Machine-learning computation of distance modulus for local galaxies

Quickly growing computing facilities and an increasing number of extragalactic observations encourage the application of data-driven approaches to uncover hidden relations from astronomical data. In this work we raise the problem of distance reconstruction for a large number of galaxies from available extensive observations. We propose a new data-driven approach for computing distance moduli for local galaxies based on the machine-learning regression as an alternative to physically oriented methods. We use key observable parameters for a large number of galaxies as input explanatory variables for training: magnitudes in U, B, I, and K bands, corresponding colour indices, surface brightness, angular size, radial velocity, and coordinates. We performed detailed tests of the five machine-learning regression techniques for inference of $m-M$: linear, polynomial, k-nearest neighbours, gradient boosting, and artificial neural network regression. As a test set we selected 91 760 galaxies at $z<0.2$ from the NASA/IPAC extragalactic database with distance moduli measured by different independent redshift methods. We find that the most effective and precise is the neural network regression model with two hidden layers. The obtained root-mean-square error of 0.35 mag, which corresponds to a relative error of 16%, does not depend on the distance to galaxy and is comparable with methods based on the Tully-Fisher and Fundamental Plane relations. The proposed model shows a 0.44 mag (20%) error in the case of spectroscopic redshift absence and is complementary to existing photometric redshift methodologies. Our approach has great potential for obtaining distance moduli for around 250 000 galaxies at $z<0.2$ for which the above-mentioned parameters are already observed.

XXL Survey XXI. The environment and clustering of X-ray AGN in the XXL-South field

This work is part of a series of studies focusing on the environment and the properties of the X-ray selected active galactic nuclei (AGN) population from the XXL survey. The present survey, given its large area, continuity, extensive multiwavelength coverage, and large-scale structure information, is ideal for this kind of study. Here, we focus on the XXL-South (XXL-S) field. Our main aim is to study the environment of the various types of X-ray selected AGN and investigate its possible role in AGN triggering and evolution. We studied the large-scale (>1 Mpc) environment up to redshift z=1 using the nearest neighbour distance method to compare various pairs of AGN types. We also investigated the small-scale environment (<0.4 Mpc) by calculating the local overdensities of optical galaxies. In addition, we built a catalogue of AGN concentrations with two or more members using the hierarchical clustering method and we correlated them with the X-ray galaxy clusters detected in the XXL survey. It is found that radio detected X-ray sources are more obscured than non-radio ones, though not all radio sources are obscured AGN. We did not find any significant differences in the large-scale clustering between luminous and faint X-ray AGN, or between obscured and unobscured ones, or between radio and non-radio sources. At local scales (<0.4 Mpc), AGN typically reside in overdense regions, compared to non-AGN; however, no differences were found between the various types of AGN. A majority of AGN concentrations with two or more members are found in the neighbourhood of X-ray galaxy clusters within <25-45 Mpc. Our results suggest that X-ray AGN are typically located in supercluster filaments, but they are also found in over- and underdense regions.

Flux and color variations of the doubly imaged quasar UM673

With the aim of characterizing the flux and color variations of the multiple components of the gravitationally lensed quasar UM673 as a function of time, we have performed multi-epoch and multi-band photometric observations with the Danish 1.54m telescope at the La Silla Observatory. The observations were carried out in the VRi spectral bands during four seasons (2008--2011). We reduced the data using the PSF (Point Spread Function) photometric technique as well as aperture photometry. Our results show for the brightest lensed component some significant decrease in flux between the first two seasons (+0.09/+0.11/+0.05 mag) and a subsequent increase during the following ones (-0.11/-0.11/-0.10 mag) in the V/R/i spectral bands, respectively. Comparing our results with previous studies, we find smaller color variations between these seasons as compared with previous ones. We also separate the contribution of the lensing galaxy from that of the fainter and close lensed component.

High-order 3D Voronoi tessellation for identifying Isolated galaxies, Pairs and Triplets

Geometric method based on the high-order 3D Voronoi tessellation is proposed for identifying the single galaxies, pairs and triplets. This approach allows to select small galaxy groups and isolated galaxies in different environment and find the isolated systems. The volume-limited sample of galaxies from the SDSS DR5 spectroscopic survey was used. We conclude that in such small groups as pairs and triplets the segregation by luminosity is clearly observed: galaxies in the isolated pairs and triplets are on average two times more luminous than isolated galaxies. We consider the dark matter content in different systems. The median values of mass-to-luminosity ratio are 12 M_sol/L_sol for the isolated pairs and 44 M_sol/L_sol for the isolated triplets; 7 (8) M_sol/L_sol for the most compact pairs (triplets). We found also that systems in the denser environment have greater rms velocity and mass-to-luminosity ratio.