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R. Miquel

Publications and source records attributed to R. Miquel.

At least 649 records · Page 36Linked to original sources

Redshift distributions of galaxies in the DES Science Verification shear catalogue and implications for weak lensing

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 analysed. 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-zs. From the galaxies in the DES SV shear catalogue, which have mean redshift $0.72\pm0.01$ over the range $0.3<z<1.3$, we construct three tomographic bins with means of $z=\{0.45, 0.67, 1.00\}$. These bins each have systematic uncertainties $δz \lesssim 0.05$ in the mean of the fiducial SkyNet photo-z $n(z)$. 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 $σ_8$ of approx. 3%. This shift is within the one sigma statistical errors on $σ_8$ for the DES SV shear catalog. We further study the potential impact of systematic differences on the critical surface density, $Σ_{\mathrm{crit}}$, 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 $n(z)$ 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.

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Wide-Field Lensing Mass Maps from DES Science Verification Data: Methodology and Detailed Analysis

Weak gravitational lensing allows one to reconstruct the spatial distribution of the projected mass density across the sky. These "mass maps" provide a powerful tool for studying cosmology as they probe both luminous and dark matter. In this paper, we present a weak lensing mass map reconstructed from shear measurements in a 139 sq. deg area from the Dark Energy Survey (DES) Science Verification (SV) data. We compare the distribution of mass with that of the foreground distribution of galaxies and clusters. The overdensities in the reconstructed map correlate well with the distribution of optically detected clusters. We demonstrate that candidate superclusters and voids along the line of sight can be identified, exploiting the tight scatter of the cluster photometric redshifts. We cross-correlate the mass map with a foreground magnitude-limited galaxy sample from the same data. Our measurement gives results consistent with mock catalogs from N-body simulations that include the primary sources of statistical uncertainties in the galaxy, lensing, and photo-z catalogs. The statistical significance of the cross-correlation is at the 6.8-sigma level with 20 arcminute smoothing. A major goal of this study is to investigate systematic effects arising from a variety of sources, including PSF and photo-z uncertainties. We make maps derived from twenty variables that may characterize systematics and find the principal components. We find that the contribution of systematics to the lensing mass maps is generally within measurement uncertainties. In this work, we analyze less than 3% of the final area that will be mapped by the DES; the tools and analysis techniques developed in this paper can be applied to forthcoming larger datasets from the survey.

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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.

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Wide-Field Lensing Mass Maps from DES Science Verification Data

We present a mass map reconstructed from weak gravitational lensing shear measurements over 139 sq. deg from the Dark Energy Survey (DES) Science Verification data. The mass map probes both luminous and dark matter, thus providing a tool for studying cosmology. We find good agreement between the mass map and the distribution of massive galaxy clusters identified using a red-sequence cluster finder. Potential candidates for super-clusters and voids are identified using these maps. We measure the cross-correlation between the mass map and a magnitude-limited foreground galaxy sample and find a detection at the 5-7 sigma level on a large range of scales. These measurements are consistent with simulated galaxy catalogs based on LCDM N-body simulations, suggesting low systematics uncertainties in the map. We summarize our key findings in this letter; the detailed methodology and tests for systematics are presented in a companion paper.

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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.

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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.

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Constraints on the Richness-Mass Relation and the Optical-SZE Positional Offset Distribution for SZE-Selected Clusters

We cross-match galaxy cluster candidates selected via their Sunyaev-Zel'dovich effect (SZE) signatures in 129.1 deg$^2$ of the South Pole Telescope 2500d SPT-SZ survey with optically identified clusters selected from the Dark Energy Survey (DES) science verification data. We identify 25 clusters between $0.1\lesssim z\lesssim 0.8$ in the union of the SPT-SZ and redMaPPer (RM) samples. RM is an optical cluster finding algorithm that also returns a richness estimate for each cluster. We model the richness $λ$-mass relation with the following function $\langle\lnλ|M_{500}\rangle\propto B_λ\ln M_{500}+C_λ\ln E(z)$ and use SPT-SZ cluster masses and RM richnesses $λ$ to constrain the parameters. We find $B_λ= 1.14^{+0.21}_{-0.18}$ and $C_λ=0.73^{+0.77}_{-0.75}$. The associated scatter in mass at fixed richness is $σ_{\ln M|λ} = 0.18^{+0.08}_{-0.05}$ at a characteristic richness $λ=70$. We demonstrate that our model provides an adequate description of the matched sample, showing that the fraction of SPT-SZ selected clusters with RM counterparts is consistent with expectations and that the fraction of RM selected clusters with SPT-SZ counterparts is in mild tension with expectation. We model the optical-SZE cluster positional offset distribution with the sum of two Gaussians, showing that it is consistent with a dominant, centrally peaked population and a sub-dominant population characterized by larger offsets. We also cross-match the RM catalog with SPT-SZ candidates below the official catalog threshold significance $ξ=4.5$, using the RM catalog to provide optical confirmation and redshifts for additional low-$ξ$ SPT-SZ candidates.In this way, we identify 15 additional clusters with $ξ\in [4,4.5]$ over the redshift regime explored by RM in the overlapping region between DES science verification data and the SPT-SZ survey.

