5 papers
Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys
Dominik Zürcher, Janis Fluri, Raphael Sgier +2
Cosmic shear data contains a large amount of cosmological information encapsulated in the non-Gaussian features of the weak lensing mass maps. This information can be extracted usi…
Predicting Cosmological Observables with PyCosmo
F. Tarsitano, U. Schmitt, A. Refregier +7
Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the co…
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…
Cosmological constraints from noisy convergence maps through deep learning
Janis Fluri, Tomasz Kacprzak, Aurelien Lucchi +3
Deep learning is a powerful analysis technique that has recently been proposed as a method to constrain cosmological parameters from weak lensing mass maps. Due to its ability to l…
Weak lensing peak statistics in the era of large scale cosmological surveys
Janis Fluri, Tomasz Kacprzak, Raphael Sgier +2
Weak lensing peak counts are a powerful statistical tool for constraining cosmological parameters. So far, this method has been applied only to surveys with relatively small areas,…