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Register a new userHorizon-AGN virtual observatory - 1. SED-fitting performance and forecasts for future imaging surveys
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Using the ligthcone from the cosmological hydrodynamical simulation Horizon-AGN, we produced a photometric catalogue over $0<z<4$ with apparent magnitudes in COSMOS, DES, LSST-like, and Euclid-like filters at depths comparable to these surveys. The virtual photometry accounts for the complex star formation history and metal enrichment of Horizon-AGN galaxies, and consistently includes magnitude errors, dust attenuation and absorption by inter-galactic medium. The COSMOS-like photometry is fitted in the same configuration as the COSMOS2015 catalogue. We then quantify random and systematic errors of photometric redshifts, stellar masses, and star-formation rates (SFR). Photometric redshifts and redshift errors capture the same dependencies on magnitude and redshift as found in COSMOS2015, excluding the impact of source extraction. COSMOS-like stellar masses are well recovered with a dispersion typically lower than 0.1 dex. The simple star formation histories and metallicities of the templates induce a systematic underestimation of stellar masses at $z<1.5$ by at most 0.12 dex. SFR estimates exhibit a dust-induced bimodality combined with a larger scatter (typically between 0.2 and 0.6 dex). We also use our mock catalogue to predict photometric redshifts and stellar masses in future imaging surveys. We stress that adding Euclid near-infrared photometry to the LSST-like baseline improves redshift accuracy especially at the faint end and decreases the outlier fraction by a factor $sim$2. It also considerably improves stellar masses, reducing the scatter up to a factor 3. It would therefore be mutually beneficial for LSST and Euclid to work in synergy.
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The mutually complementary Euclid and Roman galaxy redshift surveys will use Halpha- and [OIII]-selected emission line galaxies as tracers of the large scale structure at $0.9 lesssim z lesssim 1.9$ (Halpha) and $1.5 lesssim z lesssim 2.7$ ([OIII]). It is essential to have a reliable and sufficiently precise knowledge of the expected numbers of Halpha-emitting galaxies in the survey volume in order to optimize these redshift surveys for the study of dark energy. Additionally, these future samples of emission-line galaxies will, like all slitless spectroscopy surveys, be affected by a complex selection function that depends on galaxy size and luminosity, line equivalent width, and redshift errors arising from the misidentification of single emission-line galaxies. Focusing on the specifics of the Euclid survey, we combine two slitless spectroscopic WFC3-IR datasets -- 3D-HST+AGHAST and the WISP survey -- to construct a Euclid-like sample that covers an area of 0.56 deg$^2$ and includes 1277 emission line galaxies. We detect 1091 ($sim$3270 deg$^{-2}$) Halpha+[NII]-emitting galaxies in the range $0.9leq z leq 1.6$ and 162 ($sim$440 deg$^{-2}$) [OIII]$lambda$5007-emitters over $1.5leq z leq 2.3$ with line fluxes $geq 2 times 10^{-16}$ erg s$^{-1}$ cm$^{-2}$. The median of the Halpha+[NII] equivalent width distribution is $sim$250r{A}, and the effective radii of the continuum and Halpha+[NII] emission are correlated with a median of $sim$0.38 and significant scatter ($sigma sim $0.2$-$0.35). Finally, we explore the prevalence of redshift misidentification in future Euclid samples, finding potential contamination rates of $sim$14-20% and $sim$6% down to $2times 10^{-16}$ and $6 times 10^{-17}$ erg s$^{-1}$ cm$^{-2}$, respectively, though with increased wavelength coverage these percentages drop to nearly zero.
Using the Horizon-AGN hydrodynamical simulation and self-organising maps (SOMs), we show how to compress the complex data structure of a cosmological simulation into a 2-d grid which is much easier to analyse. We first verify the tight correlation between the observed 0.3$!-!5mu$m broad-band colours of Horizon-AGN galaxies and their high-resolution spectra. The correlation is found to extend to physical properties such as redshift, stellar mass, and star formation rate (SFR). This direct mapping from colour to physical parameter space is shown to work also after including photometric uncertainties that mimic the COSMOS survey. We then label the SOM grid with a simulated calibration sample and estimate redshift and SFR for COSMOS-like galaxies up to $zsim3$. In comparison to state-of-the-art techniques based on synthetic templates, our method is comparable in performance but less biased at estimating redshifts, and significantly better at predicting SFRs. In particular our data-driven approach, in contrast to model libraries, intrinsically allows for the complexity of galaxy formation and can handle sample biases. We advocate that obtaining the calibration for this method should be one of the goals of next-generation galaxy surveys.
In this research, we provide a new, efficient method to select infrared (IR) active galatic nucleus (AGN). In the past, AGN selection in IR had been established by many studies using color-color diagrams. However, those methods have a problem in common that the number of bands is limited. The AKARI North Ecliptic Pole (NEP) survey was carried out by the AKARI Infrared Camera (IRC), which has 9 filters in mid-IR with a continuous wavelength coverage from 2 to 24$mu$m$^{-1}$. Based on the intrinsic different mid-IR features of AGN and star-forming galaxies (SFGs), we performed SED fitting to separate these two populations by the best-fitting model. In the X-ray AGN sample, our method by SED fitting selects 50$%$ AGNs, while the previous method by colour criteria recovers only 30$%$ of them, which is a significant improvement. Furthermore, in the whole NEP deep sample, SED fitting selects two times more AGNs than the color selection. This may imply that the black hole accretion history could be more stronger than people expected before.
Until recently, it has been possible only for nearby galaxies to study the scaling relations between central black hole and host galaxy in detail. Because of the small number densities at low redshift, (luminous) AGN are underrepresented in such detailed studies. The advent of adaptive optics (AO) at large telescopes helps overcoming this hurdle, allowing to reach small linear scales over a wide range in redshift. Finding AO-suitable targets, i.e., AGN having a nearby reference star, and carrying out an initial multiwavelength classification is an excellent use case for the Virtual Observatory. We present our Virtual-Observatory approach to select an AO-suitable catalog of X-ray-emitting AGN at redshifts 0.1<z<1.
Here we review some of the main issues related to multi-wavelength source identification and characterization, with particular emphasis on the field of X-ray surveys carried out over the last years. This complex and time-consuming process is going to represent one of the main difficulties over the coming years, when significantly larger surveys, both in area and depth, will be carried out with the new generations of space- and ground-based facilities like e.g. eROSITA, WISE, VISTA, Pan-STARRS, and LSST. The Virtual Observatory can offer a reliable way to approach to a new concept of data handling and multi-wavelength source characterization, provided that uniform and rigorous data analyses and extensive quality checks are performed.
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