From the 2 of 10 linked papers with an AI index.
10 papers
Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks
Ashutosh Kumar Mishra, Emma Tolley, Nicolas Cerardi
The paper introduces a physics‑informed generative U‑Net that can evolve fuzzy dark matter fields and perform super‑resolution of simulations while enforcing the Schrödinger‑Poisso…
Multi-branch classification of diffuse cluster radio emission
Markus Bredberg, Emma Tolley
The paper investigates machine‑learning methods, specifically scattering‑transform encoders and squeeze‑excitation attention in multi‑branch neural networks, to improve detection o…
Foreground Characterization and Mitigation in the Observations of the CD/EoR with the SKA
Philip Bull, Jacob Burba, Emilio Ceccotti +20
The Square Kilometre Array (SKA), with its unprecedented sensitivity, frequency coverage, and large collecting area, is poised to revolutionize our understanding of the Cosmic Dawn…
A Guided Unconditional Diffusion Model to Synthesize and Inpaint Radio Galaxies from FIRST, MGCLS and Radio Zoo
Rémi Poitevineau, Emma Tolley, Verlon Etsebeth
We present a masked-guided approach for a denoising diffusion probabilistic model (DDPM) trained to generate and inpaint realistic radio galaxy images. The inpainting capability is…
Forecasting the occupancy of satellite megaconstellations in SKA observations
Nicolas Cerardi, Emma Tolley, Federico di Vruno
The Square Kilometre Array (SKA) is expected to start science operations in 2030 and by that time there could be up to 10 artificial satellites in Earth's orbit, comprising an…
A targeted machine learning approach for detecting diffuse radio emission with Astronomaly: Protege
Verlon Etsebeth, Michelle Lochner, Konstantinos Kolokythas +2
Diffuse radio emission in galaxy clusters, such as radio halos, relics, and mini halos, is a key tracer of non-thermal processes, turbulence, and magnetic fields within the intra-c…