Dark Energy Survey Year 1 Results: redshift distributions of the weak-lensing source galaxies

ABSTRACT Weak lensing source galaxy catalogues used in estimating the masses of galaxy clusters can be heavily contaminated by cluster members, prohibiting accurate mass calibration. In this study, we test the performance of an estimator for the extent of cluster member contamination based on decomposing the photometric redshift P(z) of source galaxies into contaminating and background components. We perform a full scale mock analysis on a simulated sky survey approximately mirroring the observational properties of the Dark Energy Survey Year One observations (DES Y1), and find excellent agreement between the true number profile of contaminating cluster member galaxies in the simulation and the estimated one. We further apply the method to estimate the cluster member contamination for the DES Y1 redMaPPer cluster mass calibration analysis, and compare the results to an alternative approach based on the angular correlation of weak lensing source galaxies. We find indications that the correlation based estimates are biased by the selection of the weak lensing sources in the cluster vicinity, which does not strongly impact the P(z) decomposition method. Collectively, these benchmarks demonstrate the strength of the P(z) decomposition method in alleviating membership contamination and enabling highly accurate cluster weak lensing studies without broad exclusion of source galaxies, thereby improving the total constraining power of cluster mass calibration via weak lensing.

Download Full-text

Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

Physical Review D ◽

10.1103/physrevd.94.042005 ◽

2016 ◽

Vol 94 (4) ◽

Cited By ~ 71

Author(s):

C. Bonnett ◽

M. A. Troxel ◽

W. Hartley ◽

A. Amara ◽

B. Leistedt ◽

...

Keyword(s):

Dark Energy ◽

Weak Lensing ◽

Dark Energy Survey ◽

Energy Survey

Download Full-text

Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/sty2711 ◽

2018 ◽

Vol 482 (1) ◽

pp. 1352-1378 ◽

Cited By ~ 50

Author(s):

T McClintock ◽

T N Varga ◽

D Gruen ◽

E Rozo ◽

E S Rykoff ◽

...

Keyword(s):

Dark Energy ◽

Galaxy Clusters ◽

Weak Lensing ◽

Dark Energy Survey ◽

Mass Calibration ◽

Energy Survey

Download Full-text

Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stw2106 ◽

2016 ◽

Vol 466 (2) ◽

pp. 1444-1461 ◽

Cited By ~ 30

Author(s):

L. Clerkin ◽

D. Kirk ◽

M. Manera ◽

O. Lahav ◽

F. Abdalla ◽

...

Keyword(s):

Dark Energy ◽

Weak Lensing ◽

Dark Energy Survey ◽

The Galaxy ◽

Energy Survey

Download Full-text

Ridges in the Dark Energy Survey for cosmic trough identification

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa3204 ◽

2020 ◽

Vol 500 (1) ◽

pp. 859-870

Author(s):

Ben Moews ◽

Morgan A Schmitz ◽

Andrew J Lawler ◽

Joe Zuntz ◽

Alex I Malz ◽

...

Keyword(s):

Dark Energy ◽

Large Scale ◽

Mass Density ◽

Mean Shift ◽

Large Scale Structure ◽

Wasserstein Distance ◽

Scale Structure ◽

Weak Lensing ◽

Dark Energy Survey ◽

Energy Survey

ABSTRACT Cosmic voids and their corresponding redshift-projected mass densities, known as troughs, play an important role in our attempt to model the large-scale structure of the Universe. Understanding these structures enables us to compare the standard model with alternative cosmologies, constrain the dark energy equation of state, and distinguish between different gravitational theories. In this paper, we extend the subspace-constrained mean shift algorithm, a recently introduced method to estimate density ridges, and apply it to 2D weak lensing mass density maps from the Dark Energy Survey Y1 data release to identify curvilinear filamentary structures. We compare the obtained ridges with previous approaches to extract trough structure in the same data, and apply curvelets as an alternative wavelet-based method to constrain densities. We then invoke the Wasserstein distance between noisy and noiseless simulations to validate the denoising capabilities of our method. Our results demonstrate the viability of ridge estimation as a precursor for denoising weak lensing observables to recover the large-scale structure, paving the way for a more versatile and effective search for troughs.

Download Full-text