Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds
We introduce the state-of-the-art deep-learning denoising diffusion probabilistic model as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps. We adopt magnetohydrodynamic simulations with different global magnetic field strengths...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2023-01-01
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| Series: | The Astrophysical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-4357/accae5 |