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Stellar Kinematics and Metallicities in the Ultra-Faint Dwarf Galaxy Reticulum II

We present Magellan/M2FS, VLT/GIRAFFE, and Gemini South/GMOS spectroscopy of the newly discovered Milky Way satellite Reticulum II. Based on the spectra of 25 Ret II member stars selected from Dark Energy Survey imaging, we measure a mean heliocentric velocity of 62.8 +/- 0.5 km/s and a velocity dispersion of 3.3 +/- 0.7 km/s. The mass-to-light ratio of Ret II within its half-light radius is 470 +/- 210 Msun/Lsun, demonstrating that it is a strongly dark matter-dominated system. Despite its spatial proximity to the Magellanic Clouds, the radial velocity of Ret II differs from that of the LMC and SMC by 199 and 83 km/s, respectively, suggesting that it is not gravitationally bound to the Magellanic system. The likely member stars of Ret II span 1.3 dex in metallicity, with a dispersion of 0.28 +/- 0.09 dex, and we identify several extremely metal-poor stars with [Fe/H] < -3. In combination with its luminosity, size, and ellipticity, these results confirm that Ret II is an ultra-faint dwarf galaxy. With a mean metallicity of [Fe/H] = -2.65 +/- 0.07, Ret II matches Segue~1 as the most metal-poor galaxy known. Although Ret II is the third-closest dwarf galaxy to the Milky Way, the line-of-sight integral of the dark matter density squared is log J = 18.8 +/- 0.6 Gev^2/cm^5 within 0.2 degrees, indicating that the predicted gamma-ray flux from dark matter annihilation in Ret II is lower than that of several other dwarf galaxies.

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Eight New Milky Way Companions Discovered in First-Year Dark Energy Survey Data

We report the discovery of eight new Milky Way companions in ~1,800 deg^2 of optical imaging data collected during the first year of the Dark Energy Survey (DES). Each system is identified as a statistically significant over-density of individual stars consistent with the expected isochrone and luminosity function of an old and metal-poor stellar population. The objects span a wide range of absolute magnitudes (M_V from -2.2 mag to -7.4 mag), physical sizes (10 pc to 170 pc), and heliocentric distances (30 kpc to 330 kpc). Based on the low surface brightnesses, large physical sizes, and/or large Galactocentric distances of these objects, several are likely to be new ultra-faint satellite galaxies of the Milky Way and/or Magellanic Clouds. We introduce a likelihood-based algorithm to search for and characterize stellar over-densities, as well as identify stars with high satellite membership probabilities. We also present completeness estimates for detecting ultra-faint galaxies of varying luminosities, sizes, and heliocentric distances in the first-year DES data.

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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.

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The Dark Energy Camera

The Dark Energy Camera is a new imager with a 2.2-degree diameter field of view mounted at the prime focus of the Victor M. Blanco 4-meter telescope on Cerro Tololo near La Serena, Chile. The camera was designed and constructed by the Dark Energy Survey Collaboration, and meets or exceeds the stringent requirements designed for the wide-field and supernova surveys for which the collaboration uses it. The camera consists of a five element optical corrector, seven filters, a shutter with a 60 cm aperture, and a CCD focal plane of 250 micron thick fully-depleted CCDs cooled inside a vacuum Dewar. The 570 Mpixel focal plane comprises 62 2kx4k CCDs for imaging and 12 2kx2k CCDs for guiding and focus. The CCDs have 15 microns x15 microns pixels with a plate scale of 0.263 arc sec per pixel. A hexapod system provides state-of-the-art focus and alignment capability. The camera is read out in 20 seconds with 6-9 electrons readout noise. This paper provides a technical description of the camera's engineering, construction, installation, and current status.

