Data re-sampling methods such as delete-one jackknife, bootstrap or the sub-sample covariance are common tools for estimating the covariance of large-scale structure probes. We investigate different ...implementations of these methods in the context of cosmic shear two-point statistics. Using lognormal simulations of the convergence field and the corresponding shear field we generate mock catalogues of a known and realistic covariance. For a survey of
${\sim } 5000 \deg ^2$
we find that jackknife, if implemented by deleting sub-volumes of galaxies, provides the most reliable covariance estimates. Bootstrap, in the common implementation of drawing sub-volumes of galaxies, strongly overestimates the statistical uncertainties. In a forecast for the complete 5-yr Dark Energy Survey, we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the Ωm–σ8 plane as measured with internally estimated covariance matrices is on average ≳85 per cent of the volume derived from the true covariance matrix. The uncertainty on the parameter combination
$\Sigma _8 \sim \sigma _8 \Omega _{\rm m}^{0.5}$
derived from internally estimated covariances is ∼90 per cent of the true uncertainty.
ABSTRACT
We perform a cross validation of the cluster catalogue selected by the red-sequence Matched-filter Probabilistic Percolation algorithm (redMaPPer) in Dark Energy Survey year 1 (DES-Y1) data ...by matching it with the Sunyaev–Zel’dovich effect (SZE) selected cluster catalogue from the South Pole Telescope SPT-SZ survey. Of the 1005 redMaPPer selected clusters with measured richness $\hat{\lambda }\gt 40$ in the joint footprint, 207 are confirmed by SPT-SZ. Using the mass information from the SZE signal, we calibrate the richness–mass relation using a Bayesian cluster population model. We find a mass trend λ ∝ MB consistent with a linear relation (B ∼ 1), no significant redshift evolution and an intrinsic scatter in richness of σλ = 0.22 ± 0.06. By considering two error models, we explore the impact of projection effects on the richness–mass modelling, confirming that such effects are not detectable at the current level of systematic uncertainties. At low richness SPT-SZ confirms fewer redMaPPer clusters than expected. We interpret this richness dependent deficit in confirmed systems as due to the increased presence at low richness of low-mass objects not correctly accounted for by our richness-mass scatter model, which we call contaminants. At a richness $\hat{\lambda }=40$, this population makes up ${\gt}12{{\ \rm per\ cent}}$ (97.5 percentile) of the total population. Extrapolating this to a measured richness $\hat{\lambda }=20$ yields ${\gt}22{{\ \rm per\ cent}}$ (97.5 percentile). With these contamination fractions, the predicted redMaPPer number counts in different plausible cosmologies are compatible with the measured abundance. The presence of such a population is also a plausible explanation for the different mass trends (B ∼ 0.75) obtained from mass calibration using purely optically selected clusters. The mean mass from stacked weak lensing (WL) measurements suggests that these low-mass contaminants are galaxy groups with masses ∼3–5 × 1013 M⊙ which are beyond the sensitivity of current SZE and X-ray surveys but a natural target for SPT-3G and eROSITA.
Abstract
We present a detailed abundance analysis of the three brightest member stars at the top of the giant branch of the ultrafaint dwarf (UFD) galaxy Grus II. All stars exhibit a higher than ...expected Mg/Ca ratio compared to metal-poor stars in other UFD galaxies and in the Milky Way (MW) halo. Nucleosynthesis in high-mass (
20
M
⊙
) core-collapse supernovae has been shown to create this signature. The abundances of this small sample (three) stars suggests the chemical enrichment of Grus II could have occurred through substantial high-mass stellar evolution, and is consistent with the framework of a top-heavy initial mass function. However, with only three stars it cannot be ruled out that the abundance pattern is the result of a stochastic chemical enrichment at early times in the galaxy. The most metal-rich of the three stars also possesses a small enhancement in rapid neutron-capture (
r
-process) elements. The abundance pattern of the
r
-process elements in this star matches the scaled
r
-process pattern of the solar system and
r
-process enhanced stars in other dwarf galaxies and in the MW halo, hinting at a common origin for these elements across a range of environments. All current proposed astrophysical sites of
r
-process element production are associated with high-mass stars, thus the possible top-heavy initial mass function of Grus II would increase the likelihood of any of these events occurring. The time delay between the
α
and
r
-process element enrichment of the galaxy favors a neutron star merger as the origin of the
r
-process elements in Grus II.
