The Auriga Stellar Haloes: Connecting stellar population properties with accretion and merging history
Antonela Monachesi, Facundo A. G\'omez, Robert J. J. Grand, Christine, M. Simpson, Guinevere Kauffmann, Sebasti\'an Bustamante, Federico Marinacci,, R\"udiger Pakmor, Volker Springel, Carlos S. Frenk, Simon D. M. White, and, Patricia B. Tissera

TL;DR
This study uses high-resolution simulations to analyze the properties of stellar haloes in Milky Way-like galaxies, revealing their diversity and connection to galaxy assembly history, with implications for interpreting observations.
Contribution
It provides a detailed comparison between simulated and observed stellar haloes, linking halo properties to accretion and merger histories, and demonstrating the predictive power of simulations.
Findings
Simulated haloes show diverse properties consistent with observations.
Halo metallicity gradients relate to the number of significant progenitors.
The halo mass-metallicity relation is driven by dominant satellite properties.
Abstract
We examine the stellar haloes of the Auriga simulations, a suite of thirty cosmological magneto-hydrodynamical high-resolution simulations of Milky Way-mass galaxies performed with the moving-mesh code AREPO. We study halo global properties and radial profiles out to kpc for each individual galaxy. The Auriga haloes are diverse in their masses and density profiles; mean metallicity and metallicity gradients; ages; and shapes, reflecting the stochasticity inherent in their accretion and merger histories. A comparison with observations of nearby late-type galaxies shows very good agreement between most observed and simulated halo properties. However, Auriga haloes are typically too massive. We find a connection between population gradients and mass assembly history: galaxies with few significant progenitors have more massive haloes, possess large negative halo metallicity…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
