2 citations · 2 across the 6 of their papers we have counts for
8 papers
First results from PADRE/MeDDEA: X-rays from a flare and its CME
Muriel Zoë Stiefel, Säm Krucker, Olivier Limousin +22
The MeDDEA hard X-ray spectrometer onboard NASAs PADRE CubeSat operates four flight-spare detectors from the Solar Orbiter/STIX instrument. This paper aims to evaluate the accuracy…
Electric Potential Patterns Forecasting in the Southern Hemisphere with Deep Learning Techniques
Francesco Pio Ramunno, Simone Mestici, Igino Coco +5
Space weather disturbances driven by the solar wind can degrade satellite navigation, disrupt radio communications, and threaten power infrastructure, making accurate forecasting o…
Automated Solar Radio Burst Detection Using Deep Learning on Augmented e-Callisto Data
Vincenzo Timmel, André Csillaghy, Christian Monstein
Solar radio bursts are signatures of energetic events associated with solar flares and coronal mass ejections and can interfere with terrestrial and space-based communication syste…
Karabo: A versatile SKA Observation Simulation Framework
Rohit Sharma, Simon Felix, Luis Fernando Machado Poletti Valle +12
Karabo is a versatile Python-based software framework simplifying research with radio astronomy data. It bundles existing software packages into a coherent whole to improve the eas…
Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model Approach
Francesco Pio Ramunno, Paolo Massa, Vitaliy Kinakh +3
The spatial properties of the solar magnetic field are crucial to decoding the physical processes in the solar interior and their interplanetary effects. However, observations from…
A machine learning approach for computing solar flare locations in X-rays on-board Solar Orbiter/STIX
Paolo Massa, Simon Felix, László István Etesi +7
The Spectrometer/Telescope for Imaging X-rays (STIX) on-board the ESA Solar Orbiter mission retrieves the coordinates of solar flare locations by means of a specific sub-collimator…
Magnetogram-to-Magnetogram: Generative Forecasting of Solar Evolution
Francesco Pio Ramunno, Hyun-Jin Jeong, Stefan Hackstein +3
Investigating the solar magnetic field is crucial to understand the physical processes in the solar interior as well as their effects on the interplanetary environment. We introduc…
Solar synthetic imaging: Introducing denoising diffusion probabilistic models on SDO/AIA data
Francesco P. Ramunno, S. Hackstein, V. Kinakh +4
Given the rarity of significant solar flares compared to smaller ones, training effective machine learning models for solar activity forecasting is challenging due to insufficient…