Kim, Chang-Goo and Ostriker, Eve C. and Fielding, Drummond B. and Smith, Matthew C. and Bryan, Greg L. and Somerville, Rachel S. and Forbes, John C. and Genel, Shy and Hernquist, Lars (2020) A Framework for Multiphase Galactic Wind Launching Using TIGRESS. The Astrophysical Journal, 903 (2). L34. ISSN 2041-8213
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Abstract
Galactic outflows have density, temperature, and velocity variations at least as large as those of the multiphase, turbulent interstellar medium (ISM) from which they originate. We have conducted a suite of parsec-resolution numerical simulations using the TIGRESS framework, in which outflows emerge as a consequence of interaction between supernovae (SNe) and the star-forming ISM. The outflowing gas is characterized by two distinct thermal phases, cool (T ≲ 104 K) and hot (T ≳ 106 K), with most mass carried by the cool phase and most energy and newly injected metals carried by the hot phase. Both components have a broad distribution of outflow velocity, and especially for cool gas this implies a varying fraction of escaping material depending on the halo potential. Informed by the TIGRESS results, we develop straightforward analytic formulae for the joint probability density functions (PDFs) of mass, momentum, energy, and metal loading as distributions in outflow velocity and sound speed. The model PDFs have only two parameters, star formation rate surface density ${{\rm{\Sigma }}}_{\mathrm{SFR}}$ and the metallicity of the ISM, and fully capture the behavior of the original TIGRESS simulation PDFs over ${{\rm{\Sigma }}}_{\mathrm{SFR}}\in ({10}^{-4},1)\,{M}_{\odot }\,{\mathrm{kpc}}^{-2}\,{\mathrm{yr}}^{-1}$. Employing PDFs from resolved simulations will enable implementations of subgrid models for galaxy formation with wind velocity and temperature (as well as total loading factors) that are based on theoretical predictions rather than empirical tuning. This is a critical step to incorporate advances from TIGRESS and other high-resolution simulations in future cosmological hydrodynamics and semi-analytic galaxy formation models. We release a Python package to prototype our model and to ease its implementation.
Item Type: | Article |
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Subjects: | European Repository > Physics and Astronomy |
Depositing User: | Managing Editor |
Date Deposited: | 18 May 2023 04:19 |
Last Modified: | 04 Nov 2023 03:30 |
URI: | http://go7publish.com/id/eprint/2290 |