Systematic difference between ionized and molecular gas velocity dispersion in $z\sim1-2$ disks and local analogues

TL;DR

This study reveals a systematic difference between molecular and ionized gas velocity dispersions in galaxies at redshift 1-2, showing ionized gas overestimates turbulence and affecting galaxy stability and pressure estimates.

Contribution

It provides the first direct comparison of molecular and ionized gas velocity dispersions in high-redshift galaxy analogues, highlighting the importance of using molecular gas for accurate kinematic measurements.

Findings

Ionized gas velocity dispersion is about 2.45 times higher than molecular gas.

Using molecular gas yields lower pressure estimates by ~0.22 dex.

Simulations overestimate molecular gas velocity dispersion at high redshift.

Abstract

We compare the molecular and ionized gas velocity dispersion of 9 nearby turbulent disks, analogues to high-redshift galaxies, from the DYNAMO sample using new ALMA and GMOS/Gemini observations. We combine our sample with 12 galaxies at $z\sim $0.5-2.5 from the literature. We find that the resolved velocity dispersion is systematically lower by a factor $2.45\pm0.38$ for the molecular gas compared to the ionized gas, after correcting for thermal broadening. This offset is constant within the galaxy disks and indicates the co-existence of a thin molecular and thick ionized gas disks. This result has a direct impact on the Toomre $Q$ and pressure derived in galaxies. We obtain pressures $\sim0.22$ dex lower on average when using the molecular gas velocity dispersion, $\sigma_{0,mol}$. We find that $\sigma_{0,mol}$ increases with gas fraction and star formation rate. We also obtain an increase with redshift and show that the EAGLE and FIRE simulations overall overestimate $\sigma_{0,mol}$ at high redshift. Our results suggest that efforts to compare the kinematics of gas using ionized gas as a proxy for the total gas may overestimate the velocity dispersion by a significant amount in galaxies at the peak of cosmic star formation. When using the molecular gas as a tracer, our sample is not consistent with predictions from constant efficiency star formation models, even when including transport as a source of turbulence. Feedback models with variable star formation efficiency, $\epsilon_{ff}$, and/or feedback efficiency, $p_*/m_*$, better predict our observations.