7 papers
DISCO-DJ II: a differentiable particle-mesh code for cosmology
Florian List, Oliver Hahn, Thomas Flöss +1
The mildly non-linear regime of cosmic structure formation holds much of the information that upcoming large-scale structure surveys aim to exploit, making fast and accurate predic…
Differentiable Halo Mass Prediction and the Cosmology-Dependence of Halo Mass Functions
Jim Buisman, Florian List, Oliver Hahn
Modern cosmological inference increasingly relies on differentiable models to enable efficient, gradient-based parameter estimation and uncertainty quantification. Here, we present…
BullFrog: Multi-step perturbation theory as a time integrator for cosmological simulations
Cornelius Rampf, Florian List, Oliver Hahn
Modelling the cosmic large-scale structure can be done through numerical N-body simulations or by using perturbation theory. Here, we present an N-body approach that effectively im…
A deep learning framework for jointly extracting spectra and source-count distributions in astronomy
Florian Wolf, Florian List, Nicholas L. Rodd +1
Astronomical observations typically provide three-dimensional maps, encoding the distribution of the observed flux in (1) the two angles of the celestial sphere and (2) energy/freq…
DISCO-DJ I: a differentiable Einstein-Boltzmann solver for cosmology
Oliver Hahn, Florian List, Natalia Porqueres
We present the Einstein-Boltzmann module of the DISCO-DJ (DIfferentiable Simulations for COsmology - Done with JAX) software package. This module implements a fully differentiable…
Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models
Andreas Schanz, Florian List, Oliver Hahn
In recent years, deep learning models have been successfully employed for augmenting low-resolution cosmological simulations with small-scale information, a task known as "super-re…