Automatic detection of solar radio bursts in NenuFAR observations

• DOI: 10.48550/arxiv.2401.04469
• Publication Date: 2024-01-01
• Authors: P. Murphy; Baptiste Cecconi; Carine Briand; Stéphane Aicardi
• Keywords: Solar radio; Radio spectrum

Solar radio bursts are some of the brightest emissions at frequencies in solar system. The emission mechanisms that generate these offer a remote insight into physical processes coronal plasma, while fine spectral features hint its underlying turbulent nature. During noise storms many hundreds can occur over course few hours. Identifying and classifying is often done manually although number automatic algorithms have been produced for this purpose. use machine learning image segmentation classification well established has shown promising results case identifying Type II III bursts. Here we present convolutional neural network applied to dynamic spectra NenuFAR observations. We highlight initial success segmenting from background outline steps necessary burst classification.