Machine learning astrophysics from 21 cm lightcones: impact of network architectures and signal contamination

Understand

Imaging the cosmic 21 cm signal will map out the first billion years of our Universe.

• The resulting 3D lightcone (LC) will encode the properties of the unseen first galaxies and physical cosmology.
• Here, we build on previous work using neural networks (NNs) to infer astrophysical parameters directly from 21 cm LC images.
• We introduce recurrent neural networks (RNNs), capable of efficiently characterizing the evolution along the redshift axis of 21 cm LC images.