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Scientific objectives and payload configuration of the Chang'E-7 mission

National Science Review 2024年第2期11卷 285-300页

作者： Chi Wang Yingzhuo Jia Changbin Xue Yangting Lin Jianzhong Liu Xiaohui Fu Lin Xu Yun Huang Yufen Zhao Yigang Xu Rui Gao Yong Wei Yuhua Tang Dengyun Yu Yongliao Zou China Aerospace Science and Technology Corporation State Key Laboratory of space Weather National Space Science Center Chinese Academy of Sciences National space Science Center Chinese Academy of Sciences Institute of Geology and Geophysics Chinese Academy of Sciences Institute of Geochemistry Chinese Academy of Sciences Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment School of Space Science and Physics Institute of Space SciencesShandong University Institute of Drug Discovery Technology Ningbo University State Key Laboratory of Isotope Geochemistry Guangzhou Institute of Geochemistry Chinese Academy of Sciences School of Earth Science and Engineering Sun Yat-sen University Lunar Exploration and space Engineering Center

As the cornerstone mission of the fourth phase of the Chinese Lunar Exploration Program, Chang'E-7(CE-7) was officially approved, and implementation started in 2022, including a main probe and a communication relay satellite. The main probe, consisting of an orbiter, a lander, a rover and a mini-flying probe, is scheduled to be launched in 2026. The lander will land on Shackleton crater's illuminated rim near the lunar south pole, along with the rover and mini-flying probe. The relay satellite(named Queqiao-2) will be launched in February 2024 as an independent mission to support relay communication during scientific exploration undertaken by Chang'E-4, the upcoming Chang'E-6 in 2024 and subsequent lunar missions.The CE-7 mission is mainly aimed at scientific and resource exploration of the lunar south pole. We present CE-7's scientific objectives, the scientific payloads configuration and the main functions for each scientific payload with its key technical specifications.

关键词： Chang’ E-7 scientific objectives scientific payloads

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Using restored two-dimensional X-ray images to reconstruct the three-dimensional magnetopause

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Earth and Planetary Physics 2024年第1期8卷 133-154页

作者： RongCong Wang JiaQi Wang DaLin Li TianRan Sun XiaoDong Peng YiHong Guo National space Science Center Chinese Academy of SciencesBeijing 100190China University of Chinese academy of sciences Beijing100049China Aerospace Information research Institute Chinese Academy of SciencesBeijing 100094China

Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)aims to capture two-dimensional(2-D)images of the Earth’s magnetosheath by using soft X-ray imaging.However,the observed 2-D images are affected by many noise factors,destroying the contained information,which is not conducive to the subsequent reconstruction of the three-dimensional(3-D)structure of the magnetopause.The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models.This makes it difficult to establish the mapping relationship between SXIsimulated observation images and target images by using mathematical models.We propose an image restoration algorithm for SXIsimulated observation images that can recover large-scale structure information on the magnetosphere.The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image,whose mapping relationship with the target image is established by the patch estimator.The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator.Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task,according to the peak signal-to-noise ratio and structural similarity.The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques,significantly improving the reconstruction results.Hence,the proposed te

关键词： Solar wind Magnetosphere Ionosphere Link Explorer(SMILE) soft X-ray imager magnetopause image restoration

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Effect of Y substitution on the microstructure,magneto-optical,and thermal properties of(Tb_(1−x)Y_(x))_(3)Al_(5)O_(12)transparent ceramics

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Journal of Advanced Ceramics 2024年第4期13卷 529-538页

作者： Lixuan Zhang Dianjun Hu Xiao Li Ziyu Liu Chen Hu Lexiang Wu Tingsong Li Dariusz Hreniak Jiang Li Transparent Ceramics research Center Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 201899China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Ganjiang Innovation academy Chinese Academy of SciencesGanzhou 341000China Institute of Low Temperature and Structure research Polish Academy of SciencesWroclaw 50-422Poland

Faraday isolators can prevent the front-end system from disturbance and damage caused by a back-reflected beam,so they are important elements in laser systems.As magneto-optical materials are the most important component in Faraday isolators,the studies on magneto-optical materials have attracted much attention these years.Tb_(3)Al_(5)O_(12)(TAG)ceramics are considered to be one of the most promising magneto-optical materials for visible to near-infrared wavelength band application because of their outstanding comprehensive magneto-optical performance.However,the optical quality of TAG ceramics needs further optimization to meet the application requirements.In this work,high optical quality(Tb_(1−x)Y_(x))_(3)Al_(5)O_(12)(x=0,0.05,0.1,0.2,and 0.3)magneto-optical ceramics were fabricated successfully by solid-state reaction sintering combined with hot isostatic pressing(HIP)post-treatment.All the ceramics obtained showed a single garnet phase for different values of x in the range studied.The addition of Y2O3 was found to suppress the secondary phase and improve optical quality significantly.The ceramic samples obtained had clear grain boundaries and possessed the in-line transmittance values of 82.9%at 1064 nm and 82.2%at 633 nm,respectively.The Verdet constants of(Tb_(1−x)Y_(x))_(3)Al_(5)O_(12)ceramics with x=0,0.05,0.1,0.2,and 0.3 were−188.1,−175.4,−168.5,−143.0,and−119.9 rad/(T·m),respectively.The thermal conductivity of TAG ceramics was found to be 5.23 W/(m·K)at 25℃,and when 20%Y was substituted in place of Tb,the thermal conductivity decreased by only 9.4%.

