Elemental abundances in Milky Way-like galaxies from a hierarchical galaxy formation model

Abstract

We develop a new method to account for the finite lifetimes of stars and trace individual abundances within a semi-analytic model of galaxy formation. At variance with previous methods, based on the storage of the (binned) past star formation history of model galaxies, our method projects the information about the metals produced by each simple stellar population (SSP) in the future. Using this approach, an accurate accounting of the timings and properties of the individual SSPs composing model galaxies is possible. We analyse the dependence of our chemical model on various ingredients, and apply it to six simulated haloes of roughly Milky Way mass and with no massive close neighbour at z=0. For all models considered, the [Fe/H] distributions of the stars in the disc component are in good agreement with Milky Way data, while for the spheroid component (whose formation we model only through mergers) these are offset low with respect to observational measurements for the Milky Way bulge. This is a consequence of narrow star formation histories, with relatively low rates of star formation. The slow recycling of gas and energy from supernovae in our chemical model has important consequences on the predicted star formation rates, which are systematically lower than the corresponding rates in the same physical model but with an instantaneous recycling approximation. The halo that resembles most our Galaxy in terms of its global properties also reproduces the observed relation between the average metallicity and luminosity of the Milky Way satellites, albeit with a slightly steeper slope.

Building blocks of the Milky Way's accreted spheroid

“…As expected, our total spheroid's SFR values are very similar to those presented in Figure 8 in De Lucia et al (2014) who use a slightly different version of the same semianalytic code. Spheroid F looks very different between both models, but this is mainly due to the single massive progenitor galaxy mentioned above that either is counted as part of the Galactic spheroid (in our model) or not (in their model).…”

“…For instance, by making the (very rough, but common) assumption that all spheroid stars formed after a certain time T , say 1 Gyr, are significantly enriched in iron from type Ia SNe, and those before that time are α-rich, we can use Figure 8 to predict that of the six Aquarius haloes, spheroids A and C have the most dominant high-α populations, spheroids B and F the least. De Lucia et al (2014 have investigated the implementation of different delay time distributions for SN Ia explosions within a semi-analytical model that includes chemical evolution, but which is otherwise very similar to ours. They conclude that the Milky Way stellar disc metallicity distribution function is best represented for delay time distributions that are fairly broad, rather than strongly peaked at either short or intermediate delay times.…”

H2-based star formation laws in hierarchical models of galaxy formation

“…We refer to De Lucia et al (2014) for a detailed description of the relevant prescriptions. Briefly, our model includes separate sets of chemical yields for Asymptotic Giant Branch stars (AGBs) and both Supernovae Type Ia (SnIa -the main contributors of iron-peak elements) and Type II (SnII -that mainly release α elements, including O, Mg, Si, S, Ca).…”

Tracing the Evolution of High-Redshift Galaxies Using Stellar Abundances

“…Graziani et al (2015) coupled a semianalytic model of galactic chemical evolution to a radiation transfer code, enabling the self-consistent calculation of ionization radiation from stellar sources in the simulation and its interaction with the gas in star-forming regions. The ionization state and temperature of a parcel of gas can then be used as criteria for local star formation, creating an SSP thatevolves via the instantaneous recycling approximation (Tinsley 1980). De Lucia et al (2014 relax the instantaneous recycling approximation by treating the stellar component of their simulation as a collection of SSPs to allow for feedback from stars to occur over a range of times following star formation, as well as to investigate the impact of the SN Ia delay time distribution on the chemical evolution of a Milky-Way-like galaxy.…”

“…Our model goes beyond their scheme, tracking many more elementsand calculating time-dependent yields for each SSP in the simulation, returning different amounts of material at different stages in the evolution of the stellar population. De Lucia et al (2014), on the other hand, return a uniform, timeaveraged fraction of the total ejecta of the SSP over the course of its life.…”