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Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generation of synthetic images through 3D radiative transfer…
Machine-learning (ML) algorithms will play a crucial role in studying the large datasets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with…
Observations of Young Star Cluster ({\bf YSC}) systems in interacting galaxies are reviewed with particular emphasis on their Luminosity Functions ({\bf LF}) and colour distributions. A few spectroscopic abundance measurements are…
This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploited the sample of 315776 SDSS DR9 galaxies with absolute…
The physical properties of the intracluster medium (ICM) reflect signatures of the underlying gravitational potential, mergers and strong interactions with other halos and satellite galaxies, as well as galactic feedback from supernovae and…
I discuss how spectroscopy of extragalactic globular clusters provides a powerful probe of the formation history and mass distribution of galaxies. One critical area is spectroscopy of objects which have been identified as candidate young…
The Legacy Survey of Space and Time, to be conducted with the Vera C. Rubin Observatory, is poised to revolutionize our understanding of the Solar System by providing an unprecedented wealth of data on various objects, including the elusive…
Star clusters in 6 nearby spiral galaxies are examined using archive images from HST/WFPC2. The galaxies have previously been studied from the ground and some of them are known to possess rich populations of "young massive clusters" (YMCs).…
We present a new method based on information theory to find the optimal number of bands required to measure the physical properties of galaxies with a desired accuracy. As a proof of concept, using the recently updated COSMOS catalog…
We present a novel graph-based machine learning classifier for identifying the dark matter cosmic web environments of galaxies. Large galaxy surveys offer comprehensive statistical views of how galaxy properties are shaped by large-scale…
The Magellanic Clouds are a local laboratory for understanding the evolution and properties of dwarf irregular galaxies. To reveal the extended structure and interaction history of the Magellanic Clouds we have undertaken a large-scale…
Tidal features provide signatures of recent mergers and offer a unique insight into the assembly history of galaxies. The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will enable an unprecedentedly large survey of…
The dense Galactic environment is a large reservoir of interstellar dust. Therefore, this region represents a perfect laboratory to study the properties of the cosmic dust grains. X-rays are the most direct way to detect the interaction of…
We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed…
We present an analysis of the X-ray properties of the galaxy cluster population in the z=0 snapshot of the IllustrisTNG simulations, utilizing machine learning techniques to perform clustering and regression tasks. We examine five…
Morphological classification conveys abundant information on the formation, evolution, and environment of galaxies. In this work, we refine the two-step galaxy morphological classification framework ({\tt\string USmorph}), which employs a…
Galaxies host a wide array of internal stellar components, which need to be decomposed accurately in order to understand their formation and evolution. While significant progress has been made with recent integral-field spectroscopic…
We have observed the closest known large, low surface brightness (LSB) galaxy, UGC 2302, with HST using WFPC2 and the F555W and F814W filters. UGC 2302 is a typical large LSB galaxy, and thus represents a good choice for detailed stellar…
The large-scale imaging survey will produce massive photometric data in multi-bands for billions of galaxies. Defining strategies to quickly and efficiently extract useful physical information from this data is mandatory. Among the stellar…
Recent hydrodynamic cosmological simulations cover volumes up to Gpc^3 and resolve halos across a wide range of masses and environments, from massive galaxy clusters down to normal galaxies, while following a large variety of physical…