Radio Astronomy Observations and Technology

Neueste Paper

• Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy

  Elisa Chiarotto, Jingbo Li, P. Chris Broekema, Rob V. van Nieuwpoort · 27. Juli 2026

  Recent Large Language Models (LLMs) can produce and optimize complex code. We investigate the use of LLMs to generate and optimize code for large-scale sciences, focusing on radio astronomy and sustainability. The LOFAR telescope is currently being upgraded, significantly increasing the sky area obs…

• Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

  Ved G. Shah, Nabeel Rehemtulla, Adam A. Miller, Sushant Sharma Chaudhary, Michael W. Coughlin, Antoine Le Calloch, Matthew J. Graham, Joahan Castaneda Jaimes, Theophile Jegou du Laz, Ashish A. Mahabal, Frank J. Masci, Josiah Purdum, Reed Riddle, Jesper Sollerman, Anastasia Wei, Mansi M. Kasliwal · 2. Juli 2026

  Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions for follow-up observations a central challenge in time-domain astronomy. Robust early classification is crucial for making informed decisions, but is…

• Stochastic Expectation Maximization for Robust State-Space Radio Interferometric Imaging

  Nawel Arab, Mohammed Nabil El Korso, Isabelle Vin, Pascal Larzabal · 24. Juni 2026

  State--space models provide a flexible framework for analyzing dynamical systems, yet they often rely on Gaussian assumptions that fail to capture heavy-tailed or outlier-prone measurement noise. We propose a robust estimation scheme for linear state--space models subject to compound-Gaussian noise,…

• Three-dimensional Conditional Diffusion Models for Cosmological 21 cm Lightcone Emulation

  Bin Xia, John H. Wise · 29. Mai 2026

  We investigate conditional diffusion modeling for three-dimensional 21 cm lightcone emulation, focusing on cubes with a sky-plane size of $64\times64$ and a line-of-sight depth up to 1024 cells. Relative to earlier 2D studies, the 3D setting is substantially harder because memory limits enforce very…

• Improving Radio Interferometry Imaging by Explicitly Modeling Cross-Domain Consistency in Reconstruction

  Kai Cheng, Ruoqi Wang, Qiong Luo · 21. April 2026

  Radio astronomy plays a crucial role in understanding the universe, particularly within the realm of non-thermal astrophysics. Images of celestial objects are derived from the signals (called visibility) measured by radio telescopes. Such imaging results, called dirty images, contain artifacts due t…

• FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation

  Bin Zhang, Yabiao Wang, Xiaoyao Xie, Shanping You, Xuhong Yu, Qiuhua Li, Hongwei Li, Shaowen Du, Chenchen Miao, Dengke Zhou, Jianhua Fang, Jiafu Wu, Pei Wang, Di Li · 15. April 2026

  The exponential growth of data from modern radio telescopes presents a significant challenge to traditional single-pulse search algorithms, which are computationally intensive and prone to high false-positive rates due to Radio Frequency Interference (RFI). In this work, we introduce FRTSearch, an e…

• STRADAViT: Towards a Foundational Model for Radio Astronomy through Self-Supervised Transfer

  Andrea DeMarco, Ian Fenech Conti, Hayley Camilleri, Ardiana Bushi, Simone Riggi · 1. April 2026

  Next-generation radio astronomy surveys are delivering millions of resolved sources, but robust and scalable morphology analysis remains difficult across heterogeneous telescopes and imaging pipelines. We present STRADAViT, a self-supervised Vision Transformer continued-pretraining framework for lea…

• Conditional Neural Bayes Ratio Estimation for Experimental Design Optimisation

  S. A. K. Leeney, T. Gessey-Jones, W. J. Handley, E. de Lera Acedo, H. T. J. Bevins, J. L. Tutt · 30. März 2026

  For frontier experiments operating at the edge of detectability, instrument design directly determines the probability of discovery. We introduce Conditional Neural Bayes Ratio Estimation (cNBRE), which extends neural Bayes ratio estimation by conditioning on design parameters, enabling a single tra…

• POLISH'ing the Sky: Wide-Field and High-Dynamic Range Interferometric Image Reconstruction with Application to Strong Lens Discovery

  Zihui Wu, Liam Connor, Samuel McCarty, Katherine L. Bouman · 11. März 2026

  Radio interferometry enables high-resolution imaging of astronomical radio sources by synthesizing a large effective aperture from an array of antennas and solving a deconvolution problem to reconstruct the image. Deep learning has emerged as a promising solution to the imaging problem, reducing com…

• HyperAIRI: a plug-and-play algorithm for precise hyperspectral image reconstruction in radio interferometry

  Chao Tang, Arwa Dabbech, Adrian Jackson, Yves Wiaux · 12. Februar 2026

  The next-generation radio-interferometric (RI) telescopes require imaging algorithms capable of forming high-resolution high-dynamic-range images from large data volumes spanning wide frequency bands. Recently, AIRI, a plug-and-play (PnP) approach taking the forward-backward algorithmic structure (F…

• VVTRec: Radio Interferometric Reconstruction through Visual and Textual Modality Enrichment

  Kai Cheng, Ruoqi Wang, Qiong Luo · 13. Januar 2026

  Radio astronomy is an indispensable discipline for observing distant celestial objects. Measurements of wave signals from radio telescopes, called visibility, need to be transformed into images for astronomical observations. These dirty images blend information from real sources and artifacts. There…

• Polarization based direction of arrival estimation using a radio interferometric array

  Sarod Yatawatta · 23. Dezember 2025

  Direction of arrival (DOA) estimation is mostly performed using specialized arrays that have carefully designed receiver spacing and layouts to match the operating frequency range. In contrast, radio interferometric arrays are designed to optimally sample the Fourier space data for making high quali…

• AI Agent for Source Finding by SoFiA-2 for SKA-SDC2

  Xingchen Zhou, Nan Li, Peng Jia, Yingfeng Liu, Furen Deng, Shuanghao Shu, Ying Li, Liang Cao, Huanyuan Shan, Ayodeji Ibitoye · 2. Dezember 2025

  Source extraction is crucial in analyzing data from next-generation, large-scale sky surveys in radio bands, such as the Square Kilometre Array (SKA). Several source extraction programs, including SoFiA and Aegean, have been developed to address this challenge. However, finding optimal parameter con…

• Exploring the Early Universe with Deep Learning

  Emmanuel de Salis, Massimo De Santis, Davide Piras, Sambit K. Giri, Michele Bianco, Nicolas Cerardi, Philipp Denzel, Merve Selcuk-Simsek, Kelley M. Hess, M. Carmen Toribio, Franz Kirsten, Hatem Ghorbel · 31. Oktober 2025

  Hydrogen is the most abundant element in our Universe. The first generation of stars and galaxies produced photons that ionized hydrogen gas, driving a cosmological event known as the Epoch of Reionization (EoR). The upcoming Square Kilometre Array Observatory (SKAO) will map the distribution of neu…