S. N. Zhang, M. Feroci, A. Santangelo, Y. W. Dong, H. Feng, F. J. Lu, K. Nandra, Z. S. Wang, S. Zhang, E. Bozzo, S. Brandt, A. De Rosa, L. J. Gou, M. Hernanz, M. van der Klis, X. D. Li, Y. Liu, P. Orleanski, G. Pareschi, M. Pohl, J. Poutanen, J. L. Qu, S. Schanne, L. Stella, P. Uttley, A. Watts, R. Xu, W. F. Yu, J. J. M. in ’t Zand, S. Zane, L. Alvarez, L. Amati, L. Baldini, C. Bambi, S. Basso, S. Bhattacharyya, R. Bellazzini, T. Belloni, P. Bellutti, S. Bianchi, A. Brez, M. Bursa, V. Burwitz, C. Budtz-Jørgensen, I. Caiazzo, R. Campana, X. L. Cao, P. Casella, C. Y. Chen, L. Chen, T. Chen, Y. Chen, M. Civitani, F. Coti Zelati, W. Cui, Z. G. Dai, E. Del Monte, D. de Martino, S. Di Cosimo, S. Diebold, M. Dovciak, I. Donnarumma, V. Doroshenko, P. Esposito, Y. Evangelista, Y. Favre, P. Friedrich, F. Fuschino, J. Galvez, Z. Gao, M. Ge, O. Gevin, D. Goetz, D. Han, J. Heyl, J. Horak, W. Hu, F. Huang, Q. S. Huang, R. Hudec, D. Huppenkothen, G. L. Israel, A. Ingram, V. Karas, D. Karelin, P. Jenke, L. Ji, S. Korpela, D. Kunneriath, C. Labanti, G. Li, X. Li, Z. S. Li, E. W. Liang, O. Limousin, L. Lin, Z. X. Ling, H. B. Liu, H. Liu, Z. Liu, B. Lu, N. Lund, D. Lai, B. Luo, T. Luo, B. Ma, S. Mahmoodifar, M. Marisaldi, A. Martindale, N. Meidinger, Y. P. Men, M. Michalska, R. Mignani, M. Minuti, S. Motta, F. Muleri, J. Neilsen, M. Orlandini, A. T. Pan, A. Patruno, E. Perinati, A. Picciotto, C. Piemonte, M. Pinchera, A. Rachevski, M. Rapisarda, N. Rea, E. M. Rossi, A. Rubini, G. Sala, X. W. Shu, C. Sgro, Z. X. Shen, P. Soffitta, L. Song, G. Spandre, G. Stratta, T. Strohmayer, L. Sun, J. Svoboda, G. Tagliaferri, C. Tenzer, T. Hong, R. Taverna, G. Torok, R. Turolla, S. Vacchi, J. Wang, D. Walton, K. Wang, J. F. Wang, R. J. Wang, Y. Wang, S. Weng, J. Wilms, B. Winter, X. Wu, S. L. Xiong, Y. Xu, Y. Xue, Z. Yan, S. Yang, X. Yang, Y. J. Yang, F. Yuan, W. Yuan, Y. F. Yuan, G. Zampa, N. Zampa, A. Zdziarski, C. Zhang, C. L. Zhang, L. Zhang, X. Zhang, Z. Zhang, W. Zhang, S. Zheng, P. Zhou, X. Zhou
eXTP is a science mission designed to study the state of matter under extreme conditions of density, gravity and magnetism. Primary goals are the determination of the equation of state of matter at supra-nuclear density, the measurement of QED effects in highly magnetized star, and the study of accretion in the strong-field regime of gravity. Primary targets include isolated and binary neutron stars, strong magnetic field systems like magnetars, and stellar-mass and supermassive black holes. The mission carries a unique and unprecedented suite of state-of-the-art scientific instruments enabling for the first time ever the simultaneous spectral-timing-polarimetry studies of cosmic sources in the energy range from 0.5-30 keV (and beyond). Key elements of the payload are: the Spectroscopic Focusing Array (SFA) - a set of 11 X-ray optics for a total effective area of ∼0.9 m2 and 0.6 m2 at 2 keV and 6 keV respectively, equipped with Silicon Drift Detectors offering <180 eV spectral resolution; the Large Area Detector (LAD) - a deployable set of 640 Silicon Drift Detectors, for a total effective area of ∼3.4 m2, between 6 and 10 keV, and spectral resolution better than 250 eV; the Polarimetry Focusing Array (PFA) – a set of 2 X-ray telescope, for a total effective area of 250 cm2 at 2 keV, equipped with imaging gas pixel photoelectric polarimeters; the Wide Field Monitor (WFM) - a set of 3 coded mask wide field units, equipped with position-sensitive Silicon Drift Detectors, each covering a 90 degrees x 90 degrees field of view. The eXTP international consortium includes major institutions of the Chinese Academy of Sciences and Universities in China, as well as major institutions in several European countries and the United States. The predecessor of eXTP, the XTP mission concept, has been selected and funded as one of the so-called background missions in the Strategic Priority Space Science Program of the Chinese Academy of Sciences since 2011. The strong European participation has significantly enhanced the scientific capabilities of eXTP. The planned launch date of the mission is earlier than 2025.
Astronomical data analysis depends on the accumulation of data, including integrity of data in observing location, time, and diversity of data. We are now developing a reorganization project of solar physics history data of China. There are 90 years, 44 kinds of solar observing data in China. In the project, we will finish imagination, digitalization and standardization of these data. This article introduces the project framework, data, data processing, and how to share.
KEYWORDS: Magnetism, Space telescopes, Autoregressive models, Solar radiation models, Telescopes, Data modeling, Magnetism, Solar processes, Data centers, Astronomy, Observatories
The Sun is the source of space weather. The characteristics and evolution of the solar active-region magnetic field closely relate to violent solar eruptions such as flares and coronal mass ejections. The Solar Magnetic Field Telescope in Huairou Solar Observing Station has accumulated numerous vector magnetogram data of solar photospheric active regions (AR) covering nearly 30 years. Utilizing these precious historical data to establish statistical prediction models for solar eruptive events, not only can provide a reference for the timely adjustment of observation mode to specific active regions, but also can offer valuable reference to the monitoring and forecasting departments of solar and space weather. In this part of work, we focus on the Yes/No and occurrence time predictions for AR-related solar flares, and the predictions independently rely on the vector magnetic-filed observation of the solar surface.
KEYWORDS: Magnetism, Solar processes, Autoregressive models, Image processing, Solar radiation models, Solar energy, Data processing, Curium, Astronomy, Spatial resolution
Intense solar active events have made significant impacts on the modern high technology system and living environment
of human being, therefore solar activities forecast and space weather forecast are getting more and more attention.
Meanwhile, data volume acquisitioned by solar monitor facility is growing larger and larger due to the requirement of
multiple dimensions observation and high temporal and spatial resolution. As staffs of a solar monitor data producer, we
are encouraged to adopt new techniques and methods to provide valuable information to solar activities forecast
organization and the other related users, and provide convenient products and tools to the users. In the previous paper “A
complete solar eruption activities processing tool with robotization and real time (I)”, we presented a fully automatic and
real time detecting architecture for different solar erupt activities. In this paper, we present new components of new data
sets in the architecture design, latest progresses on automatic recognition of solar flare, filament and magnetic field, and
a newly introduced method with which solar photospheric magnetic nonpotentiality parameters are processed in real
time, then its result directly can be used in solar active forecast.
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