Probing star formation across cosmic time with absorption line systems

TL;DR

This paper establishes a strong empirical link between MgII absorption systems and star formation, demonstrating that absorption line data can trace the universe's star formation history up to redshift 2 without dust bias.

Contribution

It introduces a novel method connecting MgII absorbers with star formation rates, revealing their potential as dust-unbiased probes of cosmic star formation history.

Findings

A 15 sigma correlation between MgII equivalent width and OII luminosity.

MgII absorbers account for a significant fraction of the universe's star formation.

High covering factor of cold gas around star-forming galaxies, suggesting outflows.

Abstract

We present an empirical connection between cold gas in galactic halos and star formation. Using a sample of more than 8,500 MgII absorbers from SDSS quasar spectra, we report the detection of a 15 sigma correlation between the rest equivalent width W0 of MgII absorbers and the associated OII luminosity, an estimator of star formation rate. This correlation has interesting implications: using only observable quantities we show that MgII absorbers trace a substantial fraction of the global OII luminosity density and recover the overall star formation history of the Universe derived from classical emission estimators up to z~2. We then show that the distribution function of MgII rest equivalent widths, dN/dW0 inherits both its shape and amplitude from the OII luminosity function Phi(L). These distributions can be naturally connected, without any free parameter. Our results imply a high covering factor of cold gas around star forming galaxies: C>0.5, favoring outflows as the mechanism responsible for MgII absorption. We then argue that intervening MgII absorbers and blue-shifted MgII absorption seen in the spectra of star forming galaxies are essentially the same systems. These results not only shed light on the nature of MgII absorbers but also provide us with a new probe of star formation, in absorption, i.e. in a way which does not suffer from dust extinction and with a redshift-independent sensitivity. As shown in this analysis, such a tool can be applied in a noise-dominated regime, i.e. using a dataset for which emission lines are not detected in individual objects. This is of particular interest for high redshift studies.