activity
20052026
most citedFundamental Physics with the Square Kilometre Array

385 citations · 7k across the 156 of their papers we have counts for

collaborators

153 papers

astro-ph.CO2026

Monitoring the power spectrum of magnetic field fluctuations across the simulated intracluster medium

T. Bartalesi, F. Vazza, S. Ettori +2

Thanks to the current and forthcoming radio interferometers, Faraday rotation measure maps extend out to the outskirts of galaxy clusters. Interpreted through models of the magneti…

astro-ph.CO2026

The topology of the magnetic field in Abell 2255 out to its virial radius. Results from the LOFAR Galaxy Cluster Ultra-Deep Field

A. Botteon, R. J. van Weeren, Y. Hu +14

We present the LOFAR Galaxy Cluster Ultra-Deep Field, in which 336 h of LOFAR observations at 120168 MHz have been collected on the nearby () cluster Abell 2255. This m…

astro-ph.CO2026

The Treble Clef radio phoenix and its old nonthermal filaments

A. Botteon, M. Brienza, K. Rajpurohit +15

By inspecting data from the LOFAR Two-meter Sky Survey (LoTSS), we noticed a peculiar bright and filamentary radio source at low-galactic latitude (). This source,…

astro-ph.CO2026

Galaxy clusters in the LoTSS-DR3: Catalogues and detection pipeline for diffuse radio emission

C. Stuardi, G. Di Gennaro, A. Botteon +19

The third data release of the LOFAR Two-metre Sky Survey provides an unprecedented view of the northern sky at 144 MHz. While compact sources can be efficiently identified with aut…

astro-ph.IM2025

Estimating Flux Densities of Diffuse Cosmological Radio Sources Exploiting Vision Transformers

Nicoletta Sanvitale, Claudio Gheller, Franco Vazza +3

We present TUNA, a Vision-Transformer based network adapted from segmentation to flux regression for faint, diffuse radio emission. Trained on LOFAR-like mock observations derived…

astro-ph.IM2025★ 2 cited

Mapping Diffuse Radio Sources Using TUNA: A Transformer-Based Deep Learning Approach

Nicoletta Sanvitale, Claudio Gheller, Franco Vazza +6

Vision Transformers are used via a customized TransUNet architecture, which is a hybrid model combining Transformers into a U-Net backbone, to achieve precise, automated, and fast…