Related papers: Machine Learning to identify ICL and BCG in simula…

The intracluster medium (ICM), composed of hot plasma, dominates the baryonic content of galaxy clusters and is primarily observable in X-rays. Its thermodynamic properties, pressure, temperature, entropy, and electron density, offer…

We present the clustering of galaxy clusters as a useful addition to the common set of cosmological observables. The clustering of clusters probes the large-scale structure of the Universe, extending galaxy clustering analysis to the…

Intrinsic color profiles of a sample of nine Brightest Cluster Galaxies (BCGs) are recovered from the observed color profiles by evaluating spurious gradients introduced by errors in the determination of the sky levels and by different…

We have observed 433 z<=0.08 brightest cluster galaxies (BCGs) in a full-sky survey of Abell clusters. The BCG Hubble diagram is consistent to within 2% of a Omega_m=0.3, Lambda=0.7 Hubble relation. The L_m-alpha relation for BCGs, which…

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…

We simulate the phase-space distribution of stellar mass in 9 massive Lambda-CDM galaxy clusters by applying the semi-analytic particle tagging method of Cooper et al. to the Phoenix suite of high-resolution N-body simulations (M200 = 7.5…

We present a sample of 329 low to intermediate redshift ($0.05 < z < 0.3$) brightest cluster galaxies (BCGs) in X-ray selected clusters from the SPectroscopic IDentification of eRosita Sources (SPIDERS) survey, a spectroscopic survey within…

Contradictory results have been reported on the time evolution of the alignment between clusters and their Brightest Cluster Galaxy (BCG). We study this topic by analyzing cosmological hydro-simulations of 24 massive clusters with…

We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by…

We have evaluated the diffuse intracluster light (ICL) in the central core of the galaxy cluster CL0024+17 at $z\sim 0.4$ observed with the prime focus camera (LBC) at LBT. The measure required an accurate removal of the galaxies light…

We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to…

In order to obtain morphological information of unlabeled galaxies, we present an unsupervised machine-learning (UML) method for morphological classification of galaxies, which can be summarized as two aspects: (1) the methodology of…

We present deep, large area B and r' imaging for a sample of 49 brightest cluster galaxies (BCGs). The clusters were selected by their x-ray luminosity and redshift to form two volume limited samples, one with mean redshift ~ 0.07 and one…

We present a machine-learning approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep machine learning tool commonly used in image recognition tasks. The CNN is trained…

The diffuse stellar component of galaxy clusters made up of intergalactic stars is termed the intracluster light (ICL). Though there is a developing understanding of the mechanisms by which the ICL is formed, no strong consensus has yet…

In-context learning (ICL) is one of the most powerful and most unexpected capabilities to emerge in recent transformer-based large language models (LLMs). Yet the mechanisms that underlie it are poorly understood. In this paper, we…

Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore a key ingredient in observational cosmology. This…

Within scientific and real life problems, classification is a typical case of extremely complex tasks in data-driven scenarios, especially if approached with traditional techniques. Machine Learning supervised and unsupervised paradigms,…

Using a sample of 2800 galaxy clusters identified in the Dark Energy Survey across the redshift range $0.20 < z < 0.60$, we characterize the hierarchical assembly of Bright Central Galaxies (BCGs) and the surrounding intracluster light…

We study the fraction of the intra-cluster light (ICL) formed in-situ in the three most massive clusters of the TNG50 simulation, with virial masses $\sim 10^{14}$ M$_{\odot}$. We find that a significant fraction of ICL stars ($8\%$-$28\%$)…