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Register a new userA $K_s$-band selected catalogue of objects in the ALHAMBRA survey
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Added by
Lorena Nieves-Seoane
Publication date
2016
fields
Physics
and research's language is
English
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The original ALHAMBRA catalogue contained over 400,000 galaxies selected using a synthetic F814W image, to the magnitude limit AB(F814W)$approx$24.5. Given the photometric redshift depth of the ALHAMBRA multiband data (<z>=0.86) and the approximately $I$-band selection, there is a noticeable bias against red objects at moderate redshift. We avoid this bias by creating a new catalogue selected in the $K_s$ band. This newly obtained catalogue is certainly shallower in terms of apparent magnitude, but deeper in terms of redshift, with a significant population of red objects at $z>1$. We select objects using the $K_s$ band images, which reach an approximate AB magnitude limit $K_s approx 22$. We generate masks and derive completeness functions to characterize the sample. We have tested the quality of the photometry and photometric redshifts using both internal and external checks. Our final catalogue includes $approx 95,000$ sources down to $K_s approx 22$, with a significant tail towards high redshift. We have checked that there is a large sample of objects with spectral energy distributions that correspond to that of massive, passively evolving galaxies at $z > 1$, reaching as far as $z approx 2.5$. We have tested the possibility of combining our data with deep infrared observations at longer wavelengths, particularly Spitzer IRAC data.
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We present the first catalogue of point-source UV-excess sources selected from the UVEX survey. UVEX images the Northern Galactic Plane in the U, g, r and HeI5875 bands in the Galactic latitude range -5deg<b<+5deg. Through an automated algorithm, which works on a field-to-field basis, we select blue UV-excess sources in 211 square degrees from the (U-g) vs. (g-r) colour-colour diagram and the g vs. (U-g) and g vs. (g-r) colour-magnitude diagrams. The UV-excess catalogue covers the magnituderange 14<g<22.5, contains 2170 sources and consists of a mix of white dwarfs, post-common-envelope objects, interacting binaries, quasars and AGN. Two other samples of outliers were found during the selection: i) a subdwarf sample, consisting of no less than 9872 candidate metal-poor stars or lightly reddened main-sequence stars, and ii) a purple sample consisting of 803 objects, most likely a mix of reddened late M-giants, T Tauri stars, planetary nebulae, symbiotic stars and carbon stars. Cross-matching the selected UV-excess catalogue with other catalogues aids with the first classification of the different populations and shows that more than 99% of our selected sources are unidentified sources.
We present the results of a programme to search and identify the nature of unusual sources within the All-sky Wide-field Infrared Survey Explorer (WISE) that is based on a machine-learning algorithm for anomaly detection, namely one-class support vector machines (OCSVM). Designed to detect sources deviating from a training set composed of known classes, this algorithm was used to create a model for the expected data based on WISE objects with spectroscopic identifications in the Sloan Digital Sky Survey (SDSS). Subsequently, it marked as anomalous those sources whose WISE photometry was shown to be inconsistent with this model. We report the results from optical and near-infrared spectroscopy follow-up observations of a subset of 36 bright ($g_{AB}$<19.5) objects marked as anomalous by the OCSVM code to verify its performance. Among the observed objects, we identified three main types of sources: i) low redshift (z~0.03-0.15) galaxies containing large amounts of hot dust (53%), including three Wolf-Rayet galaxies; ii) broad-line quasi-stellar objects (QSOs) (33%) including low-ionisation broad absorption line (LoBAL) quasars and a rare QSO with strong and narrow ultraviolet iron emission; iii) Galactic objects in dusty phases of their evolution (3%). The nature of four of these objects (11%) remains undetermined due to low signal-to-noise or featureless spectra. The current data show that the algorithm works well at detecting rare but not necessarily unknown objects among the brightest candidates. They mostly represent peculiar sub-types of otherwise well-known sources.
