2024/07/30 by Nashwan Sabti, Sabti, Nashwan, Reddy, Ram +6 · 3 citations
Earth and Planetary Sciences · Medicine · #Astrophysics of Galaxies (astro-ph.GA) #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Geological Modeling and Analysis #Medical Imaging Techniques and Applications #Seismic Imaging and Inversion Techniques
paper · pdf · doi:10.48550/arxiv.2407.21097
openalex publication_date 2024/07/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Analyses of the cosmic 21-cm signal are hampered by astrophysical foregrounds that are far stronger than the signal itself. These foregrounds, typically confined to a wedge-shaped region in Fourier space, often necessitate the removal of a vast majority of modes, thereby degrading the quality of the data anisotropically. To address this challenge, we introduce a novel deep generative model based on stochastic interpolants to reconstruct the 21-cm data lost to wedge filtering. Our method leverages the non-Gaussian nature of the 21-cm signal to effectively map wedge-filtered 3D lightcones to samples from the conditional distribution of wedge-recovered lightcones. We demonstrate how our method is able to restore spatial information effectively, considering both varying cosmological initial conditions and astrophysics. Furthermore, we discuss a number of future avenues where this approach could be applied in analyses of the 21-cm signal, potentially offering new opportunities to improve our understanding of the Universe during the epochs of cosmic dawn and reionization.