Abundance gradients in the Milky Way for α elements, iron peak elements, barium, lanthanum, and europium

Abstract

We model the abundance gradients in the disk of the Milky Way for several chemical elements (O, Mg, Si, S, Ca, Se, Ti, Co, V, Fe, Ni, Zn, Cu, Mn, Cr, Ba, La and Eu), and compare our results with the most recent and homogeneous observational data. We adopt a chemical evolution model able to well reproduce the main properties of the solar vicinity. The model assumes that the disk formed inside-out with a timescale for the formation of the thin disk of 7 Gyr in the solar vicinity, whereas the halo formed on a timescale of 0.8 Gyr. We adopt new empirical stellar yields derived to best fit the abundances and the abundance ratios in the solar vicinity. We compute, for the first time, the abundance gradients for all the mentioned elements in the galactocentric distance range 4-22 kpc. Comparison with the observed data on Cepheids in the galactocentric distance range 5-17 kpc gives a very good agreement for many of the studied elements. In addition, we well fit the data for the evolution of lanthanum in the solar vicinity, for which we present results here for the first time. We explore, also for the first time, the behavior of the abundance gradients at large galactocentric distances by comparing our results with data relative to distant open clusters and red giants and select the best chemical evolution model on that basis. We find a very good fit to the observed abundance gradients, as traced by Cepheids, for most of the elements, thus confirming the validity of the inside-out scenario for the formation of the Milky Way disk as well as the adopted nucleosynthesis prescriptions. The flat gradients at large galactocentric distances (>12 kpc), as traced by the Cepheids, open cluster and red giant data, lead us to conclude that a model where the density of the halo stellar component is constant in the inner 20 kpc should be preferred. Other models with different distributions of the halo stellar mass do not produce a good fit of the data. © ESO 2007.