of reionization and their clustering properties (Dumitru et al 2019;Padmanabhan 2019;Karoumpis et al 2022;Padmanabhan et al 2022;Sun et al 2023). Furthermore, mapping the Universe using various rotational transitions of CO (J-level transition) can probe the formation of structures at high redshifts, offering insights into the process of reionization and the SFH of the first-generation galaxies (Kovetz et al 2017;Breysse et al 2022).…”

Constraining the halo-ISM connection through multi-transition carbon monoxide line-intensity mapping

“…Yet previous literature forecasting CO LIM signals at z ≳ 6 [9,[33][34][35][36] leans towards either modelling only a single CO transition, or applying empirical halo models for multiple CO transitions that ultimately abstract away many of the physical variables governing CO excitation in dense gas. That said, some works have constructed modelling frameworks for LIM observables encompassing multiple lines based on explicit, self-consistent physical approaches (e.g., [37][38][39][40][41]). For quite possibly the first time, we move beyond even those works to present a detailed consideration of recoverability of ISM environmental variables specifically from multi-transition CO LIM.…”

State-of-art Simulations and Observations for Star Formation

“…During ~1-2, the density of star formation rate in the universe reached its peak in ~1-2, and gradually decreased with the passage of time. There are two main influencing factors: bright red galaxies (LIRG, LIR>10 11 L⊙) or extremely bright infrared galaxies (ULIRGs, LIR>10 12 L⊙) [3]. This type of galaxy is rare in the low redshift universe, but in ~1-2, its density increases sharply, its star formation rate is greater than 10 M⊙yr-1, and there are mergers and remnants [4].…”