相关论文: Identifying group galaxies merging with massive cl…
The environments where galaxies reside crucially shape their star formation histories. We investigate a large sample of 1626 cluster galaxies located within 105 galaxy clusters spanning a large range in redshift ($0.26 < z < 1.13)$. The…
(abridged) Mass loss is a key parameter in the evolution of massive stars, with discrepancies between theory and observations and with unknown importance of the episodic mass loss. To address this we need increased numbers of classified…
We compile a sample of spectroscopically- and photometrically-selected cluster galaxies from four high-redshift galaxy clusters ($1.59 < z < 1.71$) from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS), and a comparison…
The environment is known to affect the formation and evolution of galaxies considerably best visible through the well-known morphology-density relationship. In this paper we study the effect of environment on the evolution of early-type…
Planet formation simulations are capable of directly integrating the evolution of hundreds to thousands of planetary embryos and planetesimals, as they accrete pairwise to become planets. In principle such investigations allow us to better…
The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify several million celestial sources. In the case of variable stars, supervised learning…
Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify…
In this work we present the results of a novel approach devoted to disentangle the role of the environmental processes affecting galaxies in clusters. This is based on the analysis of the NUV-r' distributions of a large sample of…
The two currently largest all-sky photometric datasets, WISE and SuperCOSMOS, were cross-matched by Bilicki et al. (2016) (B16) to construct a novel photometric redshift catalogue on 70% of the sky. Galaxies were therein separated from…
Galaxy groups and clusters are the most massive collapsed structures in the Universe. Those structures are formed by collapsing with other smaller structures. Groups and cluster mergers provide an appropriate environment for the evolution…
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,…
The mass accretion rate of galaxy clusters is a key factor in determining their structure, but a reliable observational tracer has yet to be established. We present a state-of-the-art machine learning model for constraining the mass…
Galaxy mergers play a crucial role in galaxy evolution. However, the correlation between mergers and the local environment of galaxies is not fully understood. We aim to address the question of whether galaxy mergers prefer denser or less…
The environmental effect is commonly used to explain the excess of gas-poor galaxies in galaxy clusters. Meanwhile, the presence of gas-poor galaxies at cluster outskirts, where galaxies have not spent enough time to feel the cluster…
Due to the inherently nonlinear nature of gravity cosmological N-body simulations have become an invaluable tool when the growth of structure is being studied and modelled closer to the present epoch. Large simulations with high dynamical…
The characterization of the internal structure of the superclusters of galaxies (walls, filaments and knots where the clusters are located) is paramount for understanding the formation of the Large Scale Structure and for outlining the…
This paper presents a review of the topic of galaxy formation and evolution, focusing on basic features of galaxies, and how these observables reveal how galaxies and their stars assemble over cosmic time. I give an overview of the observed…
We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantised variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that…
In this thesis, we aim to further elucidate the phenomenon of galaxy evolution in the environment of galaxy clusters using the methodology of numerical simulations. For that, we have developed hydrodynamic models in which idealized gas-rich…
Significant galaxy mergers throughout cosmic time play a fundamental role in theories of galaxy evolution. The widespread usage of human classifiers to visually assess whether galaxies are in merging systems remains a fundamental component…