Conditional Diffusion-Flow models for generating 3D cosmic density fields: applications to f(R) cosmologies

Conditional Diffusion-Flow models for generating 3D cosmic density fields: applications to f(R) cosmologies

Next-generation galaxy surveys promise unprecedented precision in testing gravity at cosmological scales. However, realising this potential requires accurately modelling the non-linear cosmic web. We address this challenge by exploring conditional generative modelling to create 3D dark matter densit...

Full description

Saved in:
Bibliographic Details
Main Authors: Julieth K Riveros, Paola A Saavedra, Héctor J Hortúa, Jorge Enrique García-Farieta, Ivan Olier
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
cosmology: large-scale structure of Universe
methods: statistical
methods: numerical
diffusion models
Online Access:https://doi.org/10.1088/2632-2153/adf8b1
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1088/2632-2153/adf8b1

Similar Items