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Mass and galaxy distributions of four massive galaxy clusters from Dark Energy Survey Science Verification data

We measure the weak-lensing masses and galaxy distributions of four massive galaxy clusters observed during the Science Verification phase of the Dark Energy Survey. This pathfinder study is meant to 1) validate the DECam imager for the task of measuring weak-lensing shapes, and 2) utilize DECam's large field of view to map out the clusters and their environments over 90 arcmin. We conduct a series of rigorous tests on astrometry, photometry, image quality, PSF modeling, and shear measurement accuracy to single out flaws in the data and also to identify the optimal data processing steps and parameters. We find Science Verification data from DECam to be suitable for the lensing analysis described in this paper. The PSF is generally well-behaved, but the modeling is rendered difficult by a flux-dependent PSF width and ellipticity. We employ photometric redshifts to distinguish between foreground and background galaxies, and a red-sequence cluster finder to provide cluster richness estimates and cluster-galaxy distributions. By fitting NFW profiles to the clusters in this study, we determine weak-lensing masses that are in agreement with previous work. For Abell 3261, we provide the first estimates of redshift, weak-lensing mass, and richness. In addition, the cluster-galaxy distributions indicate the presence of filamentary structures attached to 1E 0657-56 and RXC J2248.7-4431, stretching out as far as 1 degree (approximately 20 Mpc), showcasing the potential of DECam and DES for detailed studies of degree-scale features on the sky.

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DES13S2cmm: The First Superluminous Supernova from the Dark Energy Survey

We present DES13S2cmm, the first spectroscopically-confirmed superluminous supernova (SLSN) from the Dark Energy Survey (DES). We briefly discuss the data and search algorithm used to find this event in the first year of DES operations, and outline the spectroscopic data obtained from the European Southern Observatory (ESO) Very Large Telescope to confirm its redshift (z = 0.663 +/- 0.001 based on the host-galaxy emission lines) and likely spectral type (type I). Using this redshift, we find M_U_peak = -21.05 +0.10 -0.09 for the peak, rest-frame U-band absolute magnitude, and find DES13S2cmm to be located in a faint, low metallicity (sub-solar), low stellar-mass host galaxy (log(M/M_sun) = 9.3 +/- 0.3); consistent with what is seen for other SLSNe-I. We compare the bolometric light curve of DES13S2cmm to fourteen similarly well-observed SLSNe-I in the literature and find it possesses one of the slowest declining tails (beyond +30 days rest frame past peak), and is the faintest at peak. Moreover, we find the bolometric light curves of all SLSNe-I studied herein possess a dispersion of only 0.2-0.3 magnitudes between +25 and +30 days after peak (rest frame) depending on redshift range studied; this could be important for 'standardising' such supernovae, as is done with the more common type Ia. We fit the bolometric light curve of DES13S2cmm with two competing models for SLSNe-I - the radioactive decay of 56Ni, and a magnetar - and find that while the magnetar is formally a better fit, neither model provides a compelling match to the data. Although we are unable to conclusively differentiate between these two physical models for this particular SLSN-I, further DES observations of more SLSNe-I should break this degeneracy, especially if the light curves of SLSNe-I can be observed beyond 100 days in the rest frame of the supernova.

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Combining Dark Energy Survey Science Verification Data with Near Infrared Data from the ESO VISTA Hemisphere Survey

We present the combination of optical data from the Science Verification phase of the Dark Energy Survey (DES) with near infrared data from the ESO VISTA Hemisphere Survey (VHS). The deep optical detections from DES are used to extract fluxes and associated errors from the shallower VHS data. Joint 7-band ($grizYJK$) photometric catalogues are produced in a single 3 sq-deg DECam field centred at 02h26m$-$04d36m where the availability of ancillary multi-wavelength photometry and spectroscopy allows us to test the data quality. Dual photometry increases the number of DES galaxies with measured VHS fluxes by a factor of $\sim$4.5 relative to a simple catalogue level matching and results in a $\sim$1.5 mag increase in the 80\% completeness limit of the NIR data. Almost 70\% of DES sources have useful NIR flux measurements in this initial catalogue. Photometric redshifts are estimated for a subset of galaxies with spectroscopic redshifts and initial results, although currently limited by small number statistics, indicate that the VHS data can help reduce the photometric redshift scatter at both $z<0.5$ and $z>1$. We present example DES+VHS colour selection criteria for high redshift Luminous Red Galaxies (LRGs) at $z\sim0.7$ as well as luminous quasars. Using spectroscopic observations in this field we show that the additional VHS fluxes enable a cleaner selection of both populations with $<$10\% contamination from galactic stars in the case of spectroscopically confirmed quasars and $<0.5\%$ contamination from galactic stars in the case of spectroscopically confirmed LRGs. The combined DES+VHS dataset, which will eventually cover almost 5000 sq-deg, will therefore enable a range of new science and be ideally suited for target selection for future wide-field spectroscopic surveys.

