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Baryonic effects for weak lensing. Part II. Combination with X-ray data and extended cosmologies
Aurel Schneider, Alexandre Refregier, Sebastian Grandis +6
An accurate modelling of baryonic feedback effects is required to exploit the full potential of future weak-lensing surveys such as Euclid or LSST. In this second paper in a series…
Cosmological N-body simulations: a challenge for scalable generative models
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi +3
Deep generative models, such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAs) have been demonstrated to produce images of high visual quality. However, t…
Monte Carlo Control Loops for cosmic shear cosmology with DES Year 1
T. Kacprzak, J. Herbel, A. Nicola +52
Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and re…
Cosmological constraints with deep learning from KiDS-450 weak lensing maps
Janis Fluri, Tomasz Kacprzak, Aurelien Lucchi +4
Convolutional Neural Networks (CNN) have recently been demonstrated on synthetic data to improve upon the precision of cosmological inference. In particular they have the potential…
Effects of baryons on weak lensing peak statistics
Andreas J. Weiss, Aurel Schneider, Raphael Sgier +3
Upcoming weak-lensing surveys have the potential to become leading cosmological probes provided all systematic effects are under control. Recently, the ejection of gas due to feedb…
DeepSphere: towards an equivariant graph-based spherical CNN
Michaël Defferrard, Nathanaël Perraudin, Tomasz Kacprzak +1
Spherical data is found in many applications. By modeling the discretized sphere as a graph, we can accommodate non-uniformly distributed, partial, and changing samplings. Moreover…