Related papers: Automated Simulations of Galaxy Morphology Evoluti…
Globular cluster systems provide valuable fossil records of the formation history of their parent galaxies. This review specifically concentrates on using color distributions of the globular cluster systems of elliptical galaxies to…
Understanding morphological types of galaxies is a key parameter for studying their formation and evolution. Neural networks that have been used previously for galaxy morphology classification have some disadvantages, such as not being…
Cosmological simulations are the key tool for investigating the different processes involved in the formation of the universe from small initial density perturbations to galaxies and clusters of galaxies observed today. The identification…
We use sparse regression methods (SRM) to build accurate and explainable models that predict the stellar mass of central and satellite galaxies as a function of properties of their host dark matter halos. SRM are machine learning algorithms…
It is now possible for hydrodynamical simulations to reproduce a representative galaxy population. Accordingly, it is timely to assess critically some of the assumptions of traditional semi-analytic galaxy formation models. We use the Eagle…
In star forming regions, we can observe different evolutionary stages of various objects and phenomena such as molecular clouds, protostellar jets and outflows, circumstellar disks, and protostars. However, it is difficult to directly…
A review of the present observational and theoretical status of elliptical galaxies is presented with the aim to clarify whether the monolithic or the hierarchical, is a more viable scenario for the origin of these structures. We describe…
Hierarchical structure formation theory is based on the notion that mergers drive galaxy evolution, so a considerable framework of semi-analytic models and N-body simulations has been constructed to calculate how mergers transform a growing…
We simulate the formation and chemodynamical evolution of 124 elliptical galaxies by using a GRAPE-SPH code that includes various physical processes associated with the formation of stellar systems: radiative cooling, star formation,…
Deep surveys conducted during the past decades have shown that galaxies in the distant universe are generally of more irregular shapes, and are disky in appearance and in their star formation rate, compared to galaxies in similar…
We present results of high resolution hydrodynamical simulations of the formation and evolution of dwarf galaxies. Our simulations start from cosmological initial conditions at high redshift. They include metal-dependent cooling, star…
We introduce the MOdelling Star cluster population Assembly In Cosmological Simulations within EAGLE (E-MOSAICS) project. E-MOSAICS incorporates models describing the formation, evolution and disruption of star clusters into the EAGLE…
We use TNG and EAGLE hydrodynamic simulations to investigate the central galaxy - dark matter halo relations that are needed for a halo-based empirical model of star formation in galaxies. Using a linear dimension reduction algorithm and a…
In this study, we investigate the morphology of galaxies in the TNG100 simulation by applying mock observation techniques and compare the results with the observational data from the Sloan Digital Sky Survey (SDSS). By employing a…
We present the ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) code, which uses three different machine learning techniques to classify galaxies in, and around, clusters, according to their projected phase-space position. We…
N-body simulations of galactic collisions are employed to investigate the formation of elliptical rings in disk galaxies. The relative inclination between disk and dwarf galaxies is studied with a fine step of five degrees. It is confirmed…
We present a new two-fluid conduction scheme to simulate the evolution of an isolated, self-gravitating, equilibrium cluster of stars and collisionless dark matter on secular (gravothermal) timescales. We integrate the equations in…
Structural properties posses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a…
Observations of the high redshift Universe, interpreted in the context of a new generation of computer simulated model Universes, are providing new insights into the processes by which galaxies and quasars form and evolve, as well as the…
The formation, inner properties, and spatial distribution of galaxy groups and clusters are closely related to the background cosmological model. We use numerical simulations of variants of the CDM model with different cosmological…