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Register a new userELDAR, a new method to identify AGN in multi-filter surveys: the ALHAMBRA test-case
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Added by
Jon\\'as Chaves-Montero
Publication date
2017
fields
Physics
and research's language is
English
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We present ELDAR, a new method that exploits the potential of medium- and narrow-band filter surveys to securely identify active galactic nuclei (AGN) and determine their redshifts. Our methodology improves on traditional approaches by looking for AGN emission lines expected to be identified against the continuum, thanks to the width of the filters. To assess its performance, we apply ELDAR to the data of the ALHAMBRA survey, which covered an effective area of $2.38,{rm deg}^2$ with 20 contiguous medium-band optical filters down to F814W$simeq 24.5$. Using two different configurations of ELDAR in which we require the detection of at least 2 and 3 emission lines, respectively, we extract two catalogues of type-I AGN. The first is composed of 585 sources ($79,%$ of them spectroscopically-unknown) down to F814W$=22.5$ at $z_{rm phot}>1$, which corresponds to a surface density of $209,{rm deg}^{-2}$. In the second, the 494 selected sources ($83,%$ of them spectroscopically-unknown) reach F814W$=23$ at $z_{rm phot}>1.5$, for a corresponding number density of $176,{rm deg}^{-2}$. Then, using samples of spectroscopically-known AGN in the ALHAMBRA fields, for the two catalogues we estimate a completeness of $73,%$ and $67,%$, and a redshift precision of $1.01,%$ and $0.86,%$ (with outliers fractions of $8.1,%$ and $5.8,%$). At $z>2$, where our selection performs best, we reach $85,%$ and $77,%$ completeness and we find no contamination from galaxies.
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We present MUFFIT, a new generic code optimized to retrieve the main stellar population parameters of galaxies in photometric multi-filter surveys, and we check its reliability and feasibility with real galaxy data from the ALHAMBRA survey. Making use of an error-weighted $chi^2$-test, we compare the multi-filter fluxes of galaxies with the synthetic photometry of mixtures of two single stellar populations at different redshifts and extinctions, to provide through a Monte Carlo method the most likely range of stellar population parameters (mainly ages and metallicities), extinctions, redshifts, and stellar masses. To improve the diagnostic reliability, MUFFIT identifies and removes from the analysis those bands that are significantly affected by emission lines. We highlight that the retrieved age-metallicity locus for a sample of $z le 0.22$ early-type galaxies in ALHAMBRA at different stellar mass bins are in very good agreement with the ones from SDSS spectroscopic diagnostics. Moreover, a one-to-one comparison between the redshifts, ages, metallicities, and stellar masses derived spectroscopically for SDSS and by MUFFIT for ALHAMBRA reveals good qualitative agreements in all the parameters. In addition, and using as input the results from photometric-redshift codes, MUFFIT improves the photometric-redshift accuracy by $sim 10$-$20%$, and it also detects nebular emissions in galaxies, providing physical information about their strengths. Our results show the potential of multi-filter galaxy data to conduct reliable stellar population studies with the appropiate analysis techniques, as MUFFIT.
Stars form through the gravitational collapse of molecular cloud cores. Before collapsing, the cores are supported by thermal pressure and turbulent motions. A question of critical importance for the understanding of star formation is how to observationally discern whether a core has already initiated gravitational collapse or is still in hydrostatic balance. The canonical method to identify gravitational collapse is based on the observed density radial profile, which would change from a Bonnor-Ebert type toward power laws as the core collapses. In practice, due to the projection effect, the resolution limit, and other caveats, it has been difficult to directly reveal the dynamical status of cores, particularly in massive star-forming regions. We here propose a novel, straight-forward diagnostic, namely, the collapsing index (CI), which can be modeled and calculated based on the radial profile of the line width of dense gas. A meaningful measurement of CI requires spatially and spectrally resolved images of optically thin and chemically stable dense gas tracers. ALMA observations are making such data sets increasingly available for massive star-forming regions. Applying our method to one of the deepest dense-gas spectral images ever taken toward such a region, namely, the Orion molecular cloud, we detect the dynamical status of selected cores therein. We observationally distinguished a collapsing core in a massive star-forming region from a hydrostatical one. Our approach would help significantly improve our understanding of the interaction between gravity and turbulence within molecular cloud cores in the process of star formation.
Various observational techniques have been used to survey galaxies and AGN, from X-rays to radio frequencies, both photometric and spectroscopic. I will review these techniques aimed at the study of galaxy evolution and of the role of AGNs and star formation as the two main energy production mechanisms. I will then present as a new observational approach the far-IR spectroscopic surveys that could be done with planned astronomical facilities of the next future, such as SPICA from the space and CCAT from the ground.
Recent models of super-massive black hole (SMBH) and host galaxy joint evolution predict the presence of a key phase where accretion, traced by obscured Active Galactic Nuclei (AGN) emission, is coupled with powerful star formation. Then feedback processes likely self-regulate the SMBH growth and quench the star-formation activity. AGN in this important evolutionary phase have been revealed in the last decade via surveys at different wavelengths. On the one hand, moderate-to-deep X-ray surveys have allowed a systematic search for heavily obscured AGN, up to very high redshifts (z~5). On the other hand, infrared/optical surveys have been invaluable in offering complementary methods to select obscured AGN also in cases where the nuclear X-ray emission below 10 keV is largely hidden to our view. In this review I will present my personal perspective of the field of obscured accretion from AGN surveys.
We aim to study the effect of environment on the presence and fuelling of Active Galactic Nuclei (AGN) in massive galaxy clusters. We explore the use of different AGN detection techniques with the goal of selecting AGN across a broad range of luminosities, AGN/host galaxy flux ratios, and obscuration levels. From a sample of 12 galaxy clusters at redshifts 0.5 < z < 0.9, we identify AGN candidates using optical variability from multi-epoch HST imaging, X-ray point sources in Chandra images, and mid-IR SED power-law fits through the Spitzer IRAC channels. We find 178 optical variables, 74 X-ray point sources, and 64 IR power law sources, resulting in an average of ~25 AGN per cluster. We find no significant difference between the fraction of AGN among galaxies in clusters and the percentage of similarly-detected AGN in field galaxy studies (~2.5%). This result provides evidence that galaxies are still able to fuel accretion onto their supermassive black holes, even in dense environments. We also investigate correlations between the percentage of AGN and cluster physical properties such as mass, X-ray luminosity, size, morphology class and redshift. We find no significant correlations among cluster properties and the percentage of AGN detected.
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