3 citations · 3 across the 5 of their papers we have counts for
5 papers
The ALMA-QUARKS survey: Investigating Thermal Feedback of Massive Protostars in Hot Molecular Cores
Dezhao Meng, Tie Liu, Jarken Esimbek +33
We identify a sample of 83 spatially resolved hot molecular cores (HMCs) in the QUARKS survey, aiming at investigating thermal feedback from massive stars. Using CHCN\,(12--11)…
Spectuner-D1: Spectral Line Fitting of Interstellar Molecules Using Deep Reinforcement Learning
Yisheng Qiu, Tianwei Zhang, Tie Liu +6
Spectral lines from interstellar molecules provide crucial insights into the physical and chemical conditions of the interstellar medium. Traditional spectral line analysis relies…
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…
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…
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…