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Register a new userAn expanded catalogue of low surface brightness galaxies in the Coma cluster using Subaru/Suprime-Cam
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We present a catalogue of low surface brightness (LSB) galaxies in the Coma cluster obtained from deep Subaru/Suprime-Cam V and R-band imaging data within a region of $sim$4 deg$^2$. We increase the number of LSB galaxies presented in Yagi et al. (2016) by a factor of $sim$3 and report the discovery of 29 new ultra-diffuse galaxies (UDGs). We compile the largest sample of ultra-diffuse galaxies with colours and structural parameters in the Coma cluster. While most UDGs lie along the red-sequence relation of the colour-magnitude diagram, $sim$5per cent are outside (bluer or redder) the red-sequence region of Coma cluster galaxies. Our analyses show that there is no special distinction in the basic photometric parameters between UDGs and other LSB galaxies. We investigate the clustercentric colour distribution and find a remarkable transition at a projected radius of $sim$0.6 Mpc. Within this cluster core region, LSB galaxies are, on average, redder than co-spatial higher surface brightness galaxies, highlighting how vulnerable LSB galaxies are to the physical processes at play in the dense central region of the cluster. The position of the transition radius agrees with expectations from recent cosmological simulation of massive galaxy clusters within which ancient infalls are predicted to dominate the LSB galaxy population.
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We present a catalog of extended low-surface-brightness galaxies (LSBGs) identified in the Wide layer of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Using the first ${sim}$200 deg$^2$ of the survey, we have uncovered 781 LSBGs, spanning red ($g-igeq0.64$) and blue ($g-i<0.64$) colors and a wide range of morphologies. Since we focus on extended galaxies ($r_mathrm{eff}=2.5$-$14^{primeprime}$), our sample is likely dominated by low-redshift objects. We define LSBGs to have mean surface brightnesses $bar{mu}_mathrm{eff}(g)>24.3$ mag arcsec$^{-2}$, which allows nucleated galaxies into our sample. As a result, the central surface brightness distribution spans a wide range of $mu_0(g)=18$-$27.4$ mag arcsec$^{-2}$, with 50% and 95% of galaxies fainter than 24.3 and 22 mag arcsec$^{-2}$, respectively. Furthermore, the surface brightness distribution is a strong function of color, with the red distribution being much broader and generally fainter than that of the blue LSBGs, and this trend shows a clear correlation with galaxy morphology. Red LSBGs typically have smooth light profiles that are well-characterized by single-component S{e}rsic functions. In contrast, blue LSBGs tend to have irregular morphologies and show evidence for ongoing star formation. We crossmatch our sample with existing optical, HI, and ultraviolet catalogs to gain insight into the physical nature of the LSBGs. We find that our sample is diverse, ranging from dwarf spheroidals and ultra-diffuse galaxies in nearby groups to gas-rich irregulars to giant LSB spirals, demonstrating the potential of the HSC-SSP to provide a truly unprecedented view of the LSBG population.
We increase the sample of ultra diffuse galaxies (UDGs) in lower density environments with characterized globular cluster (GC) populations using new Hubble Space Telescope observations of nine UDGs in group environments. While the bulk of our UDGs have GC abundances consistent with normal dwarf galaxies, two of these UDGs have excess GC populations. These two UDGs both have GC luminosity functions consistent with higher surface brightness galaxies and cluster UDGs. We then combine our nine objects with previous studies to create a catalog of UDGs with analyzed GC populations that spans a uniquely diverse range of environments. We use this catalog to examine broader trends in the GC populations of low stellar mass galaxies. The highest GC abundances are found in cluster UDGs, but whether cluster UDGs are actually more extreme requires study of many more UDGs in groups. We find a possible positive correlation between GC abundance and stellar mass, and between GC abundance and galaxy size at fixed stellar mass. However, we see no significant stellar-mass galaxy-size relation, over our limited stellar mass range. We consider possible origins of the correlation between GC abundance and galaxy size, including the possibility that these two galaxy properties are both dependent on the galaxy dark matter halo, or that they are related through baryonic processes like internal feedback.
This project is the continuation of our study of faint Low Surface Brightness Galaxies (fLSBs) in one of the densest nearby galaxy regions known, the Coma cluster. Our goal is to improve our understanding of the nature of these objects by comparing the broad band spectral energy distribution with population synthesis models. The data were obtained with the MEGACAM and CFH12K cameras at the CFHT. We used the resulting photometry in 5 broad band filters (u*, B, V, R, and I), that included new u*-band data, to fit spectral models. With these spectral fits we inferred a cluster membership criterium, as well as the ages, dust extinctions, and photometric types of these fLSBs. We show that about half of the Coma cluster fLSBs have a spectral energy distribution well represented in our template library while the other half present a flux deficit at ultraviolet wavelengths. Among the well represented, ~80% are probably part of the Coma cluster based on their spectral energy distribution. They are relatively young (younger than 2.3 Gyrs for 90% of the sample) non-starburst objects. The later their type, the younger fLSBs are. A significant part of the fLSBs are quite dusty objects. fLSBs are low stellar mass objects (the later their type the less massive they are), with stellar masses comparable to globular clusters for the faintest ones. Their characteristics are correlated with infall directions, confirming the disruptive origin for part of them.
We report an automated morphological classification of galaxies into S-wise spirals, Z-wise spirals, and non-spirals using big image data taken from Subaru/Hyper Suprime-Cam (HSC) Survey and a convolutional neural network(CNN)-based deep learning technique. The HSC i-band images are about 25 times deeper than those from the Sloan Digital Sky Survey (SDSS) and have a two times higher spatial resolution, allowing us to identify substructures such as spiral arms and bars in galaxies at z>0.1. We train CNN classifiers by using HSC images of 1447 S-spirals, 1382 Z-spirals, and 51,650 non-spirals. As the number of images in each class is unbalanced, we augment the data of spiral galaxies by horizontal flipping, rotation, and rescaling of images to make the numbers of three classes similar. The trained CNN models correctly classify 97.5% of the validation data, which is not used for training. We apply the CNNs to HSC images of a half million galaxies with an i-band magnitude of i<20 over an area of 320 deg^2. 37,917 S-spirals and 38,718 Z-spirals are identified, indicating no significant difference between the numbers of two classes. Among a total of 76,635 spiral galaxies, 48,576 are located at z>0.2, where we are hardly able to identify spiral arms in the SDSS images. Our attempt demonstrates that a combination of the HSC big data and CNNs has a large potential to classify various types of morphology such as bars, mergers and strongly-lensed objects.
We first present a catalogue of photometric redshifts for 14.68 million galaxies derived from the 7-band photometric data of Hyper Suprime-Cam Subaru Strategic Program and the Wide-field Infrared Survey Explorer using the nearest-neighbour algorithm. The redshift uncertainty is about 0.024 for galaxies of z<0.7, and steadily increases with redshift to about 0.11 at z~2. From such a large data set, we identify 21,661 clusters of galaxies, among which 5537 clusters have redshifts z>1 and 642 clusters have z>1.5, significantly enlarging the high redshift sample of galaxy clusters. Cluster richness and mass are estimated, and these clusters have an equivalent mass of M_{500} > 0.7*10^{14} Msun. We find that the stellar mass of the brightest cluster galaxies (BCGs) in each richness bin does not significantly evolve with redshift. The fraction of star-forming BCGs increases with redshift, but does not depend on cluster mass.
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