What FIREs up star formation: the emergence of the Kennicutt–Schmidt law from feedback

Abstract

We present an analysis of the global and spatially-resolved Kennicutt-Schmidt (KS) star formation relation in the FIRE (Feedback In Realistic Environments) suite of cosmological simulations, including halos with z = 0 masses ranging from 10 10 -10 13 M . We show that the KS relation emerges and is robustly maintained due to the effects of feedback on local scales regulating star-forming gas, independent of the particular small-scale star formation prescriptions employed. We demonstrate that the time-averaged KS relation is relatively independent of redshift and spatial averaging scale, and that the star formation rate surface density is weakly dependent on metallicity and inversely dependent on orbital dynamical time. At constant star formation rate surface density, the 'Cold & Dense' gas surface density (gas with T < 300 K and n > 10 cm −3 , used as a proxy for the molecular gas surface density) of the simulated galaxies is ∼0.5 dex less than observed at ∼kpc scales. This discrepancy may arise from underestimates of the local column density at the particle-scale for the purposes of shielding in the simulations. Finally, we show that on scales larger than individual giant molecular clouds, the primary condition that determines whether star formation occurs is whether a patch of the galactic disk is thermally Toomreunstable (not whether it is self-shielding): once a patch can no longer be thermally stabilized against fragmentation, it collapses, becomes self-shielding, cools, and forms stars, regardless of epoch or environment.

Interacting galaxies on FIRE-2: the connection between enhanced star formation and interstellar gas content

“…• Cold-dense gas (connection to observations): Our simulations predict that close interactions elevate colddense gas mass content in galaxies during the galaxy-pair period (median ∼18 % increase - Figure 9, lower-left panel). If we follow other published works in the literature (e.g., Bournaud et al 2015;Orr et al 2018) and treat our colddense regime is a proxy for molecular gas, our results are qualitatively in line with observations. Using a survey of CO(1-0) and CO(2-1) observations with the IRAM 30 meter telescope, Braine & Combes (1993) finds that CO luminosity is enhanced in tidally disturbed galaxies.…”

“…Meanwhile, incipient work aimed to validate our FIRE-2 simulations against the ISM in real galaxies has been conducted already. Orr et al (2018) demonstrate that their treatment of HI and H2 gas yields reasonable agreement with the observed Kennicutt Law (Kennicutt 1998;Kennicutt & Evans 2012). Guszejnov et al (2017) Exporting these methods to our galaxy mergers is in the plans.…”

Variations in the slope of the resolved star-forming main sequence: a tool for constraining the mass of star-forming regions

“…Conversely, relationships that use quantities that probe similar scales (such as the Kennucutt-Schmidt law) should not be strongly affected by resolution. Indeed, Orr et al (2018) report that the Kennicutt-Schmidt law does not depend on resolution over a similar resolution range as studied in this work.…”

A simple non-equilibrium feedback model for galaxy-scale star formation: delayed feedback and SFR scatter

“…This large scatter could suggest that we are still missing some critical physics in our models, or observationally our inferred star formation rates and gas surface densities are introducing much larger errors than usually appreciated. From the side of theory, that we are roughly matching star formation rate distributions, and their scatter in particular, in cosmological simulations is heartening (Orr et al 2018) and suggests the feedback physics included in simulations like those of Hopkins et al (2014Hopkins et al ( , 2018a or Agertz & Kravtsov (2015) are close to sufficient. On the side of observations, there remains work to be done in converging on conversion factors between luminosities or line widths, and star formation rates and gas masses but it is unlikely that these factors randomly vary by ∼ 2 dex in neighboring kpc-patches of ISM (Kennicutt & Evans 2012;Narayanan et al 2012;Bolatto et al 2013).…”