11 papers
Dark Energy Survey Year 3 results: Simulation-based CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design
A. Thomsen, J. Bucko, T. Kacprzak +99
Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the f…
: fast differentiable angular power spectra beyond Limber
Laura Reymond, Alexander Reeves, Pierre Zhang +1
The upcoming stage IV wide-field surveys will provide high precision measurements of the large-scale structure (LSS) of the universe. Their interpretation requires fast and accurat…
Baryonification: An alternative to hydrodynamical simulations for cosmological studies
Aurel Schneider, Michael KovaÄ, Jozef Bucko +8
We present an improved baryonification (BFC) model that modifies dark-matter-only -body simulations to generate particle-level outputs for gas, dark matter, and stars. Unlike pr…
galsbi: A Python package for the GalSBI galaxy population model
Silvan Fischbacher, Beatrice Moser, Tomasz Kacprzak +5
Large-scale structure surveys measure the shapes and positions of millions of galaxies in order to constrain the cosmological model with high precision. The resulting large data vo…
GalSBI-SPS: a stellar population synthesis-based galaxy population model for cosmology and galaxy evolution applications
Luca Tortorelli, Silvan Fischbacher, Daniel Grün +4
Next generation photometric and spectroscopic surveys will enable unprecedented tests of the concordance cosmological model and of galaxy formation and evolution. Fully exploiting…
UFig v1: The ultra-fast image generator
Silvan Fischbacher, Beatrice Moser, Tomasz Kacprzak +8
With the rise of simulation-based inference (SBI) methods, simulations need to be fast as well as realistic. is a public Python package that simulates astronomic…