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VizieR Online Data Catalog: SDSS galaxies morphological classification (Vavilova+, 2021)
Catalogue of the morphological types of 316031 galaxies with the absolute stellar magnitudes -24m<Mr<-13m at z<0.1 from the SDSS DR9 is obtained by the machine learning methods (support vector machine, SVM; random forest, RF). A preliminary sample of galaxies contained of ~724,000 galaxies. Following the SDSS recommendation, we input limits mr<17.7 to avoid typical statistical errors in spectroscopic flux. The absolute stellar magnitude of the galaxy was obtained by the formula (example for r-band): Mr=mr-5lg(DL)-25-Kr(z)-extr), where mr - visual stellar magnitude in r-band, DL - luminosity distance, extr - the Galactic absorption in r-band, Kr(z) - k-correction in r-band. The color indices were calculated as (example for g-i bands) Mg-Mi=(mg-mi)-(extg-exti)-(Kg(z)-Ki(z)), where mg and mi - visual stellar magnitude; extg and exti) - the Galactic absorption; Kg(z) and Ki(z) - k-correction. We provided a binary automated morphological classification: early-type "E" and late type "L". The methods of Support Vector Machine and Random Forest with Scikit-learn software machine learning library in thePython provide the highest accuracy. Namely, 96.4% for SVM (96.1% early "E" and 96.9% late "L" types) and 95.5% for Random Forest (96.7% early "E" and 92.8% late "L" types). Applying the SVM we found 139659 E and 176372 L types galaxies.
2021yCat..36480122VVizieR Online Data Catalog: Galaxies at 0.02
Catalogue of the image-based morphological classification of 315776 galaxies with the absolute stellar magnitudes in the range of -24...-13 at z<0.1 from the SDSS DR9 is obtained by the CNN classifier. To create the Catalogue, we divided it into two subsamples, SDSS DR9 galaxy dataset and Galaxy Zoo 2 (GZ2) dataset, considering them as the inference and training datasets, respectively. When training the CNN classifier for a more accurate result, we took into consideration only those galaxies for which GZ2's volunteers gave the most votes. The criteria for each image of the galaxy are defined in the GZ2 project, their description is available through web-site https://data.galaxyzoo.org/. This Catalogue contains the data on five morphological classes, where the CNN probability of galaxy to be assigned to one of the classes is as follows: cigar-shaped (75%), completely round (83%), round in-between (93%), edge-on (93%), spiral (96%). This Catalogue is supplemented with the VizieR Online Data Catalog: SDSS galaxies morphological classification (Vavilova et al., 2021A&A...648A.122V, Cat. J/A+A/648/A122) Catalogue is available in CSV format at ftp://ftp.mao.kiev.ua/pub/astro /cats/galaxies/galSDSSDR9zto0.1morph5_classes.csv.
2022yCatp071002801VVizieR Online Data Catalog: Dark matter mass fraction in gal. through X-ray gas (Harris+, 2020)
Babyk+ 2018ApJ...857...32B provide a homogeneous set of measurements of the total X-ray radial profiles, the gas mass MX, and M5 for 94 relatively massive galaxies nearer than ~200Mpc. From this list of 94, we have deleted 16 with the most uncertain measurements, leaving 78 systems. We have, however, added 24 more early-type galaxies (ETGs) with Chandra data newly measured through exactly the same procedures by I. V. Babyk (2020, in preparation), making a final total of 102 galaxies with measured mass distributions based on their X-ray gas content.
2022yCat..19050028HVizieR Online Data Catalog: Chandra X-Ray galaxy clusters at z <1.4 (Babyk+, 2014)
A reconstruction of the total mass (the fraction of dark matter, intercluster gas, and the brightest galaxy of the cluster) of 128 X-ray galaxy clusters at redshifts 0.01-1.4 based on Chandra observations is presented. The total mass M200 and the baryonic mass Mb have been measured for all the sample objects, as well as the concentration parameter c200, which characterizes the size of the dark matter halo. The existence of a tight correlation between c200 and M200 is confirmed, c{prop.to}Mavir/(1+z)b with a=-0.56+/-0.15 and b=0.80+/-0.25 (95% confidence level), in good agreement with the predictions of numerical simulations and previous observations. Fitting the inner dark-matter density slope α with a generalized NFW model yields α=1.10+/-0.48 at the 2σ confidence level, combining the results for the entire sample, for which the model gives a good description of the data. There is also a tight correlation between the inner slope of the dark-matter density profile α and the baryonic mass content Mb for massive galaxy clusters, namely, α decreases with increasing baryonic mass content. A simple power-law model is used to fit the α-Mb distributions, yielding the break point for the inner slope of the dark-matter density profile b=1.72+/-0.37 (68% confidence level).
2014yCat..80910679B