English

H2 chemistry in galaxy simulations: an improved supernova feedback model

Astrophysics of Galaxies 2019-01-21 v3 Cosmology and Nongalactic Astrophysics

Abstract

In this study, we present and validate a variation of recently-developed physically motivated sub-grid prescriptions for supernova feedback that account for the unresolved energy-conserving phase of the bubble expansion. Our model builds upon the implementation publicly available in the mesh-less hydrodynamic code GIZMO, and is coupled with the chemistry library KROME. Here, we test it against different setups, to address how it affects the formation/dissociation of molecular hydrogen (H2_2). First, we explore very idealised conditions, to show that it can accurately reproduce the terminal momentum of the blast-wave independent of resolution. Then, we apply it to a suite of numerical simulations of an isolated Milky Way-like galaxy and compare it with a similar run employing the delayed-cooling sub-grid prescription. We find that the delayed-cooling model, by pressurising ad-hoc the gas, is more effective in suppressing star formation. However, to get this effect, it must maintain the gas warm/hot at densities where it is expected to cool efficiently, artificially changing the thermo-chemical state of the gas, and reducing the H2_2 abundance even in dense gas. Mechanical feedback, on the other hand, is able to reproduce the H2_2 column densities without altering the gas thermodynamics, and, at the same time, drives more powerful outflows. However, being less effective in suppressing star formation, it over-predicts the Kennicutt-Schmidt relation by a factor of about 2.5. Finally, we show that the model is consistent at different resolution levels, with only mild differences.

Keywords

Cite

@article{arxiv.1808.10184,
  title  = {H2 chemistry in galaxy simulations: an improved supernova feedback model},
  author = {Alessandro Lupi},
  journal= {arXiv preprint arXiv:1808.10184},
  year   = {2019}
}

Comments

15 pages, 19 figures, accepted for publication in MNRAS (in press)

R2 v1 2026-06-23T03:48:55.286Z