Related papers: Towards understanding feedback from supermassive b…
This short document illustrates QLUSTER: a toy model for populations of binary black holes in dense astrophysical environments. QLUSTER is a simple tool to investigate the occurrence and properties of hierarchical black-hole mergers…
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'…
Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as…
The growing number of binary black hole mergers detected through gravitational waves offers unprecedented insight into their underlying population, yet their astrophysical formation channels remain unresolved. We present a new method to…
We study the distribution of X-ray selected clusters of galaxies with respect to superclusters determined by Abell clusters of galaxies and show that the distribution of X-ray clusters follows the supercluster-void network determined by…
More than 300 supermassive black holes have been detected at redshifts larger than 6, and they are abundant in the centers of local galaxies. Their formation mechanisms, however, are still rather unconstrained. A possible origin of these…
We present the mass--spin diagram for classifying black holes and studying their formation pathways providing an analogue to the Hertzsprung-Russell diagram. This allows for black hole evolutionary tracks as a function of redshift,…
ROSAT deep and shallow surveys have provided an almost complete inventory of the constituents of the soft X-ray background which led to a population synthesis model for the whole X-ray background with interesting cosmological consequences.…
The central engines of Active Galactic Nuclei (AGNs) are powered by accreting supermassive black holes, and while AGNs are known to play an important role in galaxy evolution, the key physical processes occur on scales that are too small to…
We present a novel approach to identify galaxy clusters that are undergoing a merger using a deep learning approach. This paper uses massive galaxy clusters spanning $0 \leq z \leq 2$ from \textsc{The Three Hundred} project, a suite of…
The groundbreaking discoveries of gravitational waves from binary black-hole mergers and, most recently, coalescing neutron stars started a new era of Multi-Messenger Astrophysics and revolutionized our understanding of the Cosmos. Machine…
Convolutional Neural Networks (CNNs) have demonstrated potential for the real-time analysis of data from gravitational-wave detector networks for the specific case of signals from coalescing compact-object binaries such as black-hole…
We perform a comprehensive study of X-ray cavities using a large sample of X-ray targets selected from the Chandra archive. The sample is selected to cover a large dynamic range including galaxy clusters, groups, and individual galaxies.…
In this paper we push forward and exploit an analogy between the morphologies of the X-ray cavities observed in some galaxy clusters, and the optically deficient point-symmetric bubbles occurring in some planetary nebulae (PNe).…
Dwarf galaxies are ideal laboratories to probe the interplay between galaxy formation and the growth of black holes (BHs) in the early Universe. Mounting observational evidence reveals the presence of BHs in low-mass galaxies across cosmic…
In large scale cosmological hydrodynamic simulations simplified sub-grid models for gas accretion onto black holes and AGN feedback are commonly used. Such models typically depend on various free parameters, which are not well constrained.…
We combine multiwavelength data in the AEGIS-XD and C-COSMOS surveys to measure the typical dark matter halo mass of X-ray selected AGN [Lx(2-10keV)>1e42 erg/s] in comparison with far-infrared selected star-forming galaxies detected in the…
Recent work has confirmed that the masses of supermassive black holes, estimated from scaling relations with global properties such as the stellar masses of their host galaxies, may be biased high. Much of this may be caused by the…
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…
Different models of dark matter can alter the distribution of mass in galaxy clusters in a variety of ways. However, so can uncertain astrophysical feedback mechanisms. Here we present a Machine Learning method that ''learns'' how the…