Yihua Yan – författare
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3 produkter
3 produkter
1 053 kr
Skickas inom 11-20 vardagar
The Sun and other stars eject large clouds of plasma and magnetic fields on a continual basis. They are accelerated to high speeds and then become capable of producing highly energetic charged particles and disrupting the magnetospheres of planets such as the Earth. This proceeding reflects recent attempts to understand these processes as well as how the magnetic evolution at the base of the corona can cause these events, and how stars are capable of rapidly releasing energy in the form of mass ejections. With contributions by leading scientists, it is a valuable resource for professional astronomers and their graduate students.
936 kr
Skickas inom 11-20 vardagar
Global magnetic fields in planets, in the Sun and other stars, in spiral galaxies and galaxy clusters are believed to be generated and maintained by a hydromagnetic dynamo, a process that converts turbulent kinetic energy into magnetic energy. These dynamo processes operate on drastically different scales, but are associated with common physical mechanisms, involving a complex interaction of rotation, turbulence and instabilities. The goal of IAU Symposium 294 was to discuss the most important results of recent studies of the cosmic dynamo processes, from planets to stars, galaxies, and clusters of galaxies. This volume covers advances in dynamo theories and numerical simulations, links between dynamos and turbulence, the origin of magnetic fields, and current and future observational projects. The proceedings of IAU S294 are an important asset for advanced students and researchers, as a summary of hot topics related to the solar and astrophysical dynamos and magnetic activity.
590 kr
Skickas inom 10-15 vardagar
The volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte solar data. Deep learning has been an invaluable tool exploited to efficiently extract key information from the massive solar observation data, to solve the tasks of data archiving/classification, object detection and recognition.Astronomical study starts with imaging from recorded raw data, followed by image processing, such as image reconstruction, inpainting and generation, to enhance imaging quality. We study deep learning for solar image processing. First, image deconvolution is investigated for synthesis aperture imaging. Second, image inpainting is explored to repair over-saturated solar image due to light intensity beyond threshold of optical lens. Third, image translation among UV/EUV observation of the chromosphere/corona, Ha observation of the chromosphere and magnetogram of the photosphere is realized by using GAN, exhibiting powerful image domain transfer ability among multiple wavebands and different observation devices. It can compensate the lack of observation time or waveband. In addition, time series model, e.g., LSTM, is exploited to forecast solar burst and solar activity indices.This book presents a comprehensive overview of the deep learning applications in solar astronomy. It is suitable for the students and young researchers who are major in astronomy and computer science, especially interdisciplinary research of them.