scholarly journals Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology

2021 ◽  
Vol 254 (2) ◽  
pp. 24
Author(s):  
I. Sevilla-Noarbe ◽  
K. Bechtol ◽  
M. Carrasco Kind ◽  
A. Carnero Rosell ◽  
M. R. Becker ◽  
...  
Keyword(s):  
Dark Energy ◽  
Photometric Data ◽  
Data Set ◽  
Dark Energy Survey ◽  
Energy Survey

scholarly journals Dark Energy Survey Year 1 Results: The Photometric Data Set for Cosmology

2018 ◽  
Vol 235 (2) ◽  
pp. 33 ◽  
Author(s):  
A. Drlica-Wagner ◽  
I. Sevilla-Noarbe ◽  
E. S. Rykoff ◽  
R. A. Gruendl ◽  
B. Yanny ◽  
...  
Keyword(s):  
Dark Energy ◽  
Photometric Data ◽  
Data Set ◽  
Dark Energy Survey ◽  
Energy Survey

scholarly journals Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

2021 ◽  
Vol 503 (2) ◽  
pp. 2688-2705
Author(s):  
C Doux ◽  
E Baxter ◽  
P Lemos ◽  
C Chang ◽  
A Alarcon ◽  
...  
Keyword(s):  
Dark Energy ◽  
Internal Consistency ◽  
Goodness Of Fit ◽  
Small Scale ◽  
P Value ◽  
Posterior Predictive Distribution ◽  
Data Set ◽  
Dark Energy Survey ◽  
Data Vector ◽  
Energy Survey

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.

scholarly journals The mystery of photometric twins DES17X1boj and DES16E2bjy

2020 ◽  
Vol 494 (4) ◽  
pp. 5576-5589 ◽  
Author(s):  
M Pursiainen ◽  
C P Gutiérrez ◽  
P Wiseman ◽  
M Childress ◽  
M Smith ◽  
...  
Keyword(s):  
Dark Energy ◽  
Light Curve ◽  
Spiral Galaxy ◽  
High Velocity ◽  
Photometric Data ◽  
Light Curves ◽  
Curve Evolution ◽  
Physical Origin ◽  
Dark Energy Survey ◽  
Energy Survey

ABSTRACT We present an analysis of DES17X1boj and DES16E2bjy, two peculiar transients discovered by the Dark Energy Survey (DES). They exhibit nearly identical double-peaked light curves that reach very different maximum luminosities (Mr = −15.4 and −17.9, respectively). The light-curve evolution of these events is highly atypical and has not been reported before. The transients are found in different host environments: DES17X1boj was found near the nucleus of a spiral galaxy, while DES16E2bjy is located in the outskirts of a passive red galaxy. Early photometric data are well fitted with a blackbody and the resulting moderate photospheric expansion velocities (1800  km s−1 for DES17X1boj and 4800  km s−1 for DES16E2bjy) suggest an explosive or eruptive origin. Additionally, a feature identified as high-velocity Ca ii absorption ($v$ ≈ 9400 km s−1) in the near-peak spectrum of DES17X1boj may imply that it is a supernova. While similar light-curve evolution suggests a similar physical origin for these two transients, we are not able to identify or characterize the progenitors.

scholarly journals Galaxy formation and evolution with the Dark Energy Survey

2012 ◽  
Vol 8 (S295) ◽  
pp. 137-140
Author(s):  
Diego Capozzi ◽  
Daniel Thomas ◽  
Claudia Maraston ◽  
Luke J. M. Davies
Keyword(s):  
Dark Energy ◽  
Galaxy Evolution ◽  
Galaxy Formation ◽  
Large Scale ◽  
Time Range ◽  
Data Set ◽  
Dark Energy Survey ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Energy Survey

