High-fidelity reproduction of central galaxy joint distributions with Neural Networks
Published in MNRAS, 2023
Natália V N Rodrigues, Natalà S M de Santi, et al., 2023, https://doi.org/10.1093/mnras/stad1186 https://doi.org/10.1093/mnras/stad1186
Paper highlights:
- Uses neural networks to predict full probability distributions of central galaxy properties from dark matter halo features in the IllustrisTNG300 simulation.
- Captures the intrinsic scatter in the halo–galaxy connection, enabling uncertainty quantification and detailed modeling of distinct galaxy populations.
- Accurately reproduces galaxy clustering statistics, outperforming traditional single-point estimators.
You can read the paper here.