ABSTRACT
We present angular diameter distance measurements obtained by locating the baryon acoustic oscillations (BAO) scale in the distribution of galaxies selected from the first year of Dark ...Energy Survey data. We consider a sample of over 1.3 million galaxies distributed over a footprint of 1336 deg2 with 0.6 < $z$photo < 1 and a typical redshift uncertainty of 0.03(1 + $z$). This sample was selected, as fully described in a companion paper, using a colour/magnitude selection that optimizes trade-offs between number density and redshift uncertainty. We investigate the BAO signal in the projected clustering using three conventions, the angular separation, the comoving transverse separation, and spherical harmonics. Further, we compare results obtained from template-based and machine-learning photometric redshift determinations. We use 1800 simulations that approximate our sample in order to produce covariance matrices and allow us to validate our distance scale measurement methodology. We measure the angular diameter distance, DA, at the effective redshift of our sample divided by the true physical scale of the BAO feature, rd. We obtain close to a 4 per cent distance measurement of DA($z$eff = 0.81)/rd = 10.75 ± 0.43. These results are consistent with the flat Λ cold dark matter concordance cosmological model supported by numerous other recent experimental results.
We report the results of a systematic search for ultra-faint Milky Way satellite galaxies using data from the Dark Energy Survey (DES) and Pan-STARRS1 (PS1). Together, DES and PS1 provide multi-band ...photometry in optical/near-infrared wavelengths over ∼80% of the sky. Our search for satellite galaxies targets ∼25,000 deg2 of the high-Galactic-latitude sky reaching a 10 point-source depth of 22.5 mag in the g and r bands. While satellite galaxy searches have been performed independently on DES and PS1 before, this is the first time that a self-consistent search is performed across both data sets. We do not detect any new high-significance satellite galaxy candidates, recovering the majority of satellites previously detected in surveys of comparable depth. We characterize the sensitivity of our search using a large set of simulated satellites injected into the survey data. We use these simulations to derive both analytic and machine-learning models that accurately predict the detectability of Milky Way satellites as a function of their distance, size, luminosity, and location on the sky. To demonstrate the utility of this observational selection function, we calculate the luminosity function of Milky Way satellite galaxies, assuming that the known population of satellite galaxies is representative of the underlying distribution. We provide access to our observational selection function to facilitate comparisons with cosmological models of galaxy formation and evolution.
ABSTRACT
We present an improved measurement of the Hubble constant (H0) using the ‘inverse distance ladder’ method, which adds the information from 207 Type Ia supernovae (SNe Ia) from the Dark ...Energy Survey (DES) at redshift 0.018 < z < 0.85 to existing distance measurements of 122 low-redshift (z < 0.07) SNe Ia (Low-z) and measurements of Baryon Acoustic Oscillations (BAOs). Whereas traditional measurements of H0 with SNe Ia use a distance ladder of parallax and Cepheid variable stars, the inverse distance ladder relies on absolute distance measurements from the BAOs to calibrate the intrinsic magnitude of the SNe Ia. We find H0 = 67.8 ± 1.3 km s−1 Mpc−1 (statistical and systematic uncertainties, 68 per cent confidence). Our measurement makes minimal assumptions about the underlying cosmological model, and our analysis was blinded to reduce confirmation bias. We examine possible systematic uncertainties and all are below the statistical uncertainties. Our H0 value is consistent with estimates derived from the Cosmic Microwave Background assuming a ΛCDM universe.
We present the first results of a survey for high-redshift, z ≥ 6, quasars using izY multicolour photometric observations from the Dark Energy Survey (DES). Here we report the discovery and ...spectroscopic confirmation of the z
AB, Y
AB = 20.2, 20.2 (M
1450 = −26.5) quasar DES J0454−4448 with a redshift of z = 6.09±0.02 based on the onset of the Ly α forest and an H i near zone size of 4.1
$_{-1.2}^{+1.1}$
proper Mpc. The quasar was selected as an i-band drop out with i−z = 2.46 and z
AB < 21.5 from an area of ∼300 deg2. It is the brightest of our 43 candidates and was identified for spectroscopic follow-up solely based on the DES i−z and z−Y colours. The quasar is detected by WISE and has W1AB = 19.68. The discovery of one spectroscopically confirmed quasar with 5.7 < z < 6.5 and z
AB ≤ 20.2 is consistent with recent determinations of the luminosity function at z ∼ 6. DES when completed will have imaged ∼5000 deg2 to Y
AB = 23.0 (5σ point source) and we expect to discover 50–100 new quasars with z > 6 including 3–10 with z > 7 dramatically increasing the numbers of quasars currently known that are suitable for detailed studies.
ABSTRACT
We demonstrate that highly accurate joint redshift–stellar mass probability distribution functions (PDFs) can be obtained using the Random Forest (RF) machine learning (ML) algorithm, even ...with few photometric bands available. As an example, we use the Dark Energy Survey (DES), combined with the COSMOS2015 catalogue for redshifts and stellar masses. We build two ML models: one containing deep photometry in the griz bands, and the second reflecting the photometric scatter present in the main DES survey, with carefully constructed representative training data in each case. We validate our joint PDFs for 10 699 test galaxies by utilizing the copula probability integral transform and the Kendall distribution function, and their univariate counterparts to validate the marginals. Benchmarked against a basic set-up of the template-fitting code bagpipes, our ML-based method outperforms template fitting on all of our predefined performance metrics. In addition to accuracy, the RF is extremely fast, able to compute joint PDFs for a million galaxies in just under 6 min with consumer computer hardware. Such speed enables PDFs to be derived in real time within analysis codes, solving potential storage issues. As part of this work we have developed galpro1, a highly intuitive and efficient python package to rapidly generate multivariate PDFs on-the-fly. galpro is documented and available for researchers to use in their cosmology and galaxy evolution studies.
ABSTRACT
Beyond ΛCDM, physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analysed assuming ΛCDM. We present an application of internal consistency ...tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of ΛCDM. We find that the DES Y1 data have an acceptable goodness of fit to ΛCDM, with a probability of finding a worse fit by random chance of p = 0.046. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5 per cent) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the p-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.
Here, we present two galaxy shape catalogues from the Dark Energy Survey Year 1 data set, covering 1500 square degrees with a median redshift of 0:59. The catalogues cover two main fields: Stripe 82, ...and an area overlapping the South Pole Telescope survey region. We also describe our data analysis process and in particular our shape measurement using two independent shear measurement pipelines, METACALIBRATION and IM3SHAPE. The METACALIBRATION catalogue uses a Gaussian model with an innovative internal calibration scheme, and was applied to riz bands, yielding 34.8M objects. The IM3SHAPE catalogue uses a maximum-likelihood bulge/disc model calibrated using simulations, and was applied to r-band data, yielding 21.9M objects. Both catalogues pass a suite of null tests that demonstrate their fitness for use in weak lensing science. Finally, we estimated the 1 uncertainties in multiplicative shear calibration to be 0.013 and 0.025 for the METACALIBRATION and IM3SHAPE catalogues, respectively.
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.
The Dark Energy Survey Image Processing Pipeline Morganson, E.; Gruendl, R. A.; Menanteau, F. ...
Publications of the Astronomical Society of the Pacific,
07/2018, Letnik:
130, Številka:
989
Journal Article
Recenzirano
Odprti dostop
The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five ...optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.
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