천문학회보 (The Bulletin of The Korean Astronomical Society)

한국천문학회 (The Korean Astronomical Society)
권호 표지

Generation of global coronal field extrapolation from frontside and AI-generated farside magnetograms

  • Jeong, Hyunjin (School of Space Research, Kyung Hee University) ;
  • Moon, Yong-Jae (School of Space Research, Kyung Hee University) ;
  • Park, Eunsu (School of Space Research, Kyung Hee University) ;
  • Lee, Harim (School of Space Research, Kyung Hee University) ;
  • Kim, Taeyoung (School of Space Research, Kyung Hee University)
  • 발행 : 2019.04.10
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초록

Global map of solar surface magnetic field, such as the synoptic map or daily synchronic frame, does not tell us real-time information about the far side of the Sun. A deep-learning technique based on Conditional Generative Adversarial Network (cGAN) is used to generate farside magnetograms from EUVI $304{\AA}$ of STEREO spacecrafts by training SDO spacecraft's data pairs of HMI and AIA $304{\AA}$. Farside(or backside) data of daily synchronic frames are replaced by the Ai-generated magnetograms. The new type of data is used to calculate the Potential Field Source Surface (PFSS) model. We compare the results of the global field with observations as well as those of the conventional method. We will discuss advantage and disadvantage of the new method and future works.

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과제정보

연구 과제번호 : Study on analysis and prediction technique of solar flares

연구 과제 주관 기관 : Institute for Information & communications Technology Promotion(IITP)