Estimating Photometric Redshifts for X-ray sources in the X-ATLAS field, using machine-learning techniques

We present photometric redshifts for 1,031 X-ray sources in the X-ATLAS field, using the machine learning technique TPZ (Carrasco Kind & Brunner 2013). X-ATLAS covers 7.1 deg2 observed with the XMM-Newton within the Science Demonstration Phase (SDP) of the H-ATLAS field, making it one of the largest contiguous areas of the sky with both XMMNewton and Herschel coverage. All of the sources have available SDSS photometry while 810 have additionally mid-IR and/or near-IR photometry. A spectroscopic sample of 5,157 sources primarily in the XMM/XXL field, but also from several X-ray surveys and the SDSS DR13 redshift catalogue, is used for the training of the algorithm. Our analysis reveals that the algorithm performs best when the sources are split, based on their optical morphology, into point-like and extended sources. Optical photometry alone is not enough for the estimation of accurate photometric redshifts, but the results greatly improve when, at least, mid-IR photometry is added in the training process. In particular, our measurements show that the estimated photometric redshifts for the X-ray sources of the training sample, have a normalized absolute median deviation, n_mad=0.06, and the percentage of outliers, eta=10-14 percent, depending on whether the sources are extended or point-like. Our final catalogue contains photometric redshifts for 933 out of the 1,031 X-ray sources with a median redshift of 0.9.Comment: 10 pages, 13 figures, A&A accepte

Disentangling the AGN and Star-Formation connection using XMM-Newton

There is growing evidence supporting the coeval growth of galaxies and their resident SMBH. Most studies also claim a correlation between the activity of the SMBH and the star-formation of the host galaxy. It is unclear, though, whether this correlation extends to all redz and LX. In this work, we use data from the X-ATLAS and XMM-XXL North fields and compile the largest X-ray sample up to date, to investigate how X-ray AGN affect the star-formation of their host galaxies in a wide redz and luminosity baseline, i.e., 0.03<z<3 and log LX (2-10 keV)= (41-45.5) ergs-1. Our sample consists of 3336 AGN. 1872 X-ray objects have spectroscopic redz. For the remaining sources we calculate photometric redz using TPZ, a machine-learning algorithm. We estimate stellar masses (M*) and Star Formation Rates (SFRs) by applying SED fitting through the CIGALE code, using optical, near-IR and mid-IR photometry. 608 of our sources also have far-IR photometry (Herschel). We use these sources to calibrate the SFR calculations of the rest of our X-ray sample. Our results show a correlation between the LX and the SFR, at all redz and LX spanned by our sample. We also find a dependence of the specific SFR (sSFR) on redz, while there are indications that LX enhances the sSFR even at low redz. We then disentangle the effects of M* and redz on the SFR and study again its dependence on the LX. Towards this end, we use the Schreiber et al. formula to estimate the SFR of main sequence galaxies that have the same stellar mass and redshift as our X-ray AGN. Our analysis reveals that the AGN enhances the star-formation of its host galaxy, when the galaxy lies below the main sequence and quenches the star-formation of the galaxy it lives in, when the host lies above the main sequence. Therefore, the effect of AGN on the SFR of the host galaxy, depends on the location of the galaxy relative to the main sequence.Comment: A&A Accepted 10 pages, 8 figures, 2 table

Star-forming early-type galaxies and quiescent late-type galaxies in the local Universe