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Photometric redshift analysis in the Dark Energy Survey Science Verification data

We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification (SV) period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq.~deg.~at the nominal depth of the survey. We assess the photometric redshift performance using about 15000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-$z$'s are obtained and studied using most of the existing photo-$z$ codes. A weighting method in a multi-dimensional color-magnitude space is applied to the spectroscopic sample in order to evaluate the photo-$z$ performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. Empirical photo-$z$ methods using, for instance, Artificial Neural Networks or Random Forests, yield the best performance in the tests, achieving core photo-$z$ resolutions $σ_{68} \sim 0.08$. Moreover, the results from most of the codes, including template fitting methods, comfortably meet the DES requirements on photo-$z$ performance, therefore, providing an excellent precedent for future DES data sets.

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Spectroscopic Needs for Imaging Dark Energy Experiments: Photometric Redshift Training and Calibration

Large sets of objects with spectroscopic redshift measurements will be needed for imaging dark energy experiments to achieve their full potential, serving two goals:_training_, i.e., the use of objects with known redshift to develop and optimize photometric redshift algorithms; and_calibration_, i.e., the characterization of moments of redshift (or photo-z error) distributions. Better training makes cosmological constraints from a given experiment stronger, while highly-accurate calibration is needed for photo-z systematics not to dominate errors. In this white paper, we investigate the required scope of spectroscopic datasets which can serve both these purposes for ongoing and next-generation dark energy experiments, as well as the time required to obtain such data with instruments available in the next decade. Large time allocations on kilo-object spectrographs will be necessary, ideally augmented by infrared spectroscopy from space. Alternatively, precision calibrations could be obtained by measuring cross-correlation statistics using samples of bright objects from a large baryon acoustic oscillation experiment such as DESI. We also summarize the additional work on photometric redshift methods needed to prepare for ongoing and future dark energy experiments.

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Cross-Correlation of spectroscopic and photometric galaxy surveys: cosmology from lensing and redshift distortions

Cosmological galaxy surveys aim at mapping the largest volumes to test models with techniques such as cluster abundance, cosmic shear correlations or baryon acoustic oscillations (BAO), which are designed to be independent of galaxy bias. Here we explore an alternative route to constrain cosmology: sampling more moderate volumes with the cross-correlation of photometric and spectroscopic surveys. We consider the angular galaxy-galaxy autocorrelation in narrow redshift bins and its combination with different probes of weak gravitational lensing (WL) and redshift space distortions (RSD). Including the cross-correlation of these surveys improves by factors of a few the constraints on both the dark energy equation of state w(z) and the cosmic growth history, parametrized by γ. The additional information comes from using many narrow redshift bins and from galaxy bias, which is measured both with WL probes and RSD, breaking degeneracies that are present when using each method separately. We show forecasts for a joint w(z) and γfigure of merit using linear scales over a deep (i<24) photometric survey and a brighter (i<22.5) spectroscopic or very accurate (0.3%) photometric redshift survey. Magnification or shear in the photometric sample produce FoM that are of the same order of magnitude of those of RSD or BAO over the spectroscopic sample. However, the cross-correlation of these probes over the same area yields a FoM that is up to a factor 100 times larger. Magnification alone, without shape measurements, can also be used for these cross-correlations and can produce better results than using shear alone. For a spectroscopic follow-up survey strategy, measuring the spectra of the foreground lenses to perform this cross-correlation provides 5 times better FoM than targeting the higher redshift tail of the galaxy distribution to study BAO over a 2.5 times larger volume.

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Cosmological and Astrophysical Neutrino Mass Measurements

Cosmological and astrophysical measurements provide powerful constraints on neutrino masses complementary to those from accelerators and reactors. Here we provide a guide to these different probes, for each explaining its physical basis, underlying assumptions, current and future reach.

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