相关论文: Identifying group galaxies merging with massive cl…

At z=0, clusters are primarily populated by red, elliptical and massive galaxies, while blue, spiral and lower-mass galaxies are common in low-density environments. Understanding how and when these differences were established is of…

We explore galaxy properties and their link with environment and clustering using a population of ~1000 galaxies formed in a high resolution hydrodynamic simulation of the Lambda CDM cosmology. At the redshift we concentrate on, z=1, the…

We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive…

To understand the role of the environment in galaxy formation, evolution, and present-day properties, it is essential to study the multi-frequency behavior of different galaxy populations under various environmental conditions. We…

Machine learning (ML) techniques, in particular supervised regression algorithms, are a promising new way to use multiple observables to predict a cluster's mass or other key features. To investigate this approach we use the \textsc{MACSIS}…

We present a study of the spectroscopic and photometric properties of galaxies in six nearby clusters. We perform a partial correlation analysis on our dataset to investigate whether the correlation between star formation rates in galaxies…

We present a study of environmental effects and preprocessing in a large galaxy group using a high-resolution, zoom-in simulation run with the GASOLINE2 hydrodynamics code. We categorize galaxies that were always in distinct haloes as…

In about 40% of the Local Group galaxies star clusters have been detected so far, but the census is still incomplete. The properties of these clusters are briefly reviewed, and the impact of galaxy environment on the evolution and survival…

To determine the importance of merging galaxies to galaxy evolution, it is necessary to design classification tools that can identify different types and stages of merging galaxies. Previously, using GADGET-3/SUNRISE simulations of merging…

Their ubiquity and extreme densities make star clusters probes of prime importance of galaxy evolution. Old globular clusters keep imprints of the physical conditions of their assembly in the early Universe, and younger stellar objects,…

We conduct an environmental analysis around 167 star-forming galaxies (SFGs) detected by the Star Formation Across Cosmic Time (SFACT) survey over the redshift range 0.129 $\leq$ z $\leq$ 0.500. We use three environmental estimators to…

A fundamental bimodality of galaxies in the local Universe is apparent in many of the features used to describe them. Multiple sub-populations exist within this framework, each representing galaxies following distinct evolutionary pathways.…

Recent models and simulations of cluster formation within molecular clumps consider multi-scale, hierarchical accretion, which leads to clump mass growth over time. This mode of mass accumulation could have implications regarding the…

Galaxy mergers are hugely important in our current dark matter cosmology. These powerful events cause the disruption of the merging galaxies, pushing the gas, stars and dust of the galaxies resulting in changes to morphologies. This…

In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…

The optical morphology of galaxies is strongly related to galactic environment, with the fraction of early-type galaxies increasing with local galaxy density. In this work we present the first analysis of the galaxy morphology-density…

The results of morphological galaxy classifications performed by humans and by automated methods are compared. In particular, a comparison is made between the eyeball classifications of 454 galaxies in the Sloan Digital Sky Survey (SDSS)…

One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is…

We use a new fiber spectroscopic survey of 12 nearby, poor groups of galaxies to examine the dynamics and evolution of galaxies in these common, but poorly studied, environments. Some of our conclusions are: (1) The nine groups in our…

Massive Ultracompact Galaxies (MUGs) are common at z=2-3, but very rare in the nearby Universe. Simulations predict that the few surviving MUGs should reside in galaxy clusters, whose large relative velocities prevent them from merging,…