Abstract
We present a measurement of galaxy–galaxy lensing around a magnitude-limited (iAB < 22.5) sample of galaxies from the dark energy survey science verification (DES-SV) data. We split these ...lenses into three photometric-redshift bins from 0.2 to 0.8, and determine the product of the galaxy bias b and cross-correlation coefficient between the galaxy and dark matter overdensity fields r in each bin, using scales above 4 h−1 Mpc comoving, where we find the linear bias model to be valid given our current uncertainties. We compare our galaxy bias results from galaxy–galaxy lensing with those obtained from galaxy clustering and CMB lensing for the same sample of galaxies, and find our measurements to be in good agreement with those in Crocce et al., while, in the lowest redshift bin (z ∼ 0.3), they show some tension with the findings in Giannantonio et al. We measure b · r to be 0.87 ± 0.11, 1.12 ± 0.16 and 1.24 ± 0.23, respectively, for the three redshift bins of width Δz = 0.2 in the range 0.2 < z < 0.8, defined with the photometric-redshift algorithm bpz. Using a different code to split the lens sample, tpz, leads to changes in the measured biases at the 10–20 per cent level, but it does not alter the main conclusion of this work: when comparing with Crocce et al. we do not find strong evidence for a cross-correlation parameter significantly below one in this galaxy sample, except possibly at the lowest redshift bin (z ∼ 0.3), where we find r = 0.71 ± 0.11 when using tpz, and 0.83 ± 0.12 with bpz.
The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large-scale structure. Anticipating a near future application of this ...analysis to Dark Energy Survey (DES) measurements of galaxy positions and shapes, we develop a practical approach to modeling the assumptions and systematic effects affecting the joint analysis of small-scale galaxy-galaxy lensing 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 being subdominant. 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 cover 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.
Abstract
We describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission ...eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF–redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. We find a well-defined X-ray luminosity–λMCMF relation with an intrinsic scatter of δln (λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF–mass relation.
ABSTRACT We describe the operation and performance of 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 2013 August through 2014 February. DES-SN is a search for transients in which ten 3 deg2 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 supernovae (SNe 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 deg2 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 two separate nights, Monte Carlo (MC) simulations predict that 27% are expected to be SNe Ia or core-collapse SNe. Another ∼30% of the transients are artifacts in which a small number of observations satisfy the selection criteria for a single-epoch detection. Spectroscopic analysis shows that most of the remaining transients are AGNs 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 MC 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. A remaining performance issue is that the measured fluxes have additional scatter (beyond Poisson fluctuations) that increases with the host galaxy surface brightness at the transient location. This bright-galaxy issue has minimal impact on the SNe Ia program, but it may lower the efficiency for finding fainter transients on bright galaxies.
Abstract
We perform a joint analysis of intrinsic alignments and cosmology using tomographic weak lensing, galaxy clustering, and galaxy–galaxy lensing measurements from Year 1 (Y1) of the Dark ...Energy Survey. We define early- and late-type subsamples, which are found to pass a series of systematics tests, including for spurious photometric redshift error and point spread function correlations. We analyse these split data alongside the fiducial mixed Y1 sample using a range of intrinsic alignment models. In a fiducial non-linear alignment model analysis, assuming a flat Λ cold dark matter cosmology, we find a significant difference in intrinsic alignment amplitude, with early-type galaxies favouring $A_\mathrm{IA} = 2.38^{+0.32}_{-0.31}$ and late-type galaxies consistent with no intrinsic alignments at $0.05^{+0.10}_{-0.09}$. The analysis is repeated using a number of extended model spaces, including a physically motivated model that includes both tidal torquing and tidal alignment mechanisms. In multiprobe likelihood chains in which cosmology, intrinsic alignments in both galaxy samples and all other relevant systematics are varied simultaneously, we find the tidal alignment and tidal torquing parts of the intrinsic alignment signal have amplitudes $A_1 = 2.66 ^{+0.67}_{-0.66}$, $A_2=-2.94^{+1.94}_{-1.83}$, respectively, for early-type galaxies and $A_1 = 0.62 ^{+0.41}_{-0.41}$, $A_2 = -2.26^{+1.30}_{-1.16}$ for late-type galaxies. In the full (mixed) Y1 sample the best constraints are $A_1 = 0.70 ^{+0.41}_{-0.38}$, $A_2 = -1.36 ^{+1.08}_{-1.41}$. For all galaxy splits and IA models considered, we report cosmological parameter constraints consistent with the results of the main DES Y1 cosmic shear and multiprobe cosmology papers.
ABSTRACT 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 ) and span a range of physical sizes (17 < r1/2 < 181 ) and heliocentric distances (25 kpc < D < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultra-faint dwarf galaxies ( 27.5 −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 < 10−3) 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.
Abstract
We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source ...galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering versus photo-zs. The systematic uncertainty in the mean redshift bias of the source galaxy sample is Δz ≲ 0.02, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.
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