scholarly journals Substructure in Clusters of Galaxies

1983 ◽  
Vol 104 ◽  
pp. 231-233
Author(s):  
M. J. Geller ◽  
T. C. Beers
Keyword(s):  
Galaxy Clusters ◽  
Surface Brightness ◽  
Clusters Of Galaxies ◽  
X Ray ◽  
Contour Maps ◽  
Cluster Evolution ◽  
Cluster Properties ◽  
Insight Into ◽  
Complete Collapse

Rich galaxy clusters containing multiple condensations are common. This subclustering affects many cluster properties and provides insight into cluster evolution.“Clumpy” clusters of galaxies are interesting, in part, because N-body simulations indicate that multi-component substructure occurs before complete collapse and virialization (White 1976). Interesting systems can be identified both from x-ray surface brightness maps (Forman et al. 1981) and from contour maps based on galaxy counts (Geller and Beers 1982).

scholarly journals The Ghosts of Galaxies: Tidal Debris in Clusters

2004 ◽  
Vol 217 ◽  
pp. 70-76
Author(s):  
Michael D. Gregg ◽  
Michael J. West
Keyword(s):  
Globular Clusters ◽  
Surface Brightness ◽  
Large Scale ◽  
Dwarf Galaxies ◽  
Cluster Formation ◽  
X Ray ◽  
Cluster Evolution ◽  
Low Surface Brightness ◽  
Intergalactic Space ◽  
Formation And Evolution

Gravitational interactions in rich clusters can strip material from the outer parts of galaxies or even completely disrupt entire systems, giving rise to large scale, low surface brightness ghostly features stretching across intergalactic space. The nearby Coma and Centaurus clusters both have striking examples of galaxy ghosts, in the form of 100 kpc-long plumes of intergalactic debris. By searching HST archival images, we have found numerous other examples of galaxy ghosts in rich clusters at low redshift, evidence that galaxy destruction and recycling are ubiquitous, important in cluster formation and evolution, and continue to mold clusters at the present epoch. Many ghosts appear in X-ray bright clusters, perhaps signaling a connection with energetic subcluster mergers.The fate of such material has important ramifications for cluster evolution. Our new HST WFPC2 V & I images of a portion of the Centaurus plume reveal that it contains an excess of discrete objects with −12 < MV < −6, consistent with being globular clusters or smaller dwarf galaxies. This tidally liberated material is being recycled directly into the intracluster population of stars, dwarf galaxies, globular clusters, and gas, which may have been built largely from a multitude of similar events over the life of the cluster.

scholarly journals A deep learning view of the census of galaxy clusters in IllustrisTNG

2020 ◽  
Vol 498 (4) ◽  
pp. 5620-5628
Author(s):  
Y Su ◽  
Y Zhang ◽  
G Liang ◽  
J A ZuHone ◽  
D J Barnes ◽  
...  
Keyword(s):  
Deep Learning ◽  
Galaxy Clusters ◽  
Large Scale ◽  
Learning Algorithm ◽  
X Ray ◽  
Deep Learning Algorithm ◽  
Cluster Evolution ◽  
Novel Method ◽  
Massive Clusters ◽  
Activation Mapping

ABSTRACT The origin of the diverse population of galaxy clusters remains an unexplained aspect of large-scale structure formation and cluster evolution. We present a novel method of using X-ray images to identify cool core (CC), weak cool core (WCC), and non-cool core (NCC) clusters of galaxies that are defined by their central cooling times. We employ a convolutional neural network, ResNet-18, which is commonly used for image analysis, to classify clusters. We produce mock Chandra X-ray observations for a sample of 318 massive clusters drawn from the IllustrisTNG simulations. The network is trained and tested with low-resolution mock Chandra images covering a central 1 Mpc square for the clusters in our sample. Without any spectral information, the deep learning algorithm is able to identify CC, WCC, and NCC clusters, achieving balanced accuracies (BAcc) of 92 per cent, 81 per cent, and 83 per cent, respectively. The performance is superior to classification by conventional methods using central gas densities, with an average ${\rm BAcc}=81{{\ \rm per\ cent}}$, or surface brightness concentrations, giving ${\rm BAcc}=73{{\ \rm per\ cent}}$. We use class activation mapping to localize discriminative regions for the classification decision. From this analysis, we observe that the network has utilized regions from cluster centres out to r ≈ 300 kpc and r ≈ 500 kpc to identify CC and NCC clusters, respectively. It may have recognized features in the intracluster medium that are associated with AGN feedback and disruptive major mergers.

scholarly journals Magnetorotational instability in cool cores of galaxy clusters

2015 ◽  
Vol 81 (5) ◽  
Author(s):  
Carlo Nipoti ◽  
L. Posti ◽  
S. Ettori ◽  
M. Bianconi
Keyword(s):  
Heat Flux ◽  
Heat Conduction ◽  
Galaxy Clusters ◽  
Magnetized Plasma ◽  
Radiative Cooling ◽  
Clusters Of Galaxies ◽  
Magnetorotational Instability ◽  
X Ray ◽  
Stability Properties ◽  
Anisotropic Heat Conduction

Clusters of galaxies are embedded in halos of optically thin, gravitationally stratified, weakly magnetized plasma at the system’s virial temperature. Owing to radiative cooling and anisotropic heat conduction, such intracluster medium (ICM) is subject to local instabilities, which are combinations of the thermal, magnetothermal and heat-flux-driven buoyancy instabilities. If the ICM rotates significantly, its stability properties are substantially modified and, in particular, also the magnetorotational instability (MRI) can play an important role. We study simple models of rotating cool-core clusters and we demonstrate that the MRI can be the dominant instability over significant portions of the clusters, with possible implications for the dynamics and evolution of the cool cores. Our results give further motivation for measuring the rotation of the ICM with future X-ray missions such as ASTRO-H and ATHENA.

