scholarly journals Second‐Order Corrections to Weak Lensing by Large‐Scale Structure

2002 ◽  
Vol 574 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Asantha Cooray ◽  
Wayne Hu
Keyword(s):  
Large Scale ◽  
Large Scale Structure ◽  
Second Order ◽  
Scale Structure ◽  
Weak Lensing

scholarly journals Higher order Hamiltonian Monte Carlo sampling for cosmological large-scale structure analysis

2021 ◽  
Vol 502 (3) ◽  
pp. 3976-3992
Author(s):  
Mónica Hernández-Sánchez ◽  
Francisco-Shu Kitaura ◽  
Metin Ata ◽  
Claudio Dalla Vecchia
Keyword(s):  
Fourth Order ◽  
Large Scale ◽  
Equations Of Motion ◽  
Large Scale Structure ◽  
Real Space ◽  
Higher Order ◽  
Second Order ◽  
Scale Structure ◽  
Integration Schemes ◽  
Reconstruction Methods

ABSTRACT We investigate higher order symplectic integration strategies within Bayesian cosmic density field reconstruction methods. In particular, we study the fourth-order discretization of Hamiltonian equations of motion (EoM). This is achieved by recursively applying the basic second-order leap-frog scheme (considering the single evaluation of the EoM) in a combination of even numbers of forward time integration steps with a single intermediate backward step. This largely reduces the number of evaluations and random gradient computations, as required in the usual second-order case for high-dimensional cases. We restrict this study to the lognormal-Poisson model, applied to a full volume halo catalogue in real space on a cubical mesh of 1250 h−1 Mpc side and 2563 cells. Hence, we neglect selection effects, redshift space distortions, and displacements. We note that those observational and cosmic evolution effects can be accounted for in subsequent Gibbs-sampling steps within the COSMIC BIRTH algorithm. We find that going from the usual second to fourth order in the leap-frog scheme shortens the burn-in phase by a factor of at least ∼30. This implies that 75–90 independent samples are obtained while the fastest second-order method converges. After convergence, the correlation lengths indicate an improvement factor of about 3.0 fewer gradient computations for meshes of 2563 cells. In the considered cosmological scenario, the traditional leap-frog scheme turns out to outperform higher order integration schemes only when considering lower dimensional problems, e.g. meshes with 643 cells. This gain in computational efficiency can help to go towards a full Bayesian analysis of the cosmological large-scale structure for upcoming galaxy surveys.

scholarly journals Weak lensing of large scale structure in the presence of screening

2015 ◽  
Vol 2015 (10) ◽  
pp. 036-036 ◽  
Author(s):  
Nicolas Tessore ◽  
Hans A. Winther ◽  
R. Benton Metcalf ◽  
Pedro G. Ferreira ◽  
Carlo Giocoli
Keyword(s):  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Weak Lensing

scholarly journals Weak Lensing by Large‐Scale Structure with the FIRST Radio Survey

2004 ◽  
Vol 617 (2) ◽  
pp. 794-810 ◽  
Author(s):  
Tzu‐Ching Chang ◽  
Alexandre Refregier ◽  
David J. Helfand
Keyword(s):  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Weak Lensing ◽  
Radio Survey

scholarly journals Weak Lensing of the CMB by Large Scale Structure

2004 ◽  
Vol 2004 (IAUS225) ◽  
pp. 105-109 ◽  
Author(s):  
A. Amblard ◽  
C. Vale ◽  
M. White
Keyword(s):  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Weak Lensing

scholarly journals DO WE HAVE EVIDENCE FOR NEW PHYSICS IN THE SKY?

2006 ◽  
Vol 21 (01) ◽  
pp. 1-21 ◽  
Author(s):  
LAURA MERSINI-HOUGHTON
Keyword(s):  
String Theory ◽  
Large Scale ◽  
Recent Progress ◽  
Large Scale Structure ◽  
New Physics ◽  
Scale Structure ◽  
Weak Lensing ◽  
Source Terms ◽  
Crucial Importance

Predicting signatures of string theory on cosmological observables is not sufficient. Often the observable effects string theory may impact upon the cosmological arena which may equally be predicted by features of inflationary physics. The question: what observable signatures are unique to new physics, is thus of crucial importance for claiming evidence for the theory. Here we discuss recent progress in addressing the above question. The evidence relies on identifying discrepancies between the source terms that give rise to large scale structure (LSS) and CMB, by cross-correlating the weak lensing potential that maps LSS with the CMB spectra.

Weak Lensing by Large-Scale Structure: A Dark Matter Halo Approach

2000 ◽  
Vol 535 (1) ◽  
pp. L9-L12 ◽  
Author(s):  
Asantha Cooray ◽  
Wayne Hu ◽  
Jordi Miralda-Escudé
Keyword(s):  
Dark Matter ◽  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Dark Matter Halo ◽  
Weak Lensing

scholarly journals Ridges in the Dark Energy Survey for cosmic trough identification

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.

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