Related papers: Automatic quantitative morphological analysis of i…
Galaxy pairs with separations of only a few kpc represent important stages in the merger-driven growth of supermassive black holes (SMBHs). However, such mergers are difficult to identify observationally due to the correspondingly small…
We address the problem of morphological classification of galaxies from the Galaxy Zoo DECaLS dataset using classical machine learning techniques. Our approach employs a dimensionality reduction method followed by a classical classifier to…
Mergers play a complex role in galaxy formation and evolution. Continuing to improve our understanding of these systems require ever larger samples, which can be difficult (even impossible) to select from individual surveys. We use the new…
Galaxy mergers play a crucial role in galaxy evolution. However, the correlation between mergers and the local environment of galaxies is not fully understood. We aim to address the question of whether galaxy mergers prefer denser or less…
Galaxy mergers play an important role in many aspects of galaxy evolution, therefore, more accurate merger identifications are paramount for achieving a complete understanding of galaxy evolution. As we enter the era of very large imaging…
We use machine learning techniques to classify galaxy merger stages, which can unveil physical processes that drive the star formation and active galactic nucleus (AGN) activities during galaxy interaction. The sample contains 4,690…
We report first results from a series of N-body/gasdynamical simulations designed to study the origin of galaxy morphologies in a cold dark matter-dominated universe. The simulations include star formation and feedback and have numerical…
How does the clustering of galaxies depend on their inner properties like morphological type and luminosity? We address this question in the mathematical framework of marked point processes and clarify the notion of luminosity and…
Galaxy morphology is a product of how galaxies formed, how they interacted with their environment, how they were influenced by internal perturbations, AGN, and dark matter, and of their varied star formation histories. This article reviews…
The morphology of galaxies can be quantified to some degree using a set of scale-invariant parameters. Concentration (C), Asymmetry (A), Smoothness (S), the Gini index (G), relative contribution of the brightest pixels to the second order…
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…
There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a…
Galaxy morphology classification plays a crucial role in understanding the structure and evolution of the universe. With galaxy observation data growing exponentially, machine learning has become a core technology for this classification…
The correlation between a galaxy's morphology and its observed optical spectrum is investigated. As an example, 4000 galaxies from the 2dF Galaxy Redshift Survey, which possess both good quality spectra and have visually determined…
The formation of Hoag-type galaxies with central spheroidal galaxies and outer stellar rings has yet to be understood in astronomy. We consider that these unique objects were formed from the past interaction between elliptical galaxies and…
Mergers and the spin of the dark matter halo are factors traditionally believed to determine the morphology of galaxies within a $\Lambda$CDM cosmology. We study this hypothesis by considering approximately 18,000 central galaxies at $z=0$…
Machine learning is becoming a popular tool to quantify galaxy morphologies and identify mergers. However, this technique relies on using an appropriate set of training data to be successful. By combining hydrodynamical simulations,…
We study the effects of mergers on the structural properties of disc-like systems by using Smooth Particle Hydrodynamical (SPH) numerical simulations in hierarchical clustering scenarios. In order to assess the effects of mergers on the…
(abridged) The clustering properties of galaxies belonging to different luminosity ranges or having different morphological types are different. These characteristics or `marks' permit to understand the galaxy catalogs that carry all this…
Merging galaxy systems provides observational evidence of the existence of dark matter and constraints on its properties. Therefore, statistical uniform samples of merging systems would be a powerful tool for several studies. In this work…