GAIA Galaxy Survey: a multi-colour galaxy survey with GAIA

The performance expected from a galaxy survey to be carried out with GAIA, the GAIA Galaxy Survey, is outlined. From a statistical model of galaxy number density, size and surface brightness distribution, and from detailed numerical simulations based on real images, it is conservatively estimated that GAIA would be able to detect and observe about 3 million galaxies brighter than $V \simeq 17$ and to provide multi-colour and multi-epoch broad-band photometry of these with an end-of-mission angular resolution of $\simeq$ 0.35 \as and a photometric accuracy of $simeq$ 0.2 {mag/arcsec$^2$} at $\mu_V = 20$ {mag/arcsec$^2$}. The substantial scientific case for performing such a survey and the additional efforts required in terms of mission preparation, operations and telemetry are also discussed.Comment: 6 pages, 5 figures, to appear in the Proceedings of the Summer School "GAIA: a European Space Project", held on the 13-18 May 2001 at the Ecole de Physique des Houches, Les Houches, France, published in the "Journal de Physique IV", EDP Science

A new approach to multiwavelength associations of astronomical sources

One of the biggest problems faced by current and next-generation astronomical surveys is trying to produce large numbers of accurate cross-identifications across a range of wavelength regimes with varying data quality and positional uncertainty. Until recently, simple spatial 'nearest neighbour' associations have been sufficient for most applications. However as advances in instrumentation allow more sensitive images to be made, the rapid increase in the source density has meant that source confusion across multiple wavelengths is a serious problem. The field of far-IR and sub-mm astronomy has been particularly hampered by such problems. The poor angular resolution of current sub-mm and far-IR instruments is such that in a lot of cases, there are multiple plausible counterparts for each source at other wavelengths. Here we present a new automated method of producing associations between sources at different wavelengths using a combination of spatial and spectral energy distribution information set in a Bayesian framework. Testing of the technique is performed on both simulated catalogues of sources from GaLICS and real data from multiwavelength observations of the Subaru-XMM Deep Field. It is found that a single figure of merit, the Bayes factor, can be effectively used to describe the confidence in the match. Further applications of this technique to future Herschel data sets are discusse

Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks

We present a sample of 16 likely strong gravitational lenses identified in the VST Optical Imaging of the CDFS and ES1 fields (VOICE survey) using Convolutional Neural Networks (CNNs). We train two different CNNs on composite images produced by superimposing simulated gravitational arcs on real Luminous Red Galaxies observed in VOICE. Specifically, the first CNN is trained on single-band images and more easily identifies systems with large Einstein radii, while the second one, trained on composite RGB images, is more accurate in retrieving systems with smaller Einstein radii. We apply both networks to real data from the VOICE survey, taking advantage of the high limiting magnitude (26.1 in the r-band) and low PSF FWHM (0.8" in the r-band) of this deep survey. We analyse ∼ 21, 200 images with < 21.5, identifying 257 lens candidates. To retrieve a high-confidence sample and to assess the accuracy of our technique, nine of the authors perform a visual inspection. Roughly 75% of the systems are classified as likely lenses by at least one of the authors. Finally, we assemble the LIVE sample (Lenses In VoicE) composed by the 16 systems passing the chosen grading threshold. Three of these candidates show likely lensing features when observed by the Hubble Space Telescope. This work represents a further confirmation of the ability of CNNs to inspect large samples of galaxies searching for gravitational lenses. These algorithms will be crucial to exploit the full scientific potential of forthcoming surveys with the Euclid satellite and the Vera Rubin Observatory

The extragalactic optical-infrared background radiations, their time evolution and the cosmic photon-photon opacity

The background radiations in the optical and the infrared constitute a relevant cause of energy loss in the propagation of high energy particles through space. In particular, TeV observations with Cherenkov telescopes of extragalactic sources are influenced by the opacity effects due to the interaction of the very high-energy source photons with the background light. With the aim of assessing with the best possible detail these opacity terms, we have modelled the extragalactic optical and IR backgrounds using available information on cosmic sources in the universe from far-UV to sub-mm wavelengths over a wide range of cosmic epochs. We have exploited the relevant cosmological survey data - including number counts, redshift distributions, luminosity functions - from ground-based observatories in the optical, near-IR, and sub-mm, as well as multi-wavelength information coming from space telescopes, HST, ISO and Spitzer. Additional constraints have been used from direct measurements or upper limits on the extragalactic backgrounds by dedicated missions (COBE). All data were fitted and interpolated with a multi-wavelength backward evolutionary model, allowing us to estimate the background photon density and its redshift evolution. From the redshift-dependent background spectrum, the photon-photon opacities for sources of high-energy emission at any redshifts were then computed. The same results can also be used to compute the optical depths for any kind of processes in the intergalactic space involving interactions with background photons (like scattering of cosmic-ray particles). We have applied our photon-photon opacity estimates to the analysis of spectral data at TeV energies on a few BLAZARs of particular interest. [abridged]Comment: Accepted for publication in Astronomy and Astrophysics. The current paper has been corrected for a small error in eq.(13) appearing in the previous versio

The evolving relation between star-formation rate and stellar mass in the VIDEO Survey since z=3z=3

We investigate the star-formation rate (SFR) and stellar mass ($M_*$) relation of a star-forming (SF) galaxy sample in the XMM-LSS field to $z\sim 3.0$ using the near-infrared data from the VISTA Deep Extragalactic Observations (VIDEO) survey. Combining VIDEO with broad-band photometry, we use the SED fitting algorithm CIGALE to derive SFRs and $M_*$ and have adapted it to account for the full photometric redshift PDF uncertainty. Applying a SF selection using the D4000 index, we find evidence for strong evolution in the normalisation of the SFR-$M_*$ relation out to $z\sim 3$ and a roughly constant slope of (SFR $\propto M_*^{\alpha}$) $\alpha=0.69\pm0.02$ to $z\sim 1.7$. We find this increases close to unity toward $z\sim2.65$. Alternatively, if we apply a colour selection, we find a distinct turnover in the SFR-$M_*$ relation between $0.7\lesssim z\lesssim2.0$ at the high mass end, and suggest that this is due to an increased contamination from passive galaxies. We find evolution of the specific SFR $\propto(1+z)^{2.60}$ at $\log(M_*)\sim$10.5, out to $z\lesssim2.4$ with an observed flattening beyond $z\sim$ 2 with increased stellar mass. Comparing to a range of simulations we find the analytical scaling relation approaches, that invoke an equilibrium model, a good fit to our data, suggesting that a continual smooth accretion regulated by continual outflows may be a key driver in the overall growth of SFGs.Comment: 19 pages, 18 figures, accepted for publication in MNRA