Search Results for author: Eric Aubourg

Found 4 papers, 3 papers with code

Neural Posterior Estimation with Differentiable Simulators

no code implementations12 Jul 2022 Justine Zeghal, François Lanusse, Alexandre Boucaud, Benjamin Remy, Eric Aubourg

Simulation-Based Inference (SBI) is a promising Bayesian inference framework that alleviates the need for analytic likelihoods to estimate posterior distributions.

Bayesian Inference Density Estimation +1

Deblending galaxies with Variational Autoencoders: a joint multi-band, multi-instrument approach

1 code implementation25 May 2020 Bastien Arcelin, Cyrille Doux, Eric Aubourg, Cécile Roucelle

The apparent superposition of galaxies with other astrophysical objects along the line of sight, a problem known as blending, will be a major challenge for upcoming, ground-based, deep, photometric galaxy surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).

Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics

Exploring cosmic homogeneity with the BOSS DR12 galaxy sample

2 code implementations7 Feb 2017 Pierros Ntelis, Jean-Christophe Hamilton, Jean-Marc Le Goff, Nicolas Guillermo Busca, Eric Aubourg, Pierre Laurent, James Rich, Etienne Burtin, Hélion du Mas des Bourboux, Nathalie Palanque Delabrouille, Christophe Yeche, David W. Hogg, Adam Myers, Jeremy Tinker, Julian Bautista, Timothée Delubac, Graziano Rossi, Donald P. Schneider Rita Toheiro, Mariana Vargas-Magaña

Defining the scale of transition to homogeneity as the scale at which $\mathcal{D}_2(r)$ reaches 3 within $1\%$, i. e. $\mathcal{D}_2(r)>2. 97$ for $r>\mathcal{R}_H$, we find $\mathcal{R}_H = (63. 3\pm0. 7) \ h^{-1}\ \mathrm{Mpc}$, in agreement at the percentage level with the predictions of the $\Lambda$CDM model $\mathcal{R}_H=62. 0\ h^{-1}\ \mathrm{Mpc}$.

Cosmology and Nongalactic Astrophysics

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