62 research outputs found

    Missing Lensed Images and the Galaxy Disk Mass in CXOCY J220132.8-320144

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    The CXOCY J220132.8-320144 system consists of an edge-on spiral galaxy lensing a background quasar into two bright images. Previous efforts to constrain the mass distribution in the galaxy have suggested that at least one additional image must be present (Castander et al. 2006). These extra images may be hidden behind the disk which features a prominent dust lane. We present and analyze Hubble Space Telescope (HST) observations of the system. We do not detect any extra images, but the observations further narrow the observable parameters of the lens system. We explore a range of models to describe the mass distribution in the system and find that a variety of acceptable model fits exist. All plausible models require 2 magnitudes of dust extinction in order to obscure extra images from detection, and some models may require an offset between the center of the galaxy and the center of the dark matter halo of 1 kiloparsec. Currently unobserved images will be detectable by future James Webb Space Telescope (JWST) observations and will provide strict constraints on the fraction of mass in the disk.Comment: 10 pages, 8 figures, 6 tables. Minor changes, version accepted for publication in Ap

    CosmoHub : Interactive exploration and distribution of astronomical data on Hadoop

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    We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informacio Científica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ciencies de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of catalogued information and 50 × 109 astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of 109 objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes

    The PAU survey: Estimating galaxy photometry with deep learning

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    With the dramatic rise in high-quality galaxy data expected from Euclid and Vera C. Rubin Observatory, there will be increasing demand for fast high-precision methods for measuring galaxy fluxes. These will be essential for inferring the redshifts of the galaxies. In this paper, we introduce Lumos, a deep learning method to measure photometry from galaxy images. Lumos builds on BKGnet, an algorithm to predict the background and its associated error, and predicts the background-subtracted flux probability density function. We have developed Lumos for data from the Physics of the Accelerating Universe Survey (PAUS), an imaging survey using 40 narrow-band filter camera (PAUCam). PAUCam images are affected by scattered light, displaying a background noise pattern that can be predicted and corrected for. On average, Lumos increases the SNR of the observations by a factor of 2 compared to an aperture photometry algorithm. It also incorporates other advantages like robustness towards distorting artifacts, e.g. cosmic rays or scattered light, the ability of deblending and less sensitivity to uncertainties in the galaxy profile parameters used to infer the photometry. Indeed, the number of flagged photometry outlier observations is reduced from 10% to 2%, comparing to aperture photometry. Furthermore, with Lumos photometry, the photo-z scatter is reduced by ~10% with the Deepz machine learning photo-z code and the photo-z outlier rate by 20%. The photo-z improvement is lower than expected from the SNR increment, however currently the photometric calibration and outliers in the photometry seem to be its limiting factor.Comment: 20 pages, 22 figure

    Galaxy clusters and groups in the ALHAMBRA Survey

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    We present a catalogue of 348 galaxy clusters and groups with 0.2<z<1.20.2<z<1.2 selected in the 2.78 deg2deg^2 ALHAMBRA Survey. The high precision of our photometric redshifts, close to 1%1\%, and the wide spread of the seven ALHAMBRA pointings ensure that this catalogue has better mass sensitivity and is less affected by cosmic variance than comparable samples. The detection has been carried out with the Bayesian Cluster Finder (BCF), whose performance has been checked in ALHAMBRA-like light-cone mock catalogues. Great care has been taken to ensure that the observable properties of the mocks photometry accurately correspond to those of real catalogues. From our simulations, we expect to detect galaxy clusters and groups with both 70%70\% completeness and purity down to dark matter halo masses of Mh3×1013MM_h\sim3\times10^{13}\rm M_{\odot} for z<0.85z<0.85. Cluster redshifts are expected to be recovered with 0.6%\sim0.6\% precision for z<1z<1. We also expect to measure cluster masses with σMhMCL0.250.35dex\sigma_{M_h|M^*_{CL}}\sim0.25-0.35\, dex precision down to 3×1013M\sim3\times10^{13}\rm M_{\odot}, masses which are 50%50\% smaller than those reached by similar work. We have compared these detections with previous optical, spectroscopic and X-rays work, finding an excellent agreement with the rates reported from the simulations. We have also explored the overall properties of these detections such as the presence of a colour-magnitude relation, the evolution of the photometric blue fraction and the clustering of these sources in the different ALHAMBRA fields. Despite the small numbers, we observe tentative evidence that, for a fixed stellar mass, the environment is playing a crucial role at lower redshifts (z<<0.5).Comment: Accepted for publication in MNRAS. Catalogues and figures available online and under the following link: http://bascaso.net46.net/ALHAMBRA_clusters.htm

    The impact from survey depth and resolution on the morphological classification of galaxies

