paper

Infrared fine-structure lines at high redshift

arXiv:2509.19444 · doi:10.1007/s00159-025-00162-7

Abstract

Infrared (IR) fine-structure line (FSL) emission arises from the radiative de-excitation of collisionally-excited electrons in atoms and ions. Thanks to their high luminosities and relatively simple physics, IR FSLs have quickly become the workhorse for studying the formation and evolution of galaxies in the nearby and distant Universe. In this review, we introduce the physics of FSL emission and the diagnostics of the ISM that we can derive from them via first principle arguments. We summarize the history of FSL observations with a focus on the far-IR wavelengths and a particular emphasis on the on-going efforts aimed at characterizing galaxies at cosmic noon and beyond. We explore the dependence of emission line trends, such as those observed in `line deficits' or [CII]-SFR relations, as a function of redshift and galaxy types. Once selection biases are controlled for, IR FSLs are a powerful tool to constrain the physics of galaxies. The precise redshift information inferred from fine-structure line observations have enabled tracing their ISM properties across cosmic reionization. FSL observations have also led to estimates of the mass of different ISM phases, and of the SFR of distant galaxies. It is thanks to IR FSL observations that we have been able to measure the internal dynamics of high-z galaxies, which in turns has allowed us to test, e.g., the onset of black hole - host galaxy relations in the first billion years of the Universe and the presence of gas outflows associated with the baryon cycle in galaxies. Finally, FSLs have provided important clues on the physics of the ISM in the most distant galaxies known to date. We demonstrate the strength and limitations of using IR FSLs to advance our understanding of galaxy formation and evolution in the early universe, and we outline future perspective for the field.

Published in A&ARv. The data compilation and related software are available here: https://github.com/tdiazsantos/fslcat/

References in corpus (192)

Cited by in corpus (4)