Related papers: A Machine Learning Approach to Enhancing eROSITA O…
The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties or galaxy cluster abundances and therefore, constraining cosmological parameters. We present a new technique for…
A direct approach to studying the galaxy-halo connection is to analyze groups and clusters of galaxies that trace the underlying dark matter halos, emphasizing the importance of identifying galaxy clusters and their associated brightest…
The soft X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) mission, eROSITA (extended ROentgen Survey with an Imaging Telescope Array), has produced the largest sample to date of galaxy groups and clusters detected via their…
Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful…
Machine learning is a powerful technique, becoming increasingly popular in astrophysics. In this paper, we apply machine learning to more than a thousand globular cluster (GC) models simulated as part of the 'MOCCA-Survey Database I'…
Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spherically symmetric…
Currently available star cluster catalogues from HST imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. The time-consuming nature of this process has limited the production of reliable…
Exploiting the fundamentally achromatic nature of gravitational lensing, we present a lens model for the massive galaxy cluster SMACSJ0723.3-7323 (SMACSJ0723, z=0.388) that significantly improves upon earlier work. Building on…
We present a new algorithm to search for distant clusters of galaxies on catalogues deriving from imaging data, as those of the ESO Imaging Survey. Our algorithm is a matched filter one, similar to that adopted by Postman et al. (1996),…
We present the first cosmological study of a sample of $eROSITA$ clusters, which were identified in the $eROSITA$ Final Equatorial Depth Survey (eFEDS). In a joint selection on X-ray and optical observables, the sample contains $455$…
We present a collection of classified X-ray sources in Globular Clusters (GCs) observed by the Chandra X-ray Observatory (CXO), including active binaries, cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries. We…
Searches and analyses of strong gravitational lenses are challenging due to the rarity and image complexity of these astronomical objects. Next-generation surveys (both ground- and space-based) will provide more opportunities to derive…
In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify.…
Measuring the morphological parameters of galaxies is a key requirement for studying their formation and evolution. Surveys such as the Sloan Digital Sky Survey (SDSS) have resulted in the availability of very large collections of images,…
Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties impinging on cluster mass estimates. Our aim is to develop a fully self-consistent…
Motivated by recent suggestions that a number of observed galaxy clusters have masses which are too high for their given redshift to occur naturally in a standard model cosmology, we use Extreme Value Statistics to construct confidence…
X-ray observations of galaxy clusters potentially provide powerful cosmological probes if systematics due to our incomplete knowledge of the intracluster medium (ICM) physics are understood and controlled. In this paper, we present mock…
The accurate tracking of live cells using video microscopy recordings remains a challenging task for popular state-of-the-art image processing based object tracking methods. In recent years, several existing and new applications have…
Long-term monitoring and exploration of extreme environments, such as underwater storage facilities, is costly, labor-intensive, and hazardous. Automating this process with low-cost, collaborative robots can greatly improve efficiency.…
We review recent advancements in cosmology with galaxy clusters. Galaxy clusters are the most massive objects in the Universe. Consequently the cluster number density as a function of cluster mass, or cluster abundance, is sensitive to…