2020/02/29 by Hayato Shimabukuro, Yi Mao, Jianrong Tan
Environmental Science · Mathematics · Physics and Astronomy · #Astronomical interferometer #Astrophysics #Astrophysics and Cosmic Phenomena #Bubble #Computational physics #Galaxy #Interferometry #Mathematics #Optics #Physics #Radio Astronomy Observations and Technology #Redshift #Reionization #Soil Moisture and Remote Sensing #Spectral density #Statistics #astro-ph.CO
paper · pdf · doi:10.1088/1674-4527/ac4ca3
published as Research in Astronomy & Astrophysics,Volume 22, Number3,35027 (2022) · 17 pages, 14 figures. Published in RAA
openalex publication_date 2022/01/18 · arxiv created 2022/03/12 · arxiv updated 2022/03/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
The bubble size distribution of ionized hydrogen regions probes the information about the morphology of \HII bubbles during the reionization. Conventionally, the \HII bubble size distribution can be derived from the tomographic imaging data of the redshifted 21~cm signal from the epoch of reionization, which, however, is observationally challenging even for the upcoming large radio interferometer arrays. Given that these interferometers promise to measure the 21~cm power spectrum accurately, we propose a new method, which is based on the artificial neural networks (ANN), to reconstruct the \HII bubble size distribution from the 21~cm power spectrum. We demonstrate that the reconstruction from the 21~cm power spectrum can be almost as accurate as directly measured from the imaging data with the fractional error \lesssim 10%, even with thermal noise at the sensitivity level of the Square Kilometre Array. Nevertheless, the reconstruction implicitly exploits the modelling in reionization simulations, and hence the recovered \HII bubble size distribution is not an independent summary statistic from the power spectrum, and should be used only as the indicator for understanding \HII bubble morphology and its evolution.