Related papers: Galaxy Merger Rates up to z $\sim$ 3 using a Bayes…
Different methodologies lead to order-of-magnitude variations in predicted galaxy merger rates. We examine and quantify the dominant uncertainties. Different halo merger rates and subhalo 'destruction' rates agree to within a factor ~2…
The contribution of major mergers to galaxy mass assembly along cosmic time is an important ingredient to the galaxy evolution scenario. We aim to measure the evolution of the merger rate for both luminosity/mass selected galaxy samples and…
Galaxy mergers can change the rate at which stars are formed. We can trace when these changes occur in simulations of galaxy mergers. However, for observed galaxies we do not know how the star formation rate (SFR) evolves along the merger…
As galaxy formation and evolution over long cosmic time-scales depends to a large degree on the structure of the universe, the assembly history of galaxies is potentially a powerful approach for learning about the universe itself. In this…
Galaxies play a key role in our endeavor to understand how structure formation proceeds in the Universe. For any precision study of cosmology or galaxy formation, there is a strong demand for huge sets of realistic mock galaxy catalogs,…
We present a study of galaxy mergers and the influence of environment in the Abell 901/902 supercluster at z~0.165. We use HST ACS F606W data from the STAGES survey, COMBO-17, Spitzer 24um, and XMM-Newton X-ray data. Our analysis utilizes…
The mass assembly of galaxies can proceed through different physical processes. Here we report on the spectroscopic identification of close physical pairs of galaxies at redshifts 2 <z < 4 and discuss the impact of major mergers in shaping…
We investigate the time evolution of non-parametric morphological quantities and their relationship to major mergers between $4\geq z \geq 2$ in high-resolution cosmological zoom simulations of disk galaxies that implement kinetic wind…
We present the quantitative rest-frame B morphological evolution and galaxy merger fractions at 0.2 < z < 1.2 as observed by the All-wavelength Extended Groth Strip International Survey (AEGIS). We use the Gini coefficent and M_20 to…
Galaxy clusters grow through the accretion of galaxies from groups, filaments, and other clusters. During this process, galaxies may undergo pre-processing in lower-density environments, where galaxy-galaxy mergers and other interactions…
We use the Galaxy And Mass Assembly (GAMA) survey to measure the local Universe mass dependent merger fraction and merger rate using galaxy pairs and the CAS structural method, which identifies highly asymmetric merger candidate galaxies.…
(Abridged) We probe the merging channel of massive galaxies over the z=0.3-1.3 redshift window by studying close pairs in a sample of 238 galaxies with stellar mass >1E11Msun, from the deep (m<26.5AB, 3 sigma) SHARDS survey. SHARDS provides…
Context. Machine-Learning (ML) solves problems by learning patterns from data, with limited or no human guidance. In Astronomy, it is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims. We…
We investigate the total major (> 1:4 by stellar mass) and minor (> 1:100 by stellar mass) merger history of a population of 80 massive (M_* > 10^11 M_sol) galaxies at high redshifts (z = 1.7 - 3). We utilize extremely deep and high…
A six-dimensional parameter space based on high-resolution numerical simulations of isolated binary galaxy collisions has been constructed to investigate the dynamical friction timescales, $\tau_{\rm mer}$, for major mergers. Our…
Galaxy mergers are hugely important in our current dark matter cosmology. These powerful events cause the disruption of the merging galaxies, pushing the gas, stars and dust of the galaxies resulting in changes to morphologies. This…
Hierarchical models predict that massive early-type galaxies (mETGs) are the latest systems to be in place into the cosmic scenario (at z<~0.5), conflicting with the observational phenomenon of galaxy mass downsizing, which poses that the…
We train deep learning models on thousands of galaxy catalogues from the state-of-the-art hydrodynamic simulations of the CAMELS project to perform regression and inference. We employ Graph Neural Networks (GNNs), architectures designed to…
We use a suite of semi-empirical models to predict galaxy merger rates and contributions to bulge growth as functions of merger mass, redshift, and mass ratio. The models use empirical halo occupation constraints to identify mergers,…
The evolution of our Universe is strongly influenced by the attractive force of gravity. A key aspect of this evolution, therefore, is the merging of galaxies. Here, we explore the role of mergers in shaping the properties of massive…