arXiv subjects

I. Sevilla-Noarbe

Publications and source records attributed to I. Sevilla-Noarbe.

At least 379 records · Page 21Linked to original sources

arXiv2016

No galaxy left behind: accurate measurements with the faintest objects in the Dark Energy Survey

Accurate statistical measurement with large imaging surveys has traditionally required throwing away a sizable fraction of the data. This is because most measurements have have relied on selecting nearly complete samples, where variations in the composition of the galaxy population with seeing, depth, or other survey characteristics are small. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of stars or galaxies detectable in an imaging survey. We have implemented our proposal in Balrog, a software package which embeds fake objects in real imaging in order to accurately characterize measurement biases. We demonstrate this technique with an angular clustering measurement using Dark Energy Survey (DES) data. We first show that recovery of our injected galaxies depends on a wide variety of survey characteristics in the same way as the real data. We then construct a flux-limited sample of the faintest galaxies in DES, chosen specifically for their sensitivity to depth and seeing variations. Using the synthetic galaxies as randoms in the standard Landy-Szalay correlation function estimator suppresses the effects of variable survey selection by at least two orders of magnitude. With this correction, our measured angular clustering is found to be in excellent agreement with that of a matched sample drawn from much deeper, higher-resolution space-based Cosmological Evolution Survey (COSMOS) imaging; over angular scales of $0.004^{\circ} < θ< 0.2^{\circ}$, we find a best-fit scaling amplitude between the DES and COSMOS measurements of $1.00 \pm 0.09$. We expect this methodology to be broadly useful for extending the statistical reach of measurements in a wide variety of coming imaging surveys.

astro-ph.GA↗

arXiv2016

DES14X3taz: A Type I Superluminous Supernova Showing a Luminous, Rapidly Cooling Initial Pre-Peak Bump

We present DES14X3taz, a new hydrogen-poor super luminous supernova (SLSN-I) discovered by the Dark Energy Survey (DES) supernova program, with additional photometric data provided by the Survey Using DECam for Superluminous Supernovae (SUDSS). Spectra obtained using OSIRIS on the Gran Telescopio CANARIAS (GTC) show DES14X3taz is a SLSN-I at z=0.608. Multi-color photometry reveals a double-peaked light curve: a blue and relatively bright initial peak that fades rapidly prior to the slower rise of the main light curve. Our multi-color photometry allows us, for the first time, to show that the initial peak cools from 22,000K to 8,000K over 15 rest-frame days, and is faster and brighter than any published core-collapse supernova, reaching 30% of the bolometric luminosity of the main peak. No physical Nickel powered model can fit this initial peak. We show that a shock-cooling model followed by a magnetar driving the second phase of the light curve can adequately explain the entire light curve of DES14X3taz. Models involving the shock-cooling of extended circumstellar material at a distance of ~400 solar radii are preferred over the cooling of shock-heated surface layers of a stellar envelope. We compare DES14X3taz to the few double-peaked SLSN-I events in the literature. Although the rise-times and characteristics of these initial peaks differ, there exists the tantalizing possibility that they can be explained by one physical interpretation.

astro-ph.SR↗

arXiv2016

CMB lensing tomography with the DES Science Verification galaxies

We measure the cross-correlation between the galaxy density in the Dark Energy Survey (DES) Science Verification data and the lensing of the cosmic microwave background (CMB) as reconstructed with the Planck satellite and the South Pole Telescope (SPT). When using the DES main galaxy sample over the full redshift range $0.2 < z < 1.2$, a cross-correlation signal is detected at $6 σ$ and $4σ$ with SPT and Planck respectively. We then divide the DES galaxies into five photometric redshift bins, finding significant ($>$$2 σ$) detections in all bins. Comparing to the fiducial Planck cosmology, we find the redshift evolution of the signal matches expectations, although the amplitude is consistently lower than predicted across redshift bins. We test for possible systematics that could affect our result and find no evidence for significant contamination. Finally, we demonstrate how these measurements can be used to constrain the growth of structure across cosmic time. We find the data are fit by a model in which the amplitude of structure in the $z<1.2$ universe is $0.73 \pm 0.16$ times as large as predicted in the LCDM Planck cosmology, a $1.7σ$ deviation.

