Mon. Not. R. Astron. Soc., 482, 1304-1329 (2019/January-1)
Simulating an isolated dwarf galaxy with multichannel feedback and chemical yields from individual stars.
EMERICK A., BRYAN G.L. and MAC LOW M.-M.
Abstract (from CDS):
In order to better understand the relationship between feedback and galactic chemical evolution, we have developed a new model for stellar feedback at grid resolutions of only a few parsecs in global disc simulations, using the adaptive mesh refinement hydrodynamics code ENZO. For the first time in galaxy-scale simulations, we simulate detailed stellar feedback from individual stars including asymptotic giant branch winds, photoelectric heating, Lyman-Werner radiation, ionizing radiation tracked through an adaptive ray-tracing radiative transfer method, and core-collapse and Type Ia supernovae. We furthermore follow the star-by-star chemical yields using tracer fields for 15 metal species: C, N, O, Na, Mg, Si, S, Ca, Mn, Fe, Ni, As, Sr, Y, and Ba. We include the yields ejected in massive stellar winds, but greatly reduce the winds' velocities due to computational constraints. We describe these methods in detail in this work and present the first results from 500 Myr of evolution of an isolated dwarf galaxy with properties similar to a Local Group, low-mass dwarf galaxy. We demonstrate that our physics and feedback model is capable of producing a dwarf galaxy whose evolution is consistent with observations in both the Kennicutt-Schmidt relationship and extended Schmidt relationship. Effective feedback drives outflows with a greater metallicity than the interstellar medium (ISM), leading to low metal retention fractions consistent with observations. Finally, we demonstrate that these simulations yield valuable information on the variation in mixing behaviour of individual metal species within the multiphase ISM.
© 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society
hydrodynamics - ISM: abundances - galaxies: dwarf - galaxies: evolution - galaxies: ISM
View the reference in ADS
To bookmark this query, right click on this link: simbad:2019MNRAS.482.1304E and select 'bookmark this link' or equivalent in the popup menu