3 papers
astro-ph.IM2024
Application of Physics-Informed Neural Networks in Removing Telescope Beam Effects
Shulei Ni, Yisheng Qiu, Yunchuan Chen +5
This study introduces {\tt{PI-AstroDeconv}}, a physics-informed semi-supervised learning method specifically designed for removing beam effects in astronomical telescope observatio…
astro-ph.GA2024
Spectuner: A Framework for Automated Line Identification of Interstellar Molecules
Yisheng Qiu, Tianwei Zhang, Thomas Möller +4
Interstellar molecules, which play an important role in astrochemistry, are identified using observed spectral lines. Despite the advent of spectral analysis tools in the past deca…
astro-ph.IM2024
PI-AstroDeconv: A Physics-Informed Unsupervised Learning Method for Astronomical Image Deconvolution
Shulei Ni, Yisheng Qiu, Yunchun Chen +4
In the imaging process of an astronomical telescope, the deconvolution of its beam or Point Spread Function (PSF) is a crucial task. However, deconvolution presents a classical and…