%0 Journal Article
%T Unmasking the masked Universe: the 2M++ catalogue through Bayesian eyes
%+ Institut d'Astrophysique de Paris (IAP)
%A Lavaux, Guilhem
%A Jasche, Jens
%< avec comitÃ© de lecture
%@ 0035-8711
%J Monthly Notices of the Royal Astronomical Society
%I Oxford University Press (OUP): Policy P - Oxford Open Option A
%V 455
%P 3169-3179
%8 2016
%D 2016
%Z 1509.05040
%Z 2016MNRAS.455.3169L
%R 10.1093/mnras/stv2499
%K methods: data analysis
%K methods: statistical
%K galaxies: statistics
%K large-scale structure of Universe
%K Astrophysics - Cosmology and Nongalactic Astrophysics
%Z Sciences of the Universe [physics]
%Z Sciences of the Universe [physics]/Astrophysics [astro-ph]Journal articles
%X This work describes a full Bayesian analysis of the Nearby Universe as traced by galaxies of the 2M++ survey. The analysis is run in two sequential steps. The first step self-consistently derives the luminosity-dependent galaxy biases, the power spectrum of matter fluctuations and matter density fields within a Gaussian statistic approximation. The second step makes a detailed analysis of the three-dimensional large-scale structures, assuming a fixed bias model and a fixed cosmology. This second step allows for the reconstruction of both the final density field and the initial conditions at z = 1000 assuming a fixed bias model. From these, we derive fields that self-consistently extrapolate the observed large-scale structures. We give two examples of these extrapolation and their utility for the detection of structures: the visibility of the Sloan Great Wall, and the detection and characterization of the Local Void using DIVA, a Lagrangian based technique to classify structures.
%G English
%2 https://insu.hal.science/insu-03747403/document
%2 https://insu.hal.science/insu-03747403/file/stv2499.pdf
%L insu-03747403
%U https://insu.hal.science/insu-03747403
%~ INSU
%~ CNRS
%~ IAP
%~ SORBONNE-UNIVERSITE
%~ SU-INF-2018
%~ SU-SCIENCES
%~ SU-TI
%~ ALLIANCE-SU