HInet: Generating neutral hydrogen from dark matter with neural networks

Understand

Upcoming 21cm surveys will map the spatial distribution of cosmic neutral hydrogen (HI) over very large cosmological volumes.

• In order to maximize the scientific return of these surveys, accurate theoretical predictions are needed.
• Hydrodynamic simulations currently are the most accurate tool to provide those predictions in the mildly to non-linear regime.
• Unfortunately, their computational cost is very high: tens of millions of CPU hours.