Related papers: Bridging observations and simulations: a machine l…
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 study simple models of massive galaxy clusters in which the intracluster medium (ICM) rotates differentially in equilibrium in the cluster gravitational potential. We obtain the X-ray surface brightness maps, evaluating the isophote…
We present an investigation of the metal enrichment of the intra-cluster medium (ICM) by galactic winds and merger-driven starbursts. We use combined N-body/hydrodynamic simulations with a semi-numerical galaxy formation model. The mass…
The increasing sensitivity of current experiments, which nowadays routinely measure the thermal SZ effect within galaxy clusters, provide the hope that peculiar velocities of individual clusters of galaxies will be measured rather soon…
CMB lensing is a promising, novel way to measure galaxy cluster masses that can be used, e.g., for mass calibration in galaxy cluster counts analyses. Understanding the statistics of the galaxy cluster mass observable obtained with such…
Clusters of galaxies can be used for very different kinds of cosmological tests. I review a few of the methods: determination of cluster masses and dark matter content, metal enrichment and its connection to the origin of the intra-cluster…
We present a set-based machine learning framework that infers posterior distributions of galaxy cluster masses from projected galaxy dynamics. Our model combines Deep Sets and conditional normalizing flows to incorporate both positional and…
The Multi-Channel Imager (MCI), one of the instruments aboard the China Survey Space Telescope (CSST), is designed to simultaneously observe the sky in three filters, covering wavelengths from the near-ultraviolet (NUV) to the near-infrared…
We evaluate the ability of Convolutional Neural Networks (CNNs) to predict galaxy cluster masses in the BAHAMAS hydrodynamical simulations. We train four separate single-channel networks using: stellar mass, soft X-ray flux, bolometric…
To study systematically the evolution on the angular extents of the galaxy, ICM, and dark matter components in galaxy clusters, we compiled the optical and X-ray properties of a sample of 340 clusters with redshifts $<0.5$, based on all the…
This lecture is an introduction to cosmological tests with clusters of galaxies. Here I do not intend to provide a complete review of the subject, but rather to describe the basic procedures to set up the fitting machinery to constrain…
We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments and knots, according to the distribution and kinematics of dark matter (DM),…
In this two-paper series, we present a straightforward mathematical model for synthesizing quasar absorption line profiles from sight lines through idealized, spatial-kinematic models of the circumgalactic medium (CGM) and their host…
Cosmological galaxy formation simulations are powerful tools to understand the complex processes that govern the formation and evolution of galaxies. However, evaluating the realism of these simulations remains a challenge. The two common…
Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any…
There is a strong connection between the formation of a disk galaxy and the properties of the interstellar medium (ISM). Theoretical work has typically either focused on the cosmological buildup of a galaxy with a relatively crude model for…
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…
We apply two machine learning methods, a CNN deep-leaning model and a gradient-boosting decision tree, to estimate individual cluster optical depths from observed properties derived from multiple complementary datasets. The models are…
We present a detailed analysis of the velocity structure of the hot intracluster medium (ICM) within the A3266 galaxy cluster, including new observations taken between June and November 2023. Firstly, morphological structures within the…
We present BAHAMAS-SIDM, the first large-volume, (400/h Mpc)^3, cosmological simulations including both self-interacting dark matter (SIDM) and baryonic physics. These simulations are important for two primary reasons: 1) they include the…