no code implementations • 25 Nov 2020 • Luis Fernando Machado Poletti Valle, Camille Avestruz, David J. Barnes, Arya Farahi, Erwin T. Lau, Daisuke Nagai
In this study we explore a machine learning approach for modelling the dependence of gas shapes on dark matter and baryonic properties.
Cosmology and Nongalactic Astrophysics
no code implementations • 7 Jan 2020 • Dhayaa Anbajagane, August E. Evrard, Arya Farahi, David J. Barnes, Klaus Dolag, Ian G. McCarthy, Dylan Nelson, Annalisa Pillepich
The highest resolution simulations find $\gamma \simeq -0. 8$ for the $z=0$ shape of $p(\ln M_{\star,\rm BCG}\,|\, M_{\rm halo}, z)$ and also that the fractional scatter in total stellar mass is below $10\%$ in halos more massive than $10^{14. 3} M_{\odot}$.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics
no code implementations • 19 Oct 2018 • Thomas J. Armitage, Scott T. Kay, David J. Barnes
While the weak lensing masses can be recovered with a similar scatter to that when training on the true mass, the hydrostatic mass suffers from significantly higher scatter of ${\simeq} 0. 13$ dex (${\simeq} 35$ per cent).
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies
