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    <identifier>10