astro-ph.CO↗

arXiv2015

Automated Transient Identification in the Dark Energy Survey

We describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where it was trained using a sample of 898,963 signal and background events generated by the transient detection pipeline. After reprocessing the data collected during the first DES-SN observing season (Sep. 2013 through Feb. 2014) using the algorithm, the number of transient candidates eligible for human scanning decreased by a factor of 13.4, while only 1 percent of the artificial Type Ia supernovae (SNe) injected into search images to monitor survey efficiency were lost, most of which were very faint events. Here we characterize the algorithm's performance in detail, and we discuss how it can inform pipeline design decisions for future time-domain imaging surveys, such as the Large Synoptic Survey Telescope and the Zwicky Transient Facility. An implementation of the algorithm and the training data used in this paper are available at http://portal.nersc.gov/project/dessn/autoscan.

astro-ph.IM↗

arXiv2015

Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data

We study the clustering of galaxies detected at $i<22.5$ in the Science Verification observations of the Dark Energy Survey (DES). Two-point correlation functions are measured using $2.3\times 10^6$ galaxies over a contiguous 116 deg$^2$ region in five bins of photometric redshift width $Δz = 0.2$ in the range $0.2 < z < 1.2.$ The impact of photometric redshift errors are assessed by comparing results using a template-based photo-$z$ algorithm (BPZ) to a machine-learning algorithm (TPZ). A companion paper (Leistedt et al 2015) presents maps of several observational variables (e.g. seeing, sky brightness) which could modulate the galaxy density. Here we characterize and mitigate systematic errors on the measured clustering which arise from these observational variables, in addition to others such as Galactic dust and stellar contamination. After correcting for systematic effects we measure galaxy bias over a broad range of linear scales relative to mass clustering predicted from the Planck $Λ$CDM model, finding agreement with CFHTLS measurements with $χ^2$ of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. We test a "linear bias" model, in which the galaxy clustering is a fixed multiple of the predicted non-linear dark-matter clustering. The precision of the data allow us to determine that the linear bias model describes the observed galaxy clustering to $2.5\%$ accuracy down to scales at least $4$ to $10$ times smaller than those on which linear theory is expected to be sufficient.

astro-ph.CO↗

arXiv2015

Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing

We measure the cross-correlation between weak lensing of galaxy images and of the cosmic microwave background (CMB). The effects of gravitational lensing on different sources will be correlated if the lensing is caused by the same mass fluctuations. We use galaxy shape measurements from 139 deg$^{2}$ of the Dark Energy Survey (DES) Science Verification data and overlapping CMB lensing from the South Pole Telescope (SPT) and Planck. The DES source galaxies have a median redshift of $z_{\rm med} {\sim} 0.7$, while the CMB lensing kernel is broad and peaks at $z{\sim}2$. The resulting cross-correlation is maximally sensitive to mass fluctuations at $z{\sim}0.44$. Assuming the Planck 2015 best-fit cosmology, the amplitude of the DES$\times$SPT cross-power is found to be $A = 0.88 \pm 0.30$ and that from DES$\times$Planck to be $A = 0.86 \pm 0.39$, where $A=1$ corresponds to the theoretical prediction. These are consistent with the expected signal and correspond to significances of $2.9 σ$ and $2.2 σ$ respectively. We demonstrate that our results are robust to a number of important systematic effects including the shear measurement method, estimator choice, photometric redshift uncertainty and CMB lensing systematics. Significant intrinsic alignment of galaxy shapes would increase the cross-correlation signal inferred from the data; we calculate a value of $A = 1.08 \pm 0.36$ for DES$\times$SPT when we correct the observations with a simple IA model. With three measurements of this cross-correlation now existing in the literature, there is not yet reliable evidence for any deviation from the expected LCDM level of cross-correlation, given the size of the statistical uncertainties and the significant impact of systematic errors, particularly IAs. We provide forecasts for the expected signal-to-noise of the combination of the five-year DES survey and SPT-3G.

astro-ph.CO↗

arXiv2015

Observation and Confirmation of Six Strong Lensing Systems in The Dark Energy Survey Science Verification Data

