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Register a new userAccurate photometric redshifts for the CFHT Legacy Survey calibrated using the VIMOS VLT Deep Survey
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We present photometric redshifts for an uniquely large and deep sample of 522286 objects with i_{AB}<25 in the Canada-France Legacy Survey ``Deep Survey fields, which cover a total effective area of 3.2 deg^2. We use 3241 spectroscopic redshifts with 0<z<5 from the VIMOS VLT Deep Survey as a calibration to derive these photometric redshifts. We devise a robust calibration method which removes systematic trends in the photometric redshifts and significantly reduces the fraction of catastrophic errors. We use our unique spectroscopic sample to present a detailed assessment of the robustness of the photometric redshift sample. For a sample selected at i_{AB}<24, we reach a redshift accuracy of sigma_{Delta z/(1+z)}=0.037 with eta=3.7% of catastrophic error. The reliability of our photometric redshifts is lower for fainter objects: we find sigma_{Delta z/(1+z)}=0.029, 0.043 and eta=1.7%, 5.4% for samples selected at i_{AB}=17.5-22.5 and 22.5-24 respectively. We find that the photometric redshifts of starburst galaxies in our sample are less reliable: although these galaxies represent only 18% of the spectroscopic sample they are responsible for 54% of the catastrophic errors. We find an excellent agreement between the photometric and the VVDS spectroscopic redshift distributions at i_{AB}<24. Finally, we compare the redshift distributions of i selected galaxies on the four CFHTLS deep fields, showing that cosmic variance is already present on fields of 0.8 deg^2.
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[Abridged] We present a homogeneous and complete catalogue of optical groups identified in the purely flux limited (17.5<=I<=24.0) VIMOS-VLT Deep Survey (VVDS). We use mock catalogues extracted from the MILLENNIUM simulation, to correct for potential systematics that might affect the overall distribution as well as the individual properties of the identified systems. Simulated samples allow us to forecast the number and properties of groups that can be potentially found in a survey with VVDS-like selection functions. We use them to correct for the expected incompleteness and also to asses how well galaxy redshifts trace the line-of-sight velocity dispersion of the underlying mass overdensity. In particular, we train on these mock catalogues the adopted group-finding technique (the Voronoi-Delaunay Method, VDM). The goal is to fine-tune its free parameters, recover in a robust and unbiased way the redshift and velocity dispersion distributions of groups and maximize the level of completeness (C) and purity (P) of the group catalogue. We identify 318 VVDS groups with at least 2 members within 0.2<=z<=1.0, among which 144 (/30) with at least 3 (/5) members. The sample has globally C=60% and P=50%. Nearly 45% of the groups with at least 3 members are still recovered if we run the algorithm with a parameter set which maximizes P (75%). We exploit the group sample to study the redshift evolution of the fraction f_b of blue galaxies (U-B<=1) within 0.2<=z<=1. We find that f_b is significantly lower in groups than in the whole ensemble of galaxies irrespectively of their environment. These quantities increase with redshift, with f_b in groups showing a marginally significant steeper increase. We also confirm that, at any explored redshift, f_b decreases for increasing group richness, and we extend towards fainter luminosities the magnitude range over which this result holds.
We present the type-1 active galactic nuclei (AGN) sample extracted from the VIMOS VLT Deep Survey first observations of 21000 spectra in 1.75 square degree. This sample, which is purely magnitude limited, free of morphological or color selection biases, contains 130 broad line AGN (BLAGN) spectra with redshift up to 5. Our data are divided into a wide (Iab < 22.5) and a deep (Iab < 24) subsample containing 56 and 74 objects respectively. Because of its depth and selection criteria, this sample is uniquely suited to study the population of faint type-1 AGN. Our measured surface density (~ 472 +- 48 BLAGN per square degree with Iab < 24) is significantly higher than that of any other optically selected sample of BLAGN with spectroscopic confirmation. By applying a morphological and color analysis to our AGN sample we find that: (1)~23% of the AGN brighter than Iab=22.5 are classified as extended; this percentage increases to ~42% for those with z < 1.6; (2) a non-negligible fraction of our BLAGN are lying close to the color space area occupied by stars in u*-g versus g-r color-color diagram. This leads us to the conclusion that classical optical ultraviolet preselection technique, if employed at such deep magnitudes (Iab=22.5) in conjuction with a preselection of point-like sources, can miss miss up to ~35% of the AGN population. Finally, we present a composite spectrum of our sample of objects. While the continuum shape is very similar to that of the SDSS composite at short wavelengths, it is much redder than it at lambda > 3000 A. We interpret this as due to significant contamination from emission of the host galaxies, as expected from the faint absolute magnitudes sampled by our survey.
The Canada-France-Hawaii Legacy Survey (CFHTLS) comprising about 25 000 MegaCam images was data mined to search for serendipitous encounters of known Near Earth Asteroids (NEAs) and Potentially Hazardous Asteroids (PHAs). A total of 143 asteroids (109 NEAs and 34 PHAs) were found on 508 candidate images which were field corrected and measured carefully, and their astrometry was reported to Minor Planet Centre. Both recoveries and precoveries (apparitions before discovery) were reported, including data for 27 precovered asteroids (20 NEAs and 7 PHAs) and 116 recovered asteroids (89 NEAs and 27 PHAs). Our data prolonged arcs for 41 orbits at first or last opposition, refined 35 orbits by fitting data taken at one new opposition, recovered 6 NEAs at their second opposition and allowed us to ameliorate most orbits and their Minimal Orbital Intersection Distance (MOID), an important parameter to monitor for potential Earth impact hazard in the future.
We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724 galaxies for which the spectroscopic redshift is obtained from SDSS, and magnitudes and colours are obtained from the Pan-STARRS1 Data Release 2 survey. The photometric redshift of a galaxy is then estimated by means of a local linear regression in a 5-dimensional magnitude and colour space. Our method achieves an average bias of $overline{Delta z_{rm norm}}=-2.01 times 10^{-4}$, a standard deviation of $sigma(Delta z_{rm norm})=0.0298$, and an outlier rate of $P_o=4.32%$ when cross-validating on the training set. Even though the relation between each of the Pan-STARRS1 colours and the spectroscopic redshifts is noisier than for SDSS colours, the results obtained by our method are very close to those yielded by SDSS data. The proposed method has the additional advantage of allowing the estimation of photometric redshifts on a larger portion of the sky ($sim 3/4$ vs $sim 1/3$). The training set and the code implementing this method are publicly available at www.testaddress.com.
We study the performance of the hybrid template-machine-learning photometric redshift (photo-$z$) algorithm Delight, which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the $40$ PAUS narrow bands with $6$ broadband fluxes ($uBVriz$) in the COSMOS field using three different methods, including a new method which utilises the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. Delight achieves a photo-$z$ $68$th percentile error of $sigma_{68}=0.0081(1+z)$ without any quality cut for galaxies with $i_mathrm{auto}<22.5$ as compared to $0.0089(1+z)$ and $0.0202(1+z)$ for the BPz and ANNz2 codes, respectively. Delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than BPz and ANNz2. Common photo-$z$ outliers of Delight and BCNz2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrowband fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of BCNz2 and Delight, allowing us to achieve a photo-$z$ quality of $sigma_{68}<0.0035(1+z)$ at a magnitude of $i_mathrm{auto}<22.5$ while keeping $50$ per cent objects of the galaxy sample.
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