5 papers
RAMSES-GPU: Cell-by-Cell Adaptive Mesh Refinement with Magneto-Hydrodynamics and Self-Gravity on Graphics Processing Units
Romain Teyssier, Eric Moseley, Robert V. Caddy +9
We present the implementation and optimization of the cosmological simulation code RAMSES on Graphics Processing Units (GPUs) using CUDA Fortran. This accelerated version ports the…
Learning the Universe with the 2nd Generation of CAMELS: Varying 35 parameters of the IllustrisTNG model in (50Mpc/h)^3 boxes
Shy Genel, Yongseok Jo, Boon Kiat Oh +10
We present a new set of 1,192 cosmological simulations as part of the CAMELS project, in which a space of 35 cosmological, astrophysical, and numerical parameters is explored aroun…
CosmoBench: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning
Ningyuan Huang, Richard Stiskalek, Jun-Young Lee +6
Cosmological simulations provide a wealth of data in the form of point clouds and directed trees. A crucial goal is to extract insights from this data that shed light on the nature…
The Denario project: Deep knowledge AI agents for scientific discovery
Francisco Villaescusa-Navarro, Boris Bolliet, Pablo Villanueva-Domingo +33
We present Denario, an AI multi-agent system designed to serve as a scientific research assistant. Denario can perform many different tasks, such as generating ideas, checking the…
Cosmology with Topological Deep Learning
Jun-Young Lee, Francisco Villaescusa-Navarro
The standard cosmological model with cold dark matter posits a hierarchical formation of structures. We introduce topological neural networks (TNNs), implemented as message-passing…