Star formation history of galaxies from z=0 to z=0.7 A backward approach to the evolution of star-forming galaxies

Details Star formation history of galaxies from z=0 to z=0.7 A backward approach to the evolution of star-forming galaxies Star formation history of galaxies from z=0 to z=0.7 A backward approach to the evolution of star-forming galaxies

2008-03-04

arxiv.org/abs/0803.0414v1

Astronomy and Astrophysics

Astrophysics

14 pages, 10 figures. accepted for publication in Astronomy & Astrophysics

Scientific paper

10.1051/0004-6361:20078263

We investigate whether the mean star formation activity of star-forming galaxies from z=0 to z=0.7 in the GOODS-S field can be reproduced by simple evolution models of these systems. In this case, such models might be used as first order references for studies at higher z to decipher when and to what extent a secular evolution is sufficient to explain the star formation history in galaxies. We selected star-forming galaxies at z=0 and at z=0.7 in IR and in UV to have access to all the recent star formation. We focused on galaxies with a stellar mass ranging between 10^{10} and 10^{11} M_sun for which the results are not biased by the selections. We compared the data to chemical evolution models developed for spiral galaxies and originally built to reproduce the main characteristics of the Milky Way and nearby spirals without fine-tuning them for the present analysis. We find a shallow decrease in the specific star formation rate (SSFR) when the stellar mass increases. The evolution of the SSFR characterizing both UV and IR selected galaxies from z=0 to z=0.7 is consistent with the models built to reproduce the present spiral galaxies. There is no need to strongly modify of the physical conditions in galaxies to explain the average evolution of their star formation from z=0 to z=0.7. We use the models to predict the evolution of the star formation rate and the metallicity on a wider range of redshift and we compare these predictions with the results of semi-analytical models.

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