We report the observation and confirmation of the first group- and cluster-scale strong gravitational lensing systems found in Dark Energy Survey (DES) data. Through visual inspection of data from the Science Verification (SV) season, we identified 53 candidate systems. We then obtained spectroscopic follow-up of 21 candidates using the Gemini Multi-Object Spectrograph (GMOS) at the Gemini South telescope and the Inamori-Magellan Areal Camera and Spectrograph (IMACS) at the Magellan/Baade telescope. With this follow-up, we confirmed six candidates as gravitational lenses: Three of the systems are newly discovered, and the remaining three were previously known. Of the 21 observed candidates, the remaining 15 were either not detected in spectroscopic observations, were observed and did not exhibit continuum emission (or spectral features), or were ruled out as lensing systems. The confirmed sample consists of one group-scale and five galaxy cluster-scale lenses. The lensed sources range in redshift z ~ 0.80-3.2, and in i-band surface brightness i_{SB} ~ 23-25 mag/sq.-arcsec. (2" aperture). For each of the six systems, we estimate the Einstein radius and the enclosed mass, which have ranges ~ 5.0 - 8.6" and ~ 7.5 x 10^{12} - 6.4 x 10^{13} solar masses, respectively.

astro-ph.CO↗

arXiv2015

Weak lensing by galaxy troughs in DES Science Verification data

We measure the weak lensing shear around galaxy troughs, i.e. the radial alignment of background galaxies relative to underdensities in projections of the foreground galaxy field over a wide range of redshift in Science Verification data from the Dark Energy Survey. Our detection of the shear signal is highly significant (10 to 15$σ$ for the smallest angular scales) for troughs with the redshift range z in [0.2,0.5] of the projected galaxy field and angular diameters of 10 arcmin...1°. These measurements probe the connection between the galaxy, matter density, and convergence fields. By assuming galaxies are biased tracers of the matter density with Poissonian noise, we find agreement of our measurements with predictions in a fiducial Lambda cold dark matter model. The prediction for the lensing signal on large trough scales is virtually independent of the details of the underlying model for the connection of galaxies and matter. Our comparison of the shear around troughs with that around cylinders with large galaxy counts is consistent with a symmetry between galaxy and matter over- and underdensities. In addition, we measure the two-point angular correlation of troughs with galaxies which, in contrast to the lensing signal, is sensitive to galaxy bias on all scales. The lensing signal of troughs and their clustering with galaxies is therefore a promising probe of the statistical properties of matter underdensities and their connection to the galaxy field.

astro-ph.CO↗

arXiv2015

Physical properties of star clusters in the outer LMC as observed by the Dark Energy Survey

The Large Magellanic Cloud (LMC) harbors a rich and diverse system of star clusters, whose ages, chemical abundances, and positions provide information about the LMC history of star formation. We use Science Verification imaging data from the Dark Energy Survey to increase the census of known star clusters in the outer LMC and to derive physical parameters for a large sample of such objects using a spatially and photometrically homogeneous data set. Our sample contains 255 visually identified cluster candidates, of which 109 were not listed in any previous catalog. We quantify the crowding effect for the stellar sample produced by the DES Data Management pipeline and conclude that the stellar completeness is < 10% inside typical LMC cluster cores. We therefore develop a pipeline to sample and measure stellar magnitudes and positions around the cluster candidates using DAOPHOT. We also implement a maximum-likelihood method to fit individual density profiles and colour-magnitude diagrams. For 117 (from a total of 255) of the cluster candidates (28 uncatalogued clusters), we obtain reliable ages, metallicities, distance moduli and structural parameters, confirming their nature as physical systems. The distribution of cluster metallicities shows a radial dependence, with no clusters more metal-rich than [Fe/H] ~ -0.7 beyond 8 kpc from the LMC center. The age distribution has two peaks at ~ 1.2 Gyr and ~ 2.7 Gyr.

