71 citations · 106 across the 14 of their papers we have counts for
5 papers · 1 filter
Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization
Anshuman Acharya, Michele Bianco, Daniela Breitman +18
When operational, the SKA will generate unprecedented amounts of data and provide exquisite sensitivity for 21 cm tomography of Cosmic Dawn (CD) and the Epoch of Reionization (EoR)…
RAYTHEIA: A high-performance ray-tracing algorithm for three-dimensional direction-dependent equations in astronomical simulations
Zhengping Zhu, Thomas G. Bisbas, Xuefei Tang +3
We present RAYTHEIA, a high-performance reverse ray-tracing algorithm designed to efficiently solve three-dimensional direction-dependent equations in astronomical simulations. The…
FALCO: a Foundation model of Astronomical Light Curves for time dOmain astronomy
Xiaoxiong Zuo, Yihan Tao, Yang Huang +13
Time-domain surveys have advanced astronomical research by revealing diverse variable phenomena, from stellar flares to transient events. The scale and complexity of survey data, a…
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…
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…