Aims: The general consensus is that late-type galaxies undergo intense star-formation, activity while early-type galaxies are mostly inactive. We question this general rule and investigate the existence of star-forming early-type and quiescent late-type galaxies in the local Universe. By computing the physical properties of these galaxies and by using information on their structural properties as well as the density of their local environment, we seek to understand the differences from their `typical' counterparts. Methods: We made use of the multi-wavelength photometric data (from the ultraviolet to the sub-millimetre), for 2209 morphologically classified galaxies in the Galaxy And Mass Assembly survey. Furthermore, we separated the galaxies into subsets of star-forming and quiescent based on their dominant ionising process, making use of established criteria based on the WHα width and the [NII/Hα] ratio. Taking advantage of the spectral energy distribution fitting code CIGALE, we derived galaxy properties, such as the stellar mass, dust mass, and star-formation rate, and we also estimated the unattenuated and the dust-absorbed stellar emission, for both the young (≤200 Myr) and old (> 200 Myr) stellar populations. Results: We find that about 47% of E/S0 galaxies in our sample show ongoing star-formation activity and 8% of late-type galaxies are quiescent. The star-forming elliptical galaxies, together with the little blue spheroids, constitute a population that follows the star-forming main sequence of spiral galaxies very well. The fraction of the luminosity originating from young stars in the star-forming early-type galaxies is quite substantial (∼25%) and similar to that of the star-forming late-type galaxies. The stellar luminosity absorbed by the dust (and used to heat the dust grains) is highest in star-forming E/S0 galaxies (an average of 35%) followed by star-forming Sa-Scd galaxies (27%) with this fraction becoming significantly smaller for their quiescent analogues (6% and 16%, for E/S0 and Sa-Scd, respectively). Star-forming and quiescent E/S0 galaxies donate quite different fractions of their young stellar luminosities to heat up the dust grains (74% and 36%, respectively), while these fractions are very similar for star-forming and quiescent Sa-Scd galaxies (59% and 60%, respectively). Investigating possible differences between star-forming and quiescent galaxies, we find that the intrinsic (unattenuated) shape of the SED of the star-forming galaxies is, on average, very similar for all morphological types. Concerning their structural parameters, quiescent galaxies tend to show larger values of the r-band Sérsic index and larger effective radii (compared to star-forming galaxies). Finally, we find that star-forming galaxies preferably reside in lower density environments compared to the quiescent ones, which exhibit a higher percentage of sources being members of groups

Relation between AGN type and host galaxy properties

We use 3213 active galactic nuclei (AGNs) from the XMM-XXL northern field to investigate the relation of AGN type with host galaxy properties. Applying a Bayesian method, we derive the hardness ratios, and through these the hydrogen column density (NH) for each source. We consider those with NH > 1021.5 cm−2 as absorbed sources (type 2). We examine the star formation rate (SFR) and the stellar mass (M*) distributions for both absorbed and unabsorbed sources. Our work indicates that there is no significant link between AGN type and these host galaxy properties. Next, we investigate whether the AGN power, as represented by its X-ray luminosity (LX) correlates with any deviation of the host galaxy’s place from the so-called main sequence of galaxies, and we examine this separately for the obscured and the unobscured AGN populations. To take into account the effect of M* and redshift on SFR, we use the normalised SFR (SFRnorm). We find that the correlation between LX and SFRnorm follows approximately the same trend for both absorbed and unabsorbed sources, a result that favours the standard AGN unification models. Finally, we explore the connection between the obscuration (NH) and the SFR. We find that there is no relation between them, suggesting that obscuration is not related to the large-scale SFR in the galaxy

Galaxy properties of type 1 and 2 X-ray selected AGN and a comparison among different classification criteria

We present analyses of host galaxy properties of type 1 and type 2 X-ray selected Active galactic nuclei (AGNs) in the XMM-XXL field, which have an available optical spectroscopic classification. We modelled their optical to far-infrared spectral energy distributions (SEDs) using the X-CIGALE code. X-CIGALE allows for the fitting of X-ray flux and accounts for the viewing angle of dusty torus and the attenuation from polar dust. By selecting matched type 1 and 2 sub-samples in the X-ray luminosity and redshift parameter space, we find that both types live in galaxies with similar star formation. However, type 2 AGN tend to reside in more massive systems ($10.87^{+0.06}_{-0.12}\,M_\odot$) compared to their type 1 counterparts ($10.57^{+0.20}_{-0.12}\,M_\odot$). In the second part of our analysis, we compare the spectroscopic classification with that from the SED fitting. X-CIGALE successfully identifies all spectroscopic type 2 sources either by estimating an inclination angle that corresponds to edge on viewing of the source or by measuring increased polar dust in these systems. Approximately 85% of spectroscopic type 1 AGN are also identified as such, based on the SED fitting analysis. There is a small number of sources (∼15% of the sample) that present broad lines in their spectra, but they show strong indications of obscuration, based on SED analysis. These could be systems that are viewed face on and have an extended dust component along the polar direction. The performance of X-CIGALE in classifying AGN is similar at low and high redshifts, under the condition that there is sufficient photometric coverage. Finally, the usage of optical/mid-IR colour criteria to identify optical red AGN (u − W3) suggests that these criteria are better suited for IR selected AGN and their efficiency drops for the low to moderate luminosity sources included in X-ray samples

Star formation of X-ray AGN in COSMOS: The role of AGN activity and galaxy stellar mass

