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21. ADQL Query
ID:
ivo://astron.nl/__system__/adql/query
Title:
ADQL Query
Short Name:
gavoadql
Date:
09 Jan 2020 07:54:53
Publisher:
ASTRON
Description:
An endpoint for submitting ADQL queries to the data center and retrieving the result in various forms.
22. ADQL Query
ID:
ivo://voxastro.org/__system__/adql/query
Title:
ADQL Query
Short Name:
gavoadql
Date:
05 Feb 2017 18:45:04
Publisher:
Virtual Observatory for Extragalactic Astrophysics
Description:
An endpoint for submitting ADQL queries to the data center and retrieving the result in various forms.
23. ADQL Query
ID:
ivo://xaovo/__system__/adql/query
Title:
ADQL Query
Short Name:
gavoadql
Date:
17 Jul 2018 11:01:55
Publisher:
XinJiang Astronomical Observatory
Description:
An endpoint for submitting ADQL queries to the data center and retrieving the result in various forms.
24. ADQL Query
ID:
ivo://lmd.jussieu/__system__/adql/query
Title:
ADQL Query
Short Name:
gavoadql
Date:
26 Jun 2018 14:36:05
Publisher:
LMD
Description:
An endpoint for submitting ADQL queries to the data center and retrieving the result in various forms.
25. ADQL Query
ID:
ivo://latmos.ipsl/__system__/adql/query
Title:
ADQL Query
Short Name:
gavoadql
Date:
26 Jun 2018 13:14:44
Publisher:
LATMOS
Description:
An endpoint for submitting ADQL queries to the data center and retrieving the result in various forms.
26. ADQL Query
ID:
ivo://pvol/__system__/adql/query
Title:
ADQL Query
Short Name:
gavoadql
Date:
22 Jun 2017 13:47:41
Publisher:
Planetary Virtual Observatory and Laboratory (PVOL)
Description:
An endpoint for submitting ADQL queries to the data center and retrieving the result in various forms.
27. A framework for empirical galaxy phenomenology
ID:
ivo://CDS.VizieR/J/MNRAS/448/1430
Title:
A framework for empirical galaxy phenomenology
Short Name:
J/MNRAS/448/1430
Date:
21 Oct 2021
Publisher:
CDS
Description:
We develop a theoretical framework that extracts a deeper understanding of galaxy formation from empirically derived relations among galaxy properties by extending the main-sequence integration method for computing galaxy star formation histories. We properly account for scatter in the stellar mass-star formation rate relation and the evolving fraction of passive systems and find that the latter effect is almost solely responsible for the age distributions among z~0 galaxies with stellar masses above ~10^10^ M_{sun}_. However, while we qualitatively agree with the observed median stellar metallicity as a function of stellar mass, we attribute our inability to reproduce the distribution in detail largely to a combination of imperfect gas-phase metallicity and {alpha}/Fe ratio calibrations. Our formalism will benefit from new observational constraints and, in turn, improve interpretations of future data by providing self-consistent star formation histories for population synthesis modelling.
28. AGN automatic photometric classification
ID:
ivo://CDS.VizieR/J/MNRAS/437/968
Title:
AGN automatic photometric classification
Short Name:
J/MNRAS/437/968
Date:
21 Oct 2021
Publisher:
CDS
Description:
In this paper, we discuss an application of machine-learning-based methods to the identification of candidate active galactic nucleus (AGN) from optical survey data and to the automatic classification ofAGNs in broad classes. We applied four different machine-learning algorithms, namely the Multi Layer Perceptron, trained, respectively, with the Conjugate Gradient, the Scaled Conjugate Gradient, the Quasi Newton learning rules and the Support Vector Machines, Q4 to tackle the problem of the classification of emission line galaxies in different classes, mainly AGNs versus non-AGNs, obtained using optical photometry in place of the diagnostics based on line intensity ratios which are classically used in the literature. Using the same photometric features, we discuss also the behaviour of the classifiers on finer AGN classification tasks, namely Seyfert I versus Seyfert II, and Seyfert versus LINER. Furthermore, we describe the algorithms employed, the samples of spectroscopically classified galaxies used to train the algorithms, the procedure followed to select the photometric parameters and the performances of our methods in terms of multiple statistical indicators. The results of the experiments show that the application of self-adaptive data mining algorithms trained on spectroscopic data sets and applied to carefully chosen photometric parameters represents a viable alternative to the classical methods that employ time-consuming spectroscopic observations.
