• Title/Summary/Keyword: EUV filter

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Mass constraint and temperature estimation of eruptive plasma in X-ray

  • Lee, Jin-Yi;Raymond, John C.;Reeves, Katharine K.;Moon, Yong-Jae;Kim, Kap-Sung
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.1
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    • pp.60.2-60.2
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    • 2013
  • We investigate several eruptive hot plasma observations by Hinode/XRT. Their corresponding EUV and/or white light CME features are visible in some events. Using those observations, we determine the mass constraints of eruptive plasma by assuming simplified geometrical structures of the plasma. In some events, their associated prominence eruptions and eruptive plasma were observed in EUV observations as absorption or emission features. The absorption feature provides the lower limit to the cold mass while the emission feature provides the upper limit to the mass of observed eruptive plasma in X-ray and EUV passbands. We compare the mass constraints for each temperature responses and find that the mass in EUV and XRT are smaller in their upper or lower limit than total mass in coronagraph. About half eruptive events in XRT have no corresponding CME, which may be due to failed eruptions or low plasma density. In addition, some events were observed by a few passbands in X-ray, which allows the determination of the eruptive plasma temperature using a filter ratio method. We present the isothermal plasma temperatures by the filter ratio method. These are possibly an average temperature for higher temperature plasma because the XRT is more sensitive in higher temperature.

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DEVELOPMENT OF THE SOLAR EUV TELESCOPE ENGINEERING MODEL FOR A SATELLITE (인공위성 탑재용 극자외선 태양망원경(EUVT) EM 개발)

  • 이선민;장민환;이은석
    • Journal of Astronomy and Space Sciences
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    • v.20 no.4
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    • pp.327-338
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    • 2003
  • The aim of this paper is to describe the results of the study on the extreme-ultra-violet (EUV) solar telescope, which is designed to. a possible satellite mission. Since the EUV band can not be observed on the ground, the observation in EUV should be performed in space using a satellite or a rocket. Design of the Extreme-Ultra-Violet solar Telescope (BUVT) in this study is based on "Designing a small-sized engineering model of solar EUV telescope for a Korean satellite" (Han et al. 2001). Our EUVT design is satisfied with the requirements for a satellite in size and input voltage. The major goal of the study is to confirm if we can detect the specific wavelength (58.4nm to 62.9nm) with the EUVT. We describe re-designing of the EUVT to decrease a shelter ratio. Also we describe the technics in the optic system and the detector, which were used to manufacture the EUVT. We explain the detective program, which is to calculate the amount of the solar radiation, and the image data processing system.ng system.

DESIGNING A SMALL-SIZED ENGINEERING MODEL OF SOLAR EUV TELESCOPE FOR A KOREAN SATELLITE (인공위성 탑재용 소형 극자외선 태양망원경 공학 모형 설계)

  • 한정훈;장민환;김상준
    • Journal of Astronomy and Space Sciences
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    • v.18 no.2
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    • pp.145-152
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    • 2001
  • For the research of solar EUV (extreme ultraviolet) radiation, we have designed a small-sifted engineering model of solar EUV telescope, which is suitable for a Korean satellite. The EUV sole. telescope was designed to observe the sun at $584.3AA$(He I) and $629.7AA$(OV) The optical system is an f/8 Ritchey-Chr rien, and the effective diameter and focal length are 80mm and 640mm, respectively. The He I and 0V filters are loaded in a filter wheel. In the detection part, the MCP (Microchannel Plate) type is Z-stack, and the channel-to-diameter radio is 40:1. MCP and CCD are connected by fiber optic taper. A commercial optical design software is used for the analysis of the optical system design.

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Application of Deep Learning to Solar Data: 2. Generation of Solar UV & EUV images from magnetograms

  • Park, Eunsu;Moon, Yong-Jae;Lee, Harim;Lim, Daye
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.1
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    • pp.81.3-81.3
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    • 2019
  • In this study, we apply conditional Generative Adversarial Network, which is one of the deep learning method, to the image-to-image translation from solar magentograms to solar UV and EUV images. For this, we train a model using pairs of SDO/AIA 9 wavelength UV and EUV images and their corresponding SDO/HMI line-of-sight magnetograms from 2011 to 2017 except August and September each year. We evaluate the model by comparing pairs of SDO/AIA images and corresponding generated ones in August and September. Our results from this study are as follows. First, we successfully generate SDO/AIA like solar UV and EUV images from SDO/HMI magnetograms. Second, our model has pixel-to-pixel correlation coefficients (CC) higher than 0.8 except 171. Third, our model slightly underestimates the pixel values in the view of Relative Error (RE), but the values are quite small. Fourth, considering CC and RE together, 1600 and 1700 photospheric UV line images, which have quite similar structures to the corresponding magnetogram, have the best results compared to other lines. This methodology can be applicable to many scientific fields that use several different filter images.

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