collaborators

8 papers

astro-ph.IM2026

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)…

astro-ph.IM2026

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…

astro-ph.HE2026

FAST Polarization Catalog of FRB 20240114A

Tian-Cong Wang, Jun-Shuo Zhang, Xiao-Hui Liu +60

Polarization measurements of fast radio bursts (FRBs) probe the magnetized plasma surrounding their central engines. FRB~20240114A is an exceptionally active repeating source, with…

astro-ph.GA2026

SwinYNet: A Transformer-based Multi-Task Model for Accurate and Efficient FRB Search

Yunchuan Chen, Shulei Ni, Chan Li +11

In this study, we present a transformer-based multi-task model for Fast Radio Burst (FRB) detection, signal segmentation, and parameter estimation directly from time-frequency data…

astro-ph.GA2026

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…

astro-ph.IM2025

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…