29. AGN effect on cold gas in distant SFGs
ID:
ivo://CDS.VizieR/J/A+A/654/A165
Title:
AGN effect on cold gas in distant SFGs
Short Name:
J/A+A/654/A165
Date:
22 Feb 2022
Publisher:
CDS
Description:
In the framework of a systematic study with the ALMA interferometer of infrared (IR)-selected main sequence and starburst galaxies at z~1-1.7 at typical ~1" resolution, we report on the effects of mid-IR and X-ray detected active galactic nuclei (AGN) on the reservoirs and excitation of molecular gas in a sample of 55 objects. We find widespread detectable nuclear activity in ~30% of the sample. The presence of dusty tori influences the IR spectral energy distribution of galaxies, as highlighted by the strong correlation among the AGN contribution to the total IR luminosity budget (fAGN=LIR_AGN_/LIR), its hard X-ray emission, and the Rayleigh-Jeans to mid-IR (S_1.2mm_/S_24um_) observed color with evident consequences on the ensuing empirical star formation rate estimates. Nevertheless, we find only marginal effects of the presence and strength of AGN on the carbon monoxide CO (J=2,4,5,7) or neutral carbon ([CI](3P1-3P0), [CI](3P2-3P1)) line luminosities and on the derived molecular gas excitation as gauged by line ratios and the full spectral line energy distributions. The [CI] and CO emission up to J=5,7 thus primarily traces the properties of the host in typical IR luminous galaxies. However, our analysis highlights the existence of a large variety of line luminosities and ratios despite the homogeneous selection. In particular, we find a sparse group of AGN-dominated sources with the highest LIR_AGN_/LIR_SFR_>=3 ratios that are more luminous in CO(5-4) than what predicted by the L_CO(5-4)_-LIR_SFR_ relation, which might be the result of the nuclear activity. For the general population, our findings translate into AGN having minimal effects on quantities such as gas and dust fractions and star formation efficiencies. If anything, we find hints of a marginal tendency of AGN hosts to be compact at far-IR wavelengths and to display 1.8x larger dust optical depths. In general, this is consistent with a marginal impact of the nuclear activity on the gas reservoirs and star formation in average star-forming AGN hosts with LIR>5x10^11^L_{sun}_, typically under-represented in surveys of quasars and sub-millimeter galaxies.
30. AGN photometry. II. A catalog from the CFHTLS
ID:
ivo://CDS.VizieR/J/AJ/146/87
Title:
AGN photometry. II. A catalog from the CFHTLS
Short Name:
J/AJ/146/87
Date:
21 Oct 2021
Publisher:
CDS
Description:
This is the second paper of the series Detecting Active Galactic Nuclei Using Multi-filter Imaging Data. In this paper we review shapelets, an image manipulation algorithm, which we employ to adjust the point-spread function (PSF) of galaxy images. This technique is used to ensure the image in each filter has the same and sharpest PSF, which is the preferred condition for detecting AGNs using multi-filter imaging data as we demonstrated in Paper I of this series. We apply shapelets on Canada-France-Hawaii Telescope Legacy Survey Wide Survey ugriz images. Photometric parameters such as effective radii, integrated fluxes within certain radii, and color gradients are measured on the shapelets-reconstructed images. These parameters are used by artificial neural networks (ANNs) which yield: photometric redshift with an rms of 0.026 and a regression R-value of 0.92; galaxy morphological types with an uncertainty less than 2 T types for z<=0.1; and identification of galaxies as AGNs with 70% confidence, star-forming/starburst (SF/SB) galaxies with 90% confidence, and passive galaxies with 70% confidence for z<=0.1. The incorporation of ANNs provides a more reliable technique for identifying AGN or SF/SB candidates, which could be very useful for large-scale multi-filter optical surveys that also include a modest set of spectroscopic data sufficient to train neural networks.

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