astro-ph.GA↗

arXiv2015

Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS

We present the results of the first test plates of the extended Baryon Oscillation Spectroscopic Survey. This paper focuses on the emission line galaxies (ELG) population targetted from the Dark Energy Survey (DES) photometry. We analyse the success rate, efficiency, redshift distribution, and clustering properties of the targets. From the 9000 spectroscopic redshifts targetted, 4600 have been selected from the DES photometry. The total success rate for redshifts between 0.6 and 1.2 is 71\% and 68\% respectively for a bright and faint, on average more distant, samples including redshifts measured from a single strong emission line. We find a mean redshift of 0.8 and 0.87, with 15 and 13\% of unknown redshifts respectively for the bright and faint samples. In the redshift range 0.6<z<1.2, for the most secure spectroscopic redshifts, the mean redshift for the bright and faint sample is 0.85 and 0.9 respectively. Star contamination is lower than 2\%. We measure a galaxy bias averaged on scales of 1 and 10~Mpc/h of 1.72 \pm 0.1 for the bright sample and of 1.78 \pm 0.12 for the faint sample. The error on the galaxy bias have been obtained propagating the errors in the correlation function to the fitted parameters. This redshift evolution for the galaxy bias is in agreement with theoretical expectations for a galaxy population with MB-5\log h < -21.0. We note that biasing is derived from the galaxy clustering relative to a model for the mass fluctuations. We investigate the quality of the DES photometric redshifts and find that the outlier fraction can be reduced using a comparison between template fitting and neural network, or using a random forest algorithm.

astro-ph.CO↗

arXiv2015

Eight Ultra-faint Galaxy Candidates Discovered in Year Two of the Dark Energy Survey

We report the discovery of eight new ultra-faint dwarf galaxy candidates in the second year of optical imaging data from the Dark Energy Survey (DES). Six of these candidates are detected at high confidence, while two lower-confidence candidates are identified in regions of non-uniform survey coverage. The new stellar systems are found by three independent automated search techniques and are identified as overdensities of stars, consistent with the isochrone and luminosity function of an old and metal-poor simple stellar population. The new systems are faint (Mv > -4.7 mag) and span a range of physical sizes (17 pc < $r_{1/2}$ < 181 pc) and heliocentric distances (25 kpc < D < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultra-faint dwarf galaxies (μ< 27.5 mag arcsec$^{-2}$). Roughly half of the DES candidates are more distant, less luminous, and/or have lower surface brightnesses than previously known Milky Way satellite galaxies. Most of the candidates are found in the southern part of the DES footprint close to the Magellanic Clouds. We find that the DES data alone exclude (p < 0.001) a spatially isotropic distribution of Milky Way satellites and that the observed distribution can be well, though not uniquely, described by an association between several of the DES satellites and the Magellanic system. Our model predicts that the full sky may hold ~100 ultra-faint galaxies with physical properties comparable to the DES satellites and that 20-30% of these would be spatially associated with the Magellanic Clouds.

astro-ph.GA↗

arXiv2015

The Difference Imaging Pipeline for the Transient Search in the Dark Energy Survey

We describe the difference imaging pipeline (DiffImg) used to detect transients in deep images from the Dark Energy Survey Supernova program (DES-SN) in its first observing season from Aug 2013 through Feb 2014. DES-SN is a search for transients in which ten 3-deg^2 fields are repeatedly observed in the g,r,i,z passbands with a cadence of about 1 week. The observing strategy has been optimized to measure high-quality light curves and redshifts for thousands of Type Ia supernova (SN Ia) with the goal of measuring dark energy parameters. The essential DiffImg functions are to align each search image to a deep reference image, do a pixel-by-pixel subtraction, and then examine the subtracted image for significant positive detections of point-source objects. The vast majority of detections are subtraction artifacts, but after selection requirements and image filtering with an automated scanning program, there are 130 detections per deg^2 per observation in each band, of which only 25% are artifacts. Of the 7500 transients discovered by DES-SN in its first observing season, each requiring a detection on at least 2 separate nights, Monte Carlo simulations predict that 27% are expected to be supernova. Another 30% of the transients are artifacts, and most of the remaining transients are AGN and variable stars. Fake SNe Ia are overlaid onto the images to rigorously evaluate detection efficiencies, and to understand the DiffImg performance. The DiffImg efficiency measured with fake SNe agrees well with expectations from a Monte Carlo simulation that uses analytical calculations of the fluxes and their uncertainties. In our 8 "shallow" fields with single-epoch 50% completeness depth 23.5, the SN Ia efficiency falls to 1/2 at redshift z 0.7, in our 2 "deep" fields with mag-depth 24.5, the efficiency falls to 1/2 at z 1.1.

astro-ph.IM↗

arXiv2015

Joint Analysis of Galaxy-Galaxy Lensing and Galaxy Clustering: Methodology and Forecasts for DES

The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. This analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we study how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. We conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9\%/4.8\% with its first-year data that covered over 1000 square degrees, and to 3.9\%/2.3\% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.