关键词： (Tb_(1−x)Y_(x))_(3)Al_(5)O_(12)ceramics magneto-optical materials optical quality thermal properties

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Analysis of the joint detection capability of the SMILE satellite and EISCAT-3D radar

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Earth and Planetary Physics 2024年第1期8卷 299-306页

作者： JiaoJiao Zhang TianRan Sun XiZheng Yu DaLin Li Hang Li JiaQi Guo ZongHua Ding Tao Chen Jian Wu Chi Wang State Key Laboratory of space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Key Laboratory of Solar Activity and space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese academy of sciences Beijing 101408China Key Laboratory of Electronics and Information Technology for space Systems Chinese Academy of SciencesBeijing 100190China China research Institute of Radio-wave Propagation Qingdao 266075China

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.

关键词： Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite European Incoherent Scatter sciences Association(EISCAT)-3D radar joint detection

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MTCR-CR Routing Strategy for Connection-Oriented Routing over Satellite Networks

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China Communications 2024年第5期21卷 280-296页

作者： Li Changhao Sun Xue Yan Lei Cao Suzhi The University of Chinese academy of sciences Beijing 100094China Key Laboratory of space Utilization Chinese Academy of SciencesBeijing 100094China Technology and Engineering Center for space Utilization Chinese Academy of SciencesBeijing 100094China

The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.

关键词： ISL routing stability satellite networks satellite routing dynamic strategy

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Lossless Compression Method for the Magnetic and Helioseismic Imager(MHI)Payload

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research in Astronomy and Astrophysics 2024年第4期24卷 214-221页

作者： Li-Yue Tong Jia-Ben Lin Yuan-Yong Deng Kai-Fan Ji Jun-Feng Hou Quan Wang Xiao Yang National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Key Laboratory of Solar Activity and space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China School of Astronomy and space Science University of Chinese Academy of SciencesBeijing 100049China Yunnan Observatories Chinese Academy of SciencesKunming 650216China

The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.

关键词： methods:data analysis techniques:image processing Sun:magnetic fields Sun:photosphere

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Large-scale spatial data visualization method based on augmented reality

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虚拟现实与智能硬件（中英文） 2024年第2期6卷 132-147页

作者： Xiaoning QIAO Wenming XIE Xiaodong PENG Guangyun LI Dalin LI Yingyi GUO Jingyi REN Key Laboratory of Electronics and Information Technology for space Systems National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese academy of sciences Beijing 100049China Ordnance Science and research academy of China Beijing 100089China

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

关键词： Large-scale spatial data analysis Visual analysis technology Augmented reality 3D reconstruction space environment

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Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

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Advances in Atmospheric sciences 2024年第7期41卷 1313-1325页

作者： Tingyu WANG Ping HUANG Xianke YANG Center for Monsoon System research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National space Science Center Chinese Academy of SciencesBeijing 100190China State Key Laboratory of space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China College of Plant Science and Technology Huazhong Agricultural UniversityWuhan 430070China

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

关键词： ENSO attribution deep learning ENSO prediction extreme El Niño

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Automatic Generation of Artificial space Weather Forecast Product Based on Sequence-to-sequence Model

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空间科学学报 2024年第1期44卷 80-94页

作者：罗冠霆 ZOU Yenan CAI Yanxia State Key Laboratory of space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190 University of Chinese academy of sciences Beijing 100049 Key Laboratory of Science and Technology on Environment space Situation Awareness Chinese Academy of SciencesBeijing 100190

Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.

关键词： space weather Deep learning Data-to-text Natural language generation

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Two methods for separating the magnetospheric solar wind charge exchange soft X-ray emission from the diffuse X-ray background

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Earth and Planetary Physics 2024年第1期8卷 119-132页

作者： YingJie Zhang TianRan Sun JenniferACarter WenHao Liu Steve Sembay ShuiNai Zhang Li Ji Chi Wang State Key Laboratory of space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China College of Earth and Planetary sciences The University of Chinese Academy of SciencesBeijing 100190China School of Physics and Astronomy The University of LeicesterLeicesterUK Purple Mountain Observatory Chinese Academy of SciencesNanjing 210008China

Solar wind charge exchange(SWCX)is the process of solar wind high-valence ions exchanging charges with neutral components and generating soft X-rays.Recently,detecting the SWCX emission from the magnetosphere is proposed as a new technique to study the magnetosphere using panoramic soft X-ray imaging.To better prepare for the data analysis of upcoming magnetospheric soft X-ray imaging missions,this paper compares the magnetospheric SWCX emission obtained by two methods in an XMM-Newton observation,during which the solar wind changed dramatically.The two methods differ in the data used to fit the diffuse X-ray background(DXB)parameters in spectral analysis.The method adding data from the ROSAT All-Sky Survey(RASS)is called the RASS method.The method using the quiet observation data is called the Quiet method,where quiet observations usually refer to observations made by the same satellite with the same target but under weaker solar wind conditions.Results show that the spectral compositions of magnetospheric SWCX emission obtained by the two methods are very similar,and the changes in intensity over time are highly consistent,although the intensity obtained by the RASS method is about 2.68±0.56 keV cm^(-2)s^(-1)sr^(-1)higher than that obtained by the Quiet method.Since the DXB intensity obtained by the RASS method is about 2.84±0.74 keV cm^(-2)s^(-1)sr^(-1)lower than that obtained by the Quiet method,and the linear correlation coefficient between the difference of SWCX and DXB obtained by the two methods in diffe rent energy band is close to-1,the diffe rences in magnetospheric SWCX can be fully attributed to the diffe rences in the fitted DXB.The difference between the two methods is most significant when the energy is less than 0.7 keV,which is also the main energy band of SWCX emission.In addition,the difference between the two methods is not related to the SWCX intensity and,to some extent,to solar wind conditions,because SWCX intensity typically va ries with the solar wind.In summary,both methods are robust a

关键词： solar wind charge exchange(SWCX) ROSAT All-Sky Survey(RASS) soft X-ray X-ray imaging magnetosphere

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