We study the clustering of galaxies as a function of spectral type and redshift in the range $0.35 < z < 1.1$ using data from the Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) survey. The data cover 2.381 deg$^2$ in 7 fields, after applying a detailed angular selection mask, with accurate photometric redshifts [$sigma_z < 0.014(1+z)$] down to $I_{AB} < 24$. From this catalog we draw five fixed number density, redshift-limited bins. We estimate the clustering evolution for two different spectral populations selected using the ALHAMBRA-based photometric templates: quiescent and star-forming galaxies. For each sample, we measure the real-space clustering using the projected correlation function. Our calculations are performed over the range $[0.03,10.0] h^{-1}$ Mpc, allowing us to find a steeper trend for $r_p lesssim 0.2 h^{-1}$ Mpc, which is especially clear for star-forming galaxies. Our analysis also shows a clear early differentiation in the clustering properties of both populations: star-forming galaxies show weaker clustering with evolution in the correlation length over the analysed redshift range, while quiescent galaxies show stronger clustering already at high redshifts, and no appreciable evolution. We also perform the bias calculation where similar segregation is found, but now it is among the quiescent galaxies where a growing evolution with redshift is clearer. These findings clearly corroborate the well known colour-density relation, confirming that quiescent galaxies are mainly located in dark matter halos that are more massive than those typically populated by star-forming galaxies.
The relative cosmic variance ($sigma_v$) is a fundamental source of uncertainty in pencil-beam surveys and, as a particular case of count-in-cell statistics, can be used to estimate the bias between galaxies and their underlying dark-matter distribution. Our goal is to test the significance of the clustering information encoded in the $sigma_v$ measured in the ALHAMBRA survey. We measure the cosmic variance of several galaxy populations selected with $B-$band luminosity at $0.35 leq z < 1.05$ as the intrinsic dispersion in the number density distribution derived from the 48 ALHAMBRA subfields. We compare the observational $sigma_v$ with the cosmic variance of the dark matter expected from the theory, $sigma_{v,{rm dm}}$. This provides an estimation of the galaxy bias $b$. The galaxy bias from the cosmic variance is in excellent agreement with the bias estimated by two-point correlation function analysis in ALHAMBRA. This holds for different redshift bins, for red and blue subsamples, and for several $B-$band luminosity selections. We find that $b$ increases with the $B-$band luminosity and the redshift, as expected from previous work. Moreover, red galaxies have a larger bias than blue galaxies, with a relative bias of $b_{rm rel} = 1.4 pm 0.2$. Our results demonstrate that the cosmic variance measured in ALHAMBRA is due to the clustering of galaxies and can be used to characterise the $sigma_v$ affecting pencil-beam surveys. In addition, it can also be used to estimate the galaxy bias $b$ from a method independent of correlation functions.
The Herschel Gould Belt Survey key project mapped the bulk of nearby star-forming molecular clouds in five far-infrared bands with the aim of compiling complete census of prestellar cores and young, embedded protostars. In this paper, we present the catalogue of the dense cores and YSOs/protostars extracted from the Herschel maps of the Lupus I, III, and IV molecular clouds. The physical properties of the detected objects were derived by fitting their spectral energy distributions. A total of 532 dense cores, out of which 103 are presumably prestellar in nature, and 38 YSOs/protostars have been detected in the three clouds. Almost all the prestellar cores are associated with filaments against only about one third of the unbound cores and YSOs/protostars. Prestellar core candidates are found even in filaments that are on average thermally sub-critical and over a background column density lower than that measured in other star forming regions so far. The core mass function of the prestellar cores peaks between 0.2 and 0.3 solar masses and it is compatible with the log-normal shape found in other regions. Herschel data reveal several, previously undetected, protostars and new candidates of Class 0 and Class II with transitional disks. We estimate the evolutionary status of the YSOs/protostars using two independent indicators: the $alpha$ index and the fitting of the spectral energy distribution from near- to far-infrared wavelengths. For 70% of the objects, the evolutionary stages derived with the two methods are in agreement. Lupus is confirmed to be a very low-mass star-forming region, both in terms of the prestellar condensations and of the diffuse medium. Noticeably, in the Lupus clouds we have found star formation activity associated with interstellar medium at low column density, usually quiescent in other (more massive) star forming regions.
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