astro-ph.CO↗

arXiv2015

Digging deeper into the Southern skies: a compact Milky-Way companion discovered in first-year Dark Energy Survey data

The Dark Energy Survey (DES) is a 5000 sq. degree survey in the southern hemisphere, which is rapidly reducing the existing north-south asymmetry in the census of MW satellites and other stellar substructure. We use the first-year DES data down to previously unprobed photometric depths to search for stellar systems in the Galactic halo, therefore complementing the previous analysis of the same data carried out by our group earlier this year. Our search is based on a matched filter algorithm that produces stellar density maps consistent with stellar population models of various ages, metallicities, and distances over the survey area. The most conspicuous density peaks in these maps have been identified automatically and ranked according to their significance and recurrence for different input models. We report the discovery of one additional stellar system besides those previously found by several authors using the same first-year DES data. The object is compact, and consistent with being dominated by an old and metal-poor population. DES J0034-4902 is found at high significance and appears in the DES images as a compact concentration of faint blue point sources at ~ 87 {kpc}. Its half-light radius of r_h = 9.88 +/- 4.31 {pc} and total luminosity of M_V ~ -3.05_{-0.42}^{+0.69} are consistent with it being a low mass halo cluster. It is also found to have a very elongated shape. In addition, our deeper probe of DES 1st year data confirms the recently reported satellite galaxy candidate Horologium II as a significant stellar overdensity. We also infer its structural properties and compare them to those reported in the literature.

astro-ph.GA↗

arXiv2015

redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the color-cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photozs are very nearly as accurate as the best machine-learning based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalog sampling the redshift range $z\in[0.2,0.8]$. Our fiducial sample has a comoving space density of $10^{-3}\ (h^{-1} Mpc)^{-3}$, and a median photoz bias ($z_{spec}-z_{photo}$) and scatter $(σ_z/(1+z))$ of 0.005 and 0.017 respectively. The corresponding $5σ$ outlier fraction is 1.4%. We also test our algorithm with Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8) and Stripe 82 data, and discuss how spectroscopic training can be used to control photoz biases at the 0.1% level.

astro-ph.IM↗

arXiv2015

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.

astro-ph.CO↗

arXiv2015

Observation of Two New L4 Neptune Trojans in the Dark Energy Survey Supernova Fields

We report the discovery of the eighth and ninth known Trojans in stable orbits around Neptune's leading Lagrange point, L4. The objects 2014 QO$_{441}$ and 2014 QP$_{441}$ were detected in data obtained during the 2013-14 and 2014-15 observing seasons by the Dark Energy Survey, using the Dark Energy Camera (DECam) on the 4-meter Blanco telescope at Cerro Tololo Inter-American Observatory. Both are in high-inclination orbits (18.8$^{\circ}$ and 19.4$^{\circ}$ respectively). With an eccentricity of 0.104, 2014 QO$_{441}$ has the most eccentric orbit of the eleven known stable Neptune Trojans. Here we describe the search procedure and investigate the objects' long-term dynamical stability and physical properties.

astro-ph.EP↗

arXiv2015

OzDES multi-fibre spectroscopy for the Dark Energy Survey: first-year operation and results

OzDES is a five-year, 100-night, spectroscopic survey on the Anglo-Australian Telescope, whose primary aim is to measure redshifts of approximately 2,500 Type Ia supernovae host galaxies over the redshift range 0.1 < z < 1.2, and derive reverberation-mapped black hole masses for approximately 500 active galactic nuclei and quasars over 0.3 < z < 4.5. This treasure trove of data forms a major part of the spectroscopic follow-up for the Dark Energy Survey for which we are also targeting cluster galaxies, radio galaxies, strong lenses, and unidentified transients, as well as measuring luminous red galaxies and emission line galaxies to help calibrate photometric redshifts. Here we present an overview of the OzDES program and our first-year results. Between Dec 2012 and Dec 2013, we observed over 10,000 objects and measured more than 6,000 redshifts. Our strategy of retargeting faint objects across many observing runs has allowed us to measure redshifts for galaxies as faint as m_r=25 mag. We outline our target selection and observing strategy, quantify the redshift success rate for different types of targets, and discuss the implications for our main science goals. Finally, we highlight a few interesting objects as examples of the fortuitous yet not totally unexpected discoveries that can come from such a large spectroscopic survey.

astro-ph.GA↗