Decoding the Sun: How AI Reads
Автор: Mohammed Talafha
Загружено: 2026-01-24
Просмотров: 6
Описание: This review explores the transformative role of machine learning in the field of solar physics, highlighting how advanced algorithms manage the vast data generated by 400 years of observations. The text details essential neural network architectures, such as convolutional and recurrent models, which are utilized for tasks ranging from image segmentation of solar features to predicting solar flares and geomagnetic activity. It emphasizes the creation of large-scale databases and specialized software libraries like SunPy that facilitate interdisciplinary research. Beyond simple data processing, the sources examine innovative applications like physics-informed neural networks (PINNs) for reconstructing magnetic fields and generative models for translating different types of solar imagery. Ultimately, the work illustrates how the integration of artificial intelligence with traditional physics is accelerating discovery and automating the analysis of complex solar dynamics.
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