AbstractThe Dark Energy Survey (DES) will be the new state-of the-art in large-scale galaxy imaging surveys. With 5,000 deg2, it will cover an area of the sky similar to SDSS-II, but will go over two magnitudes deeper, reaching 24th magnitude in all four optical bands (griz). DES will further provide observations in the redder Y-band and will be complemented with VISTA observations in the near-infrared bands JHK. Hence DES will furnish an unprecedented combination of sky and wavelength coverage and depth, unreached by any of the existing galaxy surveys. The very nature of the DES data set – large volume at intermediate photometric depth – allows us to probe galaxy formation and evolution within a cosmic-time range of ~ 10 Gyr and in different environments. In fact there will be many galaxy clusters available for galaxy evolution studies, given that one of the main aims of DES is to use their abundance to constrain the equation of state of dark energy. The X-ray follow up of these clusters, coupled with the use of gravitational lensing, will provide very precise measures of their masses, enabling us to study in detail the influence of the environment on galaxy formation and evolution processes. DES will leverage the study of these processes by allowing us to perform a detailed investigation of the galaxy luminosity and stellar mass functions and of the relationship between dark and baryonic matter as described by the Halo Occupation Distribution.

scholarly journals Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

2022 ◽  
Vol 258 (1) ◽  
pp. 15
Author(s):  
S. Everett ◽  
B. Yanny ◽  
N. Kuropatkin ◽  
E. M. Huff ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Dark Energy ◽  
Transfer Function ◽  
Real Data ◽  
Generative Models ◽  
Density Fluctuations ◽  
Proximity Effects ◽  
Small Subset ◽  
Data Set ◽  
Dark Energy Survey ◽  
Energy Survey

Abstract We describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant “source” galaxies and magnification biases of nearer “lens” galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1–8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

scholarly journals Linear Systematics Mitigation in Galaxy Clustering in the Dark Energy Survey Year 1 Data

2021 ◽  
Author(s):  
Erika L Wagoner ◽  
Eduardo Rozo ◽  
Xiao Fang ◽  
Martín Crocce ◽  
Jack Elvin-Poole ◽  
...  
Keyword(s):  
Correlation Function ◽  
Dark Energy ◽  
Goodness Of Fit ◽  
Density Field ◽  
Data Set ◽  
Galaxy Clustering ◽  
Dark Energy Survey ◽  
Significant Bias ◽  
The Galaxy ◽  
Energy Survey

Abstract We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment 1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself; 2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints; 3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field; 4) is fully automated, and can therefore be trivially applied to any data set The updated correlation function for the DES Y1 redMaGiC catalog minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness of fit statistic of the DES Y1 3×2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

scholarly journals KiDS+VIKING-450 and DES-Y1 combined: Cosmology with cosmic shear

2020 ◽  
Vol 638 ◽  
pp. L1 ◽  
Author(s):  
S. Joudaki ◽  
H. Hildebrandt ◽  
D. Traykova ◽  
N. E. Chisari ◽  
C. Heymans ◽  
...  
Keyword(s):  
Dark Energy ◽  
Cosmic Microwave Background ◽  
Gravitational Lensing ◽  
Error Model ◽  
Calibration Error ◽  
Microwave Background ◽  
Weak Gravitational Lensing ◽  
Dark Energy Survey ◽  
Cosmic Shear ◽  
Energy Survey

We present a combined tomographic weak gravitational lensing analysis of the Kilo Degree Survey (KV450) and the Dark Energy Survey (DES-Y1). We homogenize the analysis of these two public cosmic shear datasets by adopting consistent priors and modeling of nonlinear scales, and determine new redshift distributions for DES-Y1 based on deep public spectroscopic surveys. Adopting these revised redshifts results in a 0.8σ reduction in the DES-inferred value for S​8, which decreases to a 0.5σ reduction when including a systematic redshift calibration error model from mock DES data based on the MICE2 simulation. The combined KV450+DES-Y1 constraint on S8 = 0.762−0.024+0.025 is in tension with the Planck 2018 constraint from the cosmic microwave background at the level of 2.5σ. This result highlights the importance of developing methods to provide accurate redshift calibration for current and future weak-lensing surveys.

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