Simulating the formation and evolution of galaxies: multi-phase description of the interstellar medium, star formation, and energy feedback - Merlin, E.; Chiosi, C. (Astronomy and astrophysics (Berlin), 2007)
Context.Modelling the gaseous component of the interstellar medium (ISM) by Smoothed Particles Hydrodynamics in N-Body simulations (NB-TSPH) is still very crude when compared to the complex real situation. In the real ISM, many different and almost physically decoupled components (phases) coexist for long periods of time, and since they spread over wide ranges of density and temperature, they cannot be correctly represented by a unique continuous fluid. This would influence star formation which is thought to take place in clumps of cold, dense, molecular clouds, embedded in a warmer, neutral medium, that are almost freely moving throughout the tenuous hot ISM. Therefore, assuming that star formation is simply related to the gas content without specifying the component in which this is both observed and expected to occur may not be physically sound. Aims.We consider a multi-phase representation of the ISM in NB-TSPH simulations of galaxy formation and evolution with particular attention to the case of early-type galaxies. Methods.Cold gas clouds are described by the so-called sticky particles algorithm. They can freely move throughout the hot ISM medium; stars form within these clouds and the mass exchange among the three baryonic phases (hot gas, cold clouds, stars) is governed by radiative and Compton cooling and energy feedback by supernova (SN) explosions, stellar winds, and UV radiation. We also consider thermal conduction, cloud-cloud collisions, and chemical enrichment. Results.Our model agrees with and improves upon previous studies on the same subject. The results for the star formation rate agree with recent observational data on early-type galaxies. Conclusions.These models lend further support to the revised monolithic scheme of galaxy formation, which has recently been strengthened by high redshift data leading to the so-called downsizing and top-down scenarios.