scholarly journals Simulated X-ray galaxy clusters at the virial radius: Slopes of the gas density, temperature and surface brightness profiles

2006 ◽  
Vol 373 (4) ◽  
pp. 1339-1350 ◽  
Author(s):  
M. Roncarelli ◽  
S. Ettori ◽  
K. Dolag ◽  
L. Moscardini ◽  
S. Borgani ◽  
...  
Keyword(s):  
Galaxy Clusters ◽  
Surface Brightness ◽  
Gas Density ◽  
X Ray

The structure and spectra of the X-ray sources in clusters of galaxies

1979 ◽  
Vol 366 (1726) ◽  
pp. 403-421 ◽  
Keyword(s):  
Emission Lines ◽  
Clusters Of Galaxies ◽  
X Ray ◽  
Preliminary Results ◽  
Current State ◽  
Iron Abundance ◽  
Cluster Properties ◽  
Perseus Cluster

The current state of our knowledge of the Perseus cluster at radio, optical and X-ray wavelengths is reviewed to summarize the nature of cluster sources. Recent results on the X-ray structure of clusters are presented. Objects discussed include the Centaurus and Virgo clusters, Abell 1367 and Abell 478. Preliminary results of a study of 30 cluster X-ray spectra are reported. The derivation of the intra-cluster gas parameters is described and the relations between these parameters and other cluster properties are examined. The detection of highly ionized iron emission lines in the spectra of several clusters is discussed and estimates of iron abundance are presented.

scholarly journals ASCA Observations of Three Gravitational Lensing Clusters of Galaxies; CL0500-24, CL2244-02, and A370

1998 ◽  
Vol 188 ◽  
pp. 319-320
Author(s):  
Naomi Ota ◽  
Kazuhisa Mitsuda ◽  
Yasushi Fukazawa
Keyword(s):  
Gravitational Lensing ◽  
Surface Brightness ◽  
Clusters Of Galaxies ◽  
X Ray

We determined the X-ray temperatures of three gravitational lensing clusters, CL0500-24, CL2244-02, and A370, and obtained significant constraints on the surface brightness profile assuming the β-model and the King model profiles. The mass of the cluster estimated from these X-ray data is by a factor of two to three smaller than the mass estimated from lens models for two of the clusters.

scholarly journals X-ray selected clusters of galaxies

1988 ◽  
Vol 130 ◽  
pp. 542-542
Author(s):  
Isabella M. Gioia ◽  
T. Maccacaro ◽  
S. L. Morris ◽  
R. E. Schild ◽  
J. T. Stocke ◽  
...  
Keyword(s):  
Energy Band ◽  
Luminosity Function ◽  
High Redshift ◽  
Cosmic Time ◽  
Entire Population ◽  
Clusters Of Galaxies ◽  
Limited Sample ◽  
X Ray ◽  
Identification Process ◽  
Cluster Evolution

Studies of the evolution of X-ray emission from clusters of galaxies have so far used optically discovered distant clusters then observed at X-ray wavelengths. A different approach to the study of cluster evolution is to use clusters selected directly by their X-ray emission since X-ray selection is extremely successful at discovering high redshift clusters (up to z = 0.5). The Extension of the Medium Sensitivity Survey (Gioia, Maccacaro and Wolter, 1987), a flux limited sample of serendipitous X-ray sources discovered with the Einstein IPC, has been used to select 68 optically identified clusters and 66 possible candidates (using X-ray isointensity maps and optical POSS and ESO prints). Their X-ray fluxes are in the range 10−13 – 10−12 ergs cm−2 s−1 in the 0.3–3.5 keV energy band. Few misidentifications are expected, thus the results presented here have to be considered as preliminary. This sample can be used to study the X-ray logN-logS, the cluster luminosity function and its possible evolution with cosmic time, and also to compare the properties of X-ray selected clusters with those of samples selected by other techniques. Since the identification process is still in progress, and has not proceeded completely at random, the subset of identified sources is not representative of the entire population. With this caveat in mind we have constructed the redshift and X-ray luminosity distributions for the clusters for which we have spectroscopic observations. 68% of the clusters are at z > 0.1, 34% at z > 0.2, and 12% at z > 0.3. Their X-ray luminosities range from about 3 × 1042 to 1045 ergs s−1. At present the lack of a redshift determination for many of the cluster candidates in our sample prevents us from studying the cluster luminosity function. W e can however derive their logN(>S)-logS relation.

scholarly journals Development of New Analysis Method for Mapping Observations of Clusters of Galaxies

1998 ◽  
Vol 188 ◽  
pp. 312-313
Author(s):  
K. Kikuchi ◽  
T. Ohashi ◽  
H. Ezawa ◽  
M. Hirayama ◽  
H. Honda ◽  
...  
Keyword(s):  
Surface Brightness ◽  
Stray Light ◽  
Physical Parameters ◽  
Clusters Of Galaxies ◽  
X Rays ◽  
X Ray ◽  
Hot Gas ◽  
Cluster Data ◽  
Metal Abundance ◽  
Analysis System

Mapping observations of nearby large-extended clusters of galaxies (Coma, Perseus, Virgo, etc.) are being performed with ASCA. Such clusters allow us to map physical parameters of hot gas in the clusters, such as temperature, metal abundance, and X-ray surface brightness. To determine such parameters at each part of a cluster, one should take careful care of X-ray contamination from outside of a pointed field, which is mainly due to “stray-light” X-rays (Honda et al. 1997). For this reason, the only way to obtain the distribution of hot gas parameter is to process the whole cluster data in a self-consistent way. For this purpose, we are developing the new analysis system called TERRA.

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