We use approximately 1000 X-ray sources in the COSMOS-Legacy survey and study the position of the AGN relative to the star forming main sequence (MS). We also construct a galaxy (non-AGN) reference sample that includes about 90 000 sources. We apply the same photometric selection criteria to both datasets and construct their spectral energy distributions (SEDs) using optical to far-infrared photometry compiled by the HELP project. We perform SED fitting using the X-CIGALE algorithm and the same parametric grid for both datasets in order to measure the star formation rate (SFR) and stellar mass of the sources. The mass completeness of the data is calculated at different redshift intervals and is applied to both samples. We define our own MS based on the distributions of the specific SFR at different redshift ranges and exclude quiescent galaxies from our analysis. These allow us to compare the SFR of the two populations in a uniform manner, minimising systematic errors and selection effects. Our results show that at low to moderate X-ray luminosities, AGN tend to have lower or at most equal SFRs compared to non-AGN systems with similar stellar mass and redshift. At higher (LX, 2 − 10 keV > 2 − 3 × 1044 erg s−1), we observe an increase in the SFR of AGN for systems that have 10.5 < log [M*(M⊙)] < 11.5

Estimating photometric redshifts for X-ray sources in the X-ATLAS field using machine-learning techniques

We present photometric redshifts for 1031 X-ray sources in the X-ATLAS field using the machine-learning technique TPZ. X-ATLAS covers 7.1 deg observed with XMM-Newton within the Science Demonstration Phase of the H-ATLAS field, making it one of the largest contiguous areas of the sky with both XMM-Newton and Herschel coverage. All of the sources have available SDSS photometry, while 810 additionally have mid-IR and/or near-IR photometry. A spectroscopic sample of 5157 sources primarily in the XMM/XXL field, but also from several X-ray surveys and the SDSS DR13 redshift catalogue, was used to train the algorithm. Our analysis reveals that the algorithm performs best when the sources are split, based on their optical morphology, into point-like and extended sources. Optical photometry alone is not enough to estimate accurate photometric redshifts, but the results greatly improve when at least mid-IR photometry is added in the training process. In particular, our measurements show that the estimated photometric redshifts for the X-ray sources of the training sample have a normalized absolute median deviation, nmad - 0.06, and a percentage of outliers, - = 10-14%, depending upon whether the sources are extended or point like. Our final catalogue contains photometric redshifts for 933 out of the 1031 X-ray sources with a median redshift of 0.9.The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the AHEAD project (grant agreement No. 654215). G.M. acknowledges financial support from the AHEAD project, which is funded by the European Union as Research and Innovation Action under Grant No: 654215. F.J.C. and A.C.R. acknowledge financial support through grant AYA2015-64346-C2-1-P (MINECO/FEDER). A.C.R. also acknowledges financial support by the European Space Agency (ESA) under the PRODEX program.Peer Reviewe

The association of healthy aging with multimorbidity: Ikaria study

The aim of this study was to evaluate several sociodemographic, lifestyle, and clinical characteristics of the IKARIA study participants and to find healthy aging trajectories of multimor-bidity of Ikarian islanders. During 2009, 1410 people (aged 30+) from Ikaria Island, Greece, were voluntarily enrolled in the IKARIA study. Multimorbidity was defined as the combination of at least two of the following chronic diseases: hypertension; hypercholesterolemia; diabetes; obesity; cancer; CVD; osteoporosis; thyroid, renal, and chronic obstructive pulmonary disease. A healthy aging index (HAI) ranging from 0 to 100 was constructed using 4 attributes, i.e., depression symptomatology, cognitive function, mobility, and socializing. The prevalence of multimorbidity was 51% among men and 65.5% among women, while the average number of comorbidities was 1.7 ± 1.4 for men and 2.2 ± 1.4 for women. The most prevalent chronic diseases among men with multimorbidity were hypertension, hypercholesterolemia, and obesity while among women they were hypertension, hypercholesterolemia, and thyroid disease. Multimorbidity was correlated with HAI (Spearman’s rho = −0.127, p &lt; 0.001) and for every 10-unit increase in HAI, participants had 20% lower odds of being multimorbid. Multimorbidity in relation to HAI revealed a different trend across aging among men and women, coinciding only in the seventh decade of life. Aging is usually accompanied by chronic diseases, but multimorbidity seems to also be common among younger adults. However, healthy aging is a lifelong process that may lead to limited co-morbidities across the lifespan. © 2021 by the authors. Licensee MDPI, Basel, Switzerland