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From the 1 of 8 linked papers with an AI index.

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8 papers

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

The paper presents ultra‑deep LOFAR radio images of the galaxy cluster Abell 2255 and uses the synchrotron intensity gradient method to map the orientation of its magnetic field fr…

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.CO2025

On the interpretation of XRISM X-ray measurements of turbulence in the intracluster medium: a comparison with cosmological simulations

F. Vazza, G. Brunetti

We investigate whether the properties of turbulent gas motions recently measured via X-ray spectroscopy in the Coma cluster of galaxies by XRISM are in tension with the turbulent p…

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

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…