Extracting the Epoch of Reionization Signal with 3D U-Net Neural Networks Using a Data-driven Systematic Effect Model

Extracting the Epoch of Reionization Signal with 3D U-Net Neural Networks Using a Data-driven Systematic Effect Model

Neutral hydrogen serves as a crucial probe for the Cosmic Dawn and the Epoch of Reionization (EoR). Actual observations of the 21 cm signal often encounter challenges such as thermal noise and various systematic effects. To overcome these challenges, we simulate SKA-Low-depth images in the South Cel...

Full description

Saved in:
Bibliographic Details
Main Authors: Li-Yang Gao, Léon V. E. Koopmans, Florent G. Mertens, Satyapan Munshi, Yichao Li, Stefanie A. Brackenhoff, Emilio Ceccotti, J. Kariuki Chege, Anshuman Acharya, Raghunath Ghara, Sambit K. Giri, Ilian T. Iliev, Garrelt Mellema, Xin Zhang
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal
Subjects:
H I line emission
Reionization
Gaussian Processes regression
Neural networks
Online Access:https://doi.org/10.3847/1538-4357/ade2dc
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items