7 citations · 9 across the 4 of their papers we have counts for
4 papers
Velocityformer: Broken-Symmetry-Matched Equivariant Graph Transformers for Cosmological Velocity Reconstruction
Tilman Tröster, David Mirkovic, Veronika Oehl +1
Precise measurement of the kinematic Sunyaev-Zel'dovich (kSZ) effect - a probe of the large-scale distribution of baryonic matter, a key observable for cosmological inference - req…
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…
Hybrid Physical-Neural Simulator for Fast Cosmological Hydrodynamics
Arne Thomsen, Tilman Tröster, François Lanusse
Cosmological field-level inference requires differentiable forward models that solve the challenging dynamics of gas and dark matter under hydrodynamics and gravity. We propose a h…
Dark Energy Survey Year 3 results: CDM cosmology from simulation-based inference with persistent homology on the sphere
J. Prat, M. Gatti, C. Doux +94
We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how featu…