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 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 The WiggleZ Dark Energy Survey: small-scale clustering of Lyman-break galaxies atz< 1

2009 ◽  
Vol 395 (1) ◽  
pp. 240-254 ◽  
Author(s):  
Chris Blake ◽  
Russell J. Jurek ◽  
Sarah Brough ◽  
Matthew Colless ◽  
Warrick Couch ◽  
...  
Keyword(s):  
Dark Energy ◽  
Small Scale ◽  
Dark Energy Survey ◽  
Lyman Break Galaxies ◽  
Energy Survey

scholarly journals KiDS+VIKING-450 and DES-Y1 combined: Mitigating baryon feedback uncertainty with COSEBIs

2020 ◽  
Vol 634 ◽  
pp. A127 ◽  
Author(s):  
Marika Asgari ◽  
Tilman Tröster ◽  
Catherine Heymans ◽  
Hendrik Hildebrandt ◽  
Jan Luca van den Busch ◽  
...  
Keyword(s):  
Dark Energy ◽  
Mode Analysis ◽  
Small Scale ◽  
Microwave Background ◽  
Cosmological Constraints ◽  
Dark Energy Survey ◽  
Matter Power Spectrum ◽  
Λcdm Model ◽  
Cosmic Shear ◽  
Energy Survey

We present cosmological constraints from a joint cosmic shear analysis of the Kilo-Degree Survey (KV450) and the Dark Energy Survey (DES-Y1), which were conducted using Complete Orthogonal Sets of E/B-Integrals (COSEBIs). With COSEBIs, we isolated any B-modes that have a non-cosmic shear origin and demonstrate the robustness of our cosmological E-mode analysis as no significant B-modes were detected. We highlight how COSEBIs are fairly insensitive to the amplitude of the non-linear matter power spectrum at high k-scales, mitigating the uncertain impact of baryon feedback in our analysis. COSEBIs, therefore, allowed us to utilise additional small-scale information, improving the DES-Y1 joint constraints on S8 = σ8(Ωm/0.3)0.5 and Ωm by 20%. By adopting a flat ΛCDM model we find S8 = 0.755−0.021+0.019, which is in 3.2σ tension with the Planck Legacy analysis of the cosmic microwave background.

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 Dark energy survey year 3 results: Covariance modelling and its impact on parameter estimation and quality of fit

2021 ◽  
Author(s):  
O Friedrich ◽  
F Andrade-Oliveira ◽  
H Camacho ◽  
O Alves ◽  
R Rosenfeld ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Dark Energy ◽  
Goodness Of Fit ◽  
Function Analysis ◽  
State Parameter ◽  
Covariance Model ◽  
Dark Energy Survey ◽  
The Impact ◽  
Energy Survey

Abstract We describe and test the fiducial covariance matrix model for the combined 2-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) dataset. Using a variety of new ansatzes for covariance modelling and testing we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot-noise, galaxy weighting schemes and other, sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness-of-fit and parameter estimation. The largest impact on best-fit figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent}}$ (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for Ωm and σ8 by about $3{{\ \rm per\ cent}}$ and for the dark energy equation of state parameter by about $5{{\ \rm per\ cent}}$.

scholarly journals Dark energy survey year 1 results: Constraining baryonic physics in the Universe

2021 ◽  
Vol 502 (4) ◽  
pp. 6010-6031
Author(s):  
Hung-Jin Huang ◽  
Tim Eifler ◽  
Rachel Mandelbaum ◽  
Gary M Bernstein ◽  
Anqi Chen ◽  
...  
Keyword(s):  
Dark Energy ◽  
Large Scale ◽  
Principal Component ◽  
External Information ◽  
Small Scale ◽  
Acoustic Oscillations ◽  
Dark Energy Survey ◽  
Theoretical Predictions ◽  
Hydrodynamical Simulations ◽  
Energy Survey

ABSTRACT Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3 × 2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modelling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q1) generally reflects the strength of baryon feedback. With the upper limit of Q1 prior being bound by the Illustris feedback scenarios, we reach $\sim 20{{\ \rm per\ cent}}$ improvement in the constraint of $S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3 × 2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q1 prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ.

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 Combination of cluster number counts and two-point correlations: validation on mock Dark Energy Survey

2021 ◽  
Vol 502 (3) ◽  
pp. 4093-4111
Author(s):  
Chun-Hao To ◽  
Elisabeth Krause ◽  
Eduardo Rozo ◽  
Hao-Yi Wu ◽  
Daniel Gruen ◽  
...  
Keyword(s):  
Dark Energy ◽  
Large Scale ◽  
Galaxy Cluster ◽  
Small Scale ◽  
Cluster Number ◽  
Dark Energy Survey ◽  
Simulated Likelihood ◽  
Significant Difference ◽  
Systematic Effects ◽  
Energy Survey

ABSTRACT We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.

Sign in / Sign up

Export Citation Format

Share Document