dm2gal: Mapping Dark Matter to Galaxies with Neural Networks

Understand

Maps of cosmic structure produced by galaxy surveys are one of the key tools for answering fundamental questions about the Universe.

• Accurate theoretical predictions for these quantities are needed to maximize the scientific return of these programs.
• Simulating the Universe by including gravity and hydrodynamics is one of the most powerful techniques to accomplish this; unfortunately, these simulations are very expensive computationally.
• Alternatively, gravity-only simulations are cheaper, but do not predict the locations and properties of galaxies in the cosmic web.