Final Report Summary - STGDELUCIA2007 (Galaxies through the cosmic ages: the role of primordial conditions and environmental effects)
During the last decades, astronomers have discovered that only about 4% of the matter in the Universe is made of baryonic matter out of which stars and galaxies are made. About 21% is made of a non-baryonic form of (dark) matter that has yet to be detected in the laboratory. The remaining ~75% is made of a mysterious form of dark energy that permeates the Universe and increases its expansion rate. In this scenario, cosmic structures are believed to form in a ‘bottom-up’ fashion, with small systems like galaxies and groups of galaxies forming first and later merging into more massive structures like clusters of galaxies. Although the nature of both dark energy and dark matter remain to be understood, different experiments have led to extremely precise measurements of the cosmological parameters, setting the scenery for the formation of the baryonic matter we observe. Yet, how galaxies form and evolve is one of the main unsolved problems of modern astrophysics.
The observed properties of galaxies have long been known to depend on the environment in which they are located. The physical origin of the observed environmental trends is, however, still subject to debate. Much of the argument centers on whether these trends are the end product of physical processes that have come into play after the galaxies have become part of groups or clusters (the “nurture” hypothesis) or whether they are established before the accretion on more massive systems, due to galaxy formation proceeding differently in different environments (the “nature” hypothesis). This project aimed to understand the origin of the observed physical properties of galaxies and their dependence on the environment, as a function of cosmic time. The main achievements obtained in the framework of the funded project are:
-- We have provided a detailed characterizations of the problems and/or limits of current galaxy formation models, using a detailed comparison between observational data and predictions from different and independently developed models. This systematic comparison has also allowed us to identify specific directions for improvements. While an improvement of the treatment of satellite galaxies' evolution appears necessary (and indeed gives results in better agreement with data), we argue that the main limitations of our current models lies in our treatment of the "self-regulation" between star formation and feedback.
-- We have analysed and quantified the "environmental history" of galaxies currently residing in groups and clusters. As we argued in the original proposal, this is a crucial missing ingredients for the interpretation of observational data in a hierarchical context. This analysis has allowed us to identify a critical environment for galaxy evolution (that is that of groups with mass ~10^13 Msun) and typical time-scales (that are of the order of 5-7 Gyr) for galaxy evolution in dense environments.
-- We have carried out the first detailed controlled N-body simulations of the evolution of disk galaxies in groups. In particular, we have quantified the relative role of the tidal field and low-velocity close encounters in these environments and found that the former plays a dominant role. These simulations have been used to improve our galaxy formation models.
Using results from the research projects carried out in the past five years, we have updated our galaxy formation model. Model predictions are being used in the framework of different international collaborations, and we are now in the process of making them publicly available.
The observed properties of galaxies have long been known to depend on the environment in which they are located. The physical origin of the observed environmental trends is, however, still subject to debate. Much of the argument centers on whether these trends are the end product of physical processes that have come into play after the galaxies have become part of groups or clusters (the “nurture” hypothesis) or whether they are established before the accretion on more massive systems, due to galaxy formation proceeding differently in different environments (the “nature” hypothesis). This project aimed to understand the origin of the observed physical properties of galaxies and their dependence on the environment, as a function of cosmic time. The main achievements obtained in the framework of the funded project are:
-- We have provided a detailed characterizations of the problems and/or limits of current galaxy formation models, using a detailed comparison between observational data and predictions from different and independently developed models. This systematic comparison has also allowed us to identify specific directions for improvements. While an improvement of the treatment of satellite galaxies' evolution appears necessary (and indeed gives results in better agreement with data), we argue that the main limitations of our current models lies in our treatment of the "self-regulation" between star formation and feedback.
-- We have analysed and quantified the "environmental history" of galaxies currently residing in groups and clusters. As we argued in the original proposal, this is a crucial missing ingredients for the interpretation of observational data in a hierarchical context. This analysis has allowed us to identify a critical environment for galaxy evolution (that is that of groups with mass ~10^13 Msun) and typical time-scales (that are of the order of 5-7 Gyr) for galaxy evolution in dense environments.
-- We have carried out the first detailed controlled N-body simulations of the evolution of disk galaxies in groups. In particular, we have quantified the relative role of the tidal field and low-velocity close encounters in these environments and found that the former plays a dominant role. These simulations have been used to improve our galaxy formation models.
Using results from the research projects carried out in the past five years, we have updated our galaxy formation model. Model predictions are being used in the framework of different international collaborations, and we are now in the process of making them publicly available.