scholarly journals On the relative bias of void tracers in the Dark Energy Survey

2019 ◽  
Vol 487 (2) ◽  
pp. 2836-2852 ◽  
Author(s):  
G Pollina ◽  
N Hamaus ◽  
K Paech ◽  
K Dolag ◽  
J Weller ◽  
...  

Abstract Luminous tracers of large-scale structure are not entirely representative of the distribution of mass in our Universe. As they arise from the highest peaks in the matter density field, the spatial distribution of luminous objects is biased towards those peaks. On large scales, where density fluctuations are mild, this bias simply amounts to a constant offset in the clustering amplitude of the tracer, known as linear bias. In this work we focus on the relative bias between galaxies and galaxy clusters that are located inside and in the vicinity of cosmic voids, extended regions of relatively low density in the large-scale structure of the Universe. With the help of mock data we verify that the relation between galaxy and cluster overdensity around voids remains linear. Hence, the void-centric density profiles of different tracers can be linked by a single multiplicative constant. This amounts to the same value as the relative linear bias between tracers for the largest voids in the sample. For voids of small sizes, which typically arise in higher density regions, this constant has a higher value, possibly showing an environmental dependence similar to that observed for the linear bias itself. We confirm our findings by analysing data obtained during the first year of observations by the Dark Energy Survey. As a side product, we present the first catalogue of three-dimensional voids extracted from a photometric survey with a controlled photo-z uncertainty. Our results will be relevant in forthcoming analyses that attempt to use voids as cosmological probes.

2020 ◽  
Vol 500 (1) ◽  
pp. 859-870
Author(s):  
Ben Moews ◽  
Morgan A Schmitz ◽  
Andrew J Lawler ◽  
Joe Zuntz ◽  
Alex I Malz ◽  
...  

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.


2013 ◽  
Vol 429 (3) ◽  
pp. 1902-1912 ◽  
Author(s):  
Gregory B. Poole ◽  
Chris Blake ◽  
David Parkinson ◽  
Sarah Brough ◽  
Matthew Colless ◽  
...  

2018 ◽  
Vol 98 (10) ◽  
Author(s):  
Thiago R. P. Caramês ◽  
H. Velten ◽  
J. C. Fabris ◽  
Matheus J. Lazo

2004 ◽  
Vol 69 (2) ◽  
Author(s):  
Tuomas Multamäki ◽  
Marc Manera ◽  
Enrique Gaztañaga

2019 ◽  
Vol 630 ◽  
pp. A151 ◽  
Author(s):  
Natalia Porqueres ◽  
Jens Jasche ◽  
Guilhem Lavaux ◽  
Torsten Enßlin

One of the major science goals over the coming decade is to test fundamental physics with probes of the cosmic large-scale structure out to high redshift. Here we present a fully Bayesian approach to infer the three-dimensional cosmic matter distribution and its dynamics at z >  2 from observations of the Lyman-α forest. We demonstrate that the method recovers the unbiased mass distribution and the correct matter power spectrum at all scales. Our method infers the three-dimensional density field from a set of one-dimensional spectra, interpolating the information between the lines of sight. We show that our algorithm provides unbiased mass profiles of clusters, becoming an alternative for estimating cluster masses complementary to weak lensing or X-ray observations. The algorithm employs a Hamiltonian Monte Carlo method to generate realizations of initial and evolved density fields and the three-dimensional large-scale flow, revealing the cosmic dynamics at high redshift. The method correctly handles multi-modal parameter distributions, which allow constraining the physics of the intergalactic medium with high accuracy. We performed several tests using realistic simulated quasar spectra to test and validate our method. Our results show that detailed and physically plausible inference of three-dimensional large-scale structures at high redshift has become feasible.


2005 ◽  
Vol 216 ◽  
pp. 373-380
Author(s):  
Marguerite Pierre

We outline the main arguments in favor of cosmological X-ray surveys of galaxy clusters. We summarize recent advances in our understanding of cluster physics. After a short review of past surveys, we present the scientific motivations of the XMM Large Scale Structure survey. We further illustrate how such a survey can help constrain the nature of the dark energy as well as cluster scaling law evolution, i.e. non-gravitational physics.


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