Related papers: Identifying kinematic structures in simulated gala…
We present a method to constrain galaxy parameters directly from three-dimensional data cubes. The algorithm compares directly the data with a parametric model mapped in $x,y,\lambda$ coordinates. It uses the spectral lines-spread function…
We investigate the relevance of kinematically identified bulges, discs and their role relative to galaxy quenching. We utilize an analysis of the SDSS-MaNGA survey conducted with the GPU-based code BANG which simultaneously models galaxy…
Cosmological simulations of structure formation predict that galaxies are dramatically modified by galaxy harassment during the assembly of galaxy clusters, losing a substantial fraction of their stellar mass which today must be in the form…
In Astrophysics, the identification of candidate Globular Clusters through deep, wide-field, single band HST images, is a typical data analytics problem, where methods based on Machine Learning have revealed a high efficiency and…
We introduce Project GIBLE (Gas Is Better resoLved around galaxiEs), a suite of cosmological zoom-in simulations where gas in the circumgalactic medium (CGM) is preferentially simulated at ultra-high numerical resolution. Our initial sample…
Machine learning has the potential to improve the reconstruction of the dark matter profile of galaxies with respect to traditional methods, like rotation curves. We demonstrate on the simulation suite Illustris-TNG that a steerable…
Subjective classification of spiral galaxies is not sufficient for studying the effect of bars on their physical characteristics. In reality the problem is to comprehend the complex correlations in a multivariate parametric space.…
Modern cosmological surveys such as the Hyper Suprime-Cam (HSC) survey produce a huge volume of low-resolution images of both distant galaxies and dim stars in our own galaxy. Being able to automatically classify these images is a…
We invoke a Gaussian mixture model (GMM) to jointly analyse two traditional emission-line classification schemes of galaxy ionization sources: the Baldwin-Phillips-Terlevich (BPT) and $\rm W_{H\alpha}$ vs. [NII]/H$\alpha$ (WHAN) diagrams,…
The hot ($>10^6$ K) phase of the circumgalactic medium (CGM) contains a large fraction of baryons in galaxies. It also retains signatures of the processes that shaped the galaxies, such as feedback from active galactic nuclei (AGNs) and…
Mapping with uncertainty representation is required in many research domains, especially for localization. Although there are many investigations regarding the uncertainty of the pose estimation of an ego-robot with map information, the…
We present a suite of six high-resolution chemo-dynamical simulations of isolated galaxies, spanning observed disk-dominated environments on the star-forming main sequence, as well as quenched, bulge-dominated environments. We compare and…
We introduce a new self-consistent structure finding algorithm that parses large scale cosmological structure into clusters, filaments and voids. This structure finding algorithm probes the cosmological structure at multiple scales and…
After two decades of direct dynamical simulation of large-scale structure in the universe, it is safe to say the subject is now mature. Still, there are parts of the problem that are less well developed than others. In general, the…
We use cosmological hydrodynamical simulations of the formation of Milky Way-mass galaxies to study the relative importance of the main stellar components, i.e., discs, bulges, and bars, at redshift zero. The main aim of this work is to…
Globular clusters (GCs) are powerful tracers of galaxy assembly, frequently used to identify accreted substructure and reconstruct hierarchical merger histories. With advances in GC formation models and cosmological simulations, we can now…
We investigate the power of the caustic technique for identifying substructures of galaxy clusters from optical redshift data alone. The caustic technique is designed to estimate the mass profile of galaxy clusters to radii well beyond the…
Reconstructing dynamic 3D scenes from blurry monocular videos is challenging as motion-induced blur entangles object motion and geometry, hindering geometric consistency. We present Kinematics-GS, a kinematics-aware framework that models…
In this paper, a deep convolutional neural network architecture for galaxies classification is presented. The galaxy can be classified based on its features into main three categories Elliptical, Spiral, and Irregular. The proposed deep…
Cluster galaxies moving through the intracluster medium (ICM) are expected to lose some of their interstellar medium (ISM) through ISM-ICM interactions. We perform high resolution (40 pc) three-dimensional hydrodynamical simulations of a…