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Accepted manuscript

DARK SAGE: Next-generation semi-analytic galaxy evolution with multidimensional structure and minimal free parameters

Published online by Cambridge University Press:  27 February 2024

Adam R. H. Stevens
Affiliation:
International Centre for Radio Astronomy Research, The University of Western Australia, Crawley, WA 6009, Australia Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
Manodeep Sinha
Affiliation:
Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Alexander Rohl
Affiliation:
School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, SA 5000, Australia Department of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009, Australia
Mawson W. Sammons
Affiliation:
International Centre for Radio Astronomy Research, Curtin University, Bentley, WA 6102, Australia
Boryana Hadzhiyska
Affiliation:
Miller Institute for Basic Research in Science, University of California, Berkeley, CA 94720, USA Physics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
César Hernández-Aguayo
Affiliation:
Max-Planck-Institut für Astrophysik, D-85741 Garching, Bayern, Germany
Lars Hernquist
Affiliation:
Institute for Theory and Computation, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA

Abstract

After more than five years of development, we present a new version of Dark Sage, a semi-analytic model (SAM) of galaxy formation that breaks the mould for models of its kind. Included among the major changes is an overhauled treatment of stellar feedback that is derived from energy conservation, operates on local scales, affects gas gradually over time rather than instantaneously, and predicts a mass-loading factor for every galaxy. Building on the model’s resolved angularmomentum structure of galaxies, we now consider the heating of stellar discs, delivering predictions for disc structure both radially and vertically. We add a further dimension to stellar discs by tracking the distribution of stellar ages in each annulus. Each annulus–age bin has its own velocity dispersion and metallicity evolved in the model. This allows Dark Sage to make structural predictions for galaxies that previously only hydrodynamic simulations could. We present the model as run on the merger trees of the highest-resolution gravity-only simulation of the MillenniumTNG suite. Despite its additional complexity relative to other SAMs, Dark Sage only has three free parameters, the least of any SAM, which we calibrate exclusively against the cosmic star formation history and the z=0 stellar and Hi mass functions using a particle-swarm optimisation method. The Dark Sage codebase, written in C and python, is publicly available at https://github.com/arhstevens/DarkSage.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of the Astronomical Society of Australia

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