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    We consistently analyse for the first time the impact of survey depth and spatial resolution on the most used morphological parameters for classifying galaxies through non-parametric methods: Abraham and Conselice-Bershady concentration indices, Gini, M20moment of light, asymmetry, and smoothness. Three different non-local data sets are used, Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) and Subaru/XMMNewton Deep Survey (SXDS, examples of deep ground-based surveys), and Cosmos Evolution Survey (COSMOS, deep space-based survey). We used a sample of 3000 local, visually classified galaxies, measuring their morphological parameters at their real redshifts (z ~ 0). Then we simulated them to match the redshift and magnitude distributions of galaxies in the non-local surveys. The comparisons of the two sets allow us to put constraints on the use of each parameter for morphological classification and evaluate the effectiveness of the commonly used morphological diagnostic diagrams. All analysed parameters suffer from biases related to spatial resolution and depth, the impact of the former being much stronger. When including asymmetry and smoothness in classification diagrams, the noise effects must be taken into account carefully, especially for ground-based surveys. M20 is significantly affected, changing both the shape and range of its distribution at all brightness levels. We suggest that diagnostic diagrams based on 2-3 parameters should be avoided when classifying galaxies in ground-based surveys, independently of their brightness; for COSMOS they should be avoided for galaxies fainter than F814 = 23.0. These results can be applied directly to surveys similar to ALHAMBRA, SXDS and COSMOS, and also can serve as an upper/lower limit for shallower/deeper ones.Ministerio de Economía y Competitividad AYA2010-15169, AYA2013-42227-P, AYA2013-4318

    The Multi-Object, Fiber-Fed Spectrographs for SDSS and the Baryon Oscillation Spectroscopic Survey

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    We present the design and performance of the multi-object fiber spectrographs for the Sloan Digital Sky Survey (SDSS) and their upgrade for the Baryon Oscillation Spectroscopic Survey (BOSS). Originally commissioned in Fall 1999 on the 2.5-m aperture Sloan Telescope at Apache Point Observatory, the spectrographs produced more than 1.5 million spectra for the SDSS and SDSS-II surveys, enabling a wide variety of Galactic and extra-galactic science including the first observation of baryon acoustic oscillations in 2005. The spectrographs were upgraded in 2009 and are currently in use for BOSS, the flagship survey of the third-generation SDSS-III project. BOSS will measure redshifts of 1.35 million massive galaxies to redshift 0.7 and Lyman-alpha absorption of 160,000 high redshift quasars over 10,000 square degrees of sky, making percent level measurements of the absolute cosmic distance scale of the Universe and placing tight constraints on the equation of state of dark energy. The twin multi-object fiber spectrographs utilize a simple optical layout with reflective collimators, gratings, all-refractive cameras, and state-of-the-art CCD detectors to produce hundreds of spectra simultaneously in two channels over a bandpass covering the near ultraviolet to the near infrared, with a resolving power R = \lambda/FWHM ~ 2000. Building on proven heritage, the spectrographs were upgraded for BOSS with volume-phase holographic gratings and modern CCD detectors, improving the peak throughput by nearly a factor of two, extending the bandpass to cover 360 < \lambda < 1000 nm, and increasing the number of fibers from 640 to 1000 per exposure. In this paper we describe the original SDSS spectrograph design and the upgrades implemented for BOSS, and document the predicted and measured performances.Comment: 43 pages, 42 figures, revised according to referee report and accepted by AJ. Provides background for the instrument responsible for SDSS and BOSS spectra. 4th in a series of survey technical papers released in Summer 2012, including arXiv:1207.7137 (DR9), arXiv:1207.7326 (Spectral Classification), and arXiv:1208.0022 (BOSS Overview

    Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

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    We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods—ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ—are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z’s. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z ¼ f0.45; 0.67; 1.00g. These bins each have systematic uncertainties δz ≲ 0.05 in the mean of the fiducial SKYNET photo-z nðzÞ. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of σ8 of approximately 3%. This shift is within the one sigma statistical errors on σ8 for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, Σcrit, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of nðzÞ of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis

    The Dark Energy Survey : more than dark energy – an overview

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    This overview paper describes the legacy prospect and discovery potential of the Dark Energy Survey (DES) beyond cosmological studies, illustrating it with examples from the DES early data. DES is using a wide-field camera (DECam) on the 4 m Blanco Telescope in Chile to image 5000 sq deg of the sky in five filters (grizY). By its completion, the survey is expected to have generated a catalogue of 300 million galaxies with photometric redshifts and 100 million stars. In addition, a time-domain survey search over 27 sq deg is expected to yield a sample of thousands of Type Ia supernovae and other transients. The main goals of DES are to characterize dark energy and dark matter, and to test alternative models of gravity; these goals will be pursued by studying large-scale structure, cluster counts, weak gravitational lensing and Type Ia supernovae. However, DES also provides a rich data set which allows us to study many other aspects of astrophysics. In this paper, we focus on additional science with DES, emphasizing areas where the survey makes a difference with respect to other current surveys. The paper illustrates, using early data (from ‘Science Verification’, and from the first, second and third seasons of observations), what DES can tell us about the Solar system, the Milky Way, galaxy evolution, quasars and other topics. In addition, we show that if the cosmological model is assumed to be +cold dark matter, then important astrophysics can be deduced from the primary DES probes. Highlights from DES early data include the discovery of 34 trans-Neptunian objects, 17 dwarf satellites of the Milky Way, one published z > 6 quasar (and more confirmed) and two published superluminous supernovae (and more confirmed)
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