Research Highlights

Research Highlights

  • Early dark energy in the pre- and postrecombination epochs  Authors:   Adrià Gómez-Valent, Ziyang Zheng, Luca Amendola, Valeria Pettorino, Christof Wetterich Journal: PRD Year: 07/2021 Download: PRD | Arxiv Abstract Dark energy could play a role at redshifts z≫O(1). Many quintessence models possess scaling or attractor solutions where the fraction of dark energy follows the dominant component in previous epochs

  • Starlet l1-norm for weak lensing cosmology  Authors: Virginia Ajani, Jean-Luc Starck, Valeria Pettorino Journal: Astronomy & Astrophysics , Forthcoming article, Letters to the Editor Year: 01/2021 Download: A&A| Arxiv Abstract We present a new summary statistic for weak lensing observables, higher than second order, suitable for extracting non-Gaussian cosmological information and inferring cosmological parameters. We

  • Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear   Authors: Euclid Collaboration;Blanchard, A.;Camera, S.;Carbone, C.;Cardone, V. F.;Casas, S.;Clesse, S.;Ilić, S.;Kilbinger, M.;Kitching, T.;Kunz, M.;Lacasa, F.;Linder, E.;Majerotto, E.;Markovič, K.;Martinelli, M.;Pettorino, V.;Pourtsidou, A.;Sakr, Z.;Sánchez, A. G.;Sapone, D.;Tutusaus, I.;Yahia-Cherif, S.;Yankelevich, V.;et al. Journal: Astronomy & Astrophysics, Volume 642, id.A191, 66 pp. Year: 10/2020

  • XC importance

    Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear   Authors: Tutusaus, I.;Martinelli, M.;Cardone, V. F.;Camera, S.;Yahia-Cherif, S.;Casas, S.;Blanchard, A.;Kilbinger, M.;Lacasa, F.;Sakr, Z.;Ilić, S.;Kunz, M.;Carbone, C.;Castander, F. J.;Dournac, F.;Fosalba, P.;Kitching, T.;Markovic, K.;Mangilli, A.;Pettorino, V.;Sapone, D.;Yankelevich, V.;et al. Journal:   Astronomy & Astrophysics, Volume 643, id.A70, 17 pp. Year: 11/2020 Download:

  • The notion of self acceleration has been introduced as a convenient way to theoretically distinguish cosmological models in which acceleration is due to modified gravity from those in which it is due to the properties of matter or fields. In this paper we review the concept of self acceleration as given, for example, by [1],

  • DeepMass: The first Deep Learning reconstruction of dark matter maps from weak lensing observational data (DES SV weak lensing data)DeepMass This is the first reconstruction of dark matter maps from weak lensing observational data using deep learning. We train a convolution neural network (CNN) with a Unet based architecture on over 3.6 x 10^5 simulated data

  • Diffuse Galactic thermal dust emission: modified black-body parameter maps Diffuse emissions are ubiquitous within our Galaxy. They probe star-forming regions, the chemical composition of the Galaxy and the Galactic magnetic field. Conversely, they also obscure cosmological measurements such as the cosmic microwave background and the epoch of reionisation signal. Detailed characterisation of these emissions is

  • Weak lensing 2D & 3D density fluctuation map reconstruction The 3D tomographic weak lensing is one of the most important tools for modern cosmology:  Underlying the link between weak lensing and the compressed sensing theory, we have proposed a  new approach to reconstruct the dark matter distribution in two and three dimensions, using photometric redshift

  • Cosmology and Fundamental Physics with the Euclid Satellite Understanding the source of cosmic acceleration in the universe is one of the major challenges that will be addressed by future surveys like the Euclid space mission. Acceleration may be caused by a cosmological constant or by a dynamical fluid (dark energy) or rather be a sign

  • Radio-Interferometry: Improving the Resolution by a Factor of 4 (2 in each spatial dimension) Sparse recovery allows us to reconstruct radio-interferometric images with a resolution increased by a factor two. This has been confirmed by comparing two images of the Cygnus A radio source, the first one from the LOFAR instrument and reconstructed using sparsity,