AI RESEARCH
Three-dimensional Conditional Diffusion Models for Cosmological 21 cm Lightcone Emulation
arXiv CS.LG
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ArXi:2605.29016v1 Announce Type: cross We investigate conditional diffusion modeling for three-dimensional 21 cm lightcone emulation, focusing on cubes with a sky-plane size of $64\times64$ and a line-of-sight depth up to 1024 cells. Relative to earlier 2D studies, the 3D setting is substantially harder because memory limits enforce very small micro-batches while the underlying voxel distribution is highly skewed and long tailed. We perform controlled comparisons across preprocessing choices, dynamic-range compression settings, architecture depth, and.