According to a recent press release, “A NASA Frontier Development Lab (FDL) team has shown that by using deep learning, it is possible to virtually monitor the Sun’s extreme ultraviolet (EUV) irradiance, which is a key driver of space weather. The Sun is vital for survival, but solar flares, which typically occur a few times a year, have the potential to cause severe disruptions in space and on Earth. These disruptions can impact spacecraft, satellites and even systems here on Earth, including GPS navigation, radio communications and the power grid. Deep learning can help get more value out of our current ability to monitor the Sun by providing virtual instruments to supplement physical devices. This research will be published in Science Advances on October 2, 2019 (‘A deep learning virtual instrument for monitoring solar extreme ultraviolet spectral irradiance’).”
FDL team member and co-author Alexander Szenicer said, “Our research shows how a deep neural network can be trained to mimic an instrument on the Solar Dynamics Observatory (SDO)… By inferring what ultraviolet radiation levels that sensor would have detected based on what the other instruments on SDO are observing at any given time, we demonstrate it is possible to increase scientific productivity of NASA missions and to increase our capability to monitor solar sources of space weather.”
The release adds, “FDL is a partnership between NASA Ames Research Center, the SETI Institute and private sector and space agency partners including Google Cloud, Intel AI, IBM, Kx Lockheed Martin, Luxembourg Space Agency, NVIDIA, Canadian Space Agency, HPE and Element AI. During an 8-week summer research accelerator, interdisciplinary teams comprised of early-career researchers in AI and natural science domains work together to apply AI and machine learning to address important challenge questions. The challenge question behind this research was to develop an AI model using SDO images to predict solar spectral irradiance.”
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