Speaker
Description
Mapping the three-dimensional topology of reionization is one of the defining science goals of the SKA era. While SKA-Low will deliver 21-cm brightness-temperature maps of the neutral intergalactic medium (IGM), foreground contamination and calibration systematics remain central challenges for field-level inference. I will present TORRCH (TOmographic Reconstruction of the Reionization of Cosmic Hydrogen), a deep-learning framework that reconstructs the neutral-hydrogen fraction field during the Epoch of Reionization (EoR) directly from the spatial distributions of Lyman-alpha emitters (LAEs) and non-Lyman-alpha-selected galaxies (NLSGs), providing a foreground-free, galaxy-anchored view of ionization morphology that is complementary to 21-cm observations.
TORRCH employs a deterministic 3D U-Net trained on hydrodynamical simulations post-processed with radiative transfer, spanning diverse reionization scenarios and realistic survey depths comparable to current and forthcoming JWST and Subaru programmes. The framework recovers large-scale ionization topology, the one-point distribution of neutral fractions, the projected power spectrum, and the galaxy-IGM cross-correlation, with good fidelity on scales above ~7 h^-1 cMpc, and remains robust to realistic redshift uncertainties and ionization conditions not seen during training. With JWST delivering ever-deeper galaxy samples in the EoR, such galaxy-based tomography offers an independent, foreground-clean route to field-level reionization constraints and a natural synergistic counterpart to SKA-Low science.
