9) Is [α/Fe] bi-modality a `genetic' trait of Milky Way-like galaxies?

Abstract: The galaxy population in the universe is immutably linked to its cosmology. The characteristics of galaxies are genetic traits which are set, in a large part, by the `DNA' defined by density fluctuations in the early universe, which govern the eventual mass assembly of galaxies. Large scale surveys in the Milky Way such as Gaia, APOGEE and GALAH, among others, have revealed new and intriguing `traits' of the Milky Way. One such example is the clear bi-modality in alpha-element abundances relative to Iron at fixed Iron abundance, which exhibits itself throughout the disc of the Galaxy. Many recent works have focused on understanding and characterising this feature, and have shown that it is likely one of the most important features of the Milky Way to be understood, if we are to fully characterise its formation and evolution. Here, I will propose that the [α/Fe] bimodality in the Milky Way may be directly connected to its history of mass assembly. I will demonstrate using high-resolution simulations, which vary the assembly history of a Milky Way-like galaxy whilst holding all other conditions fixed, that this is a (near) direct predictor of a galaxy's stellar population structure in the [α/Fe] plane. This has far-reaching implications for understanding the Milky Way, but also provides a compelling motivation to search for and characterise this feature in the external galaxy population.

Bio: I am a Banting-CITA-Dunlap postdoctoral fellow at the University of Toronto, and my main interests are in the Milky Way and how we can use it as an anchor point for galaxy evolution models and theory. My work to date has focused on combining the large scale survey data for the Milky Way from surveys like APOGEE and Gaia with detailed analyses of numerical simulations such as EAGLE to unravel the origin of features of the Milky Way disc, bulge and halo. I am a co-chair of the ‘Milky Way as a Galaxy’ working group within SDSS, which seeks to use APOGEE and MaNGA data in unison and combine expertise from both surveys toward a common goal of placing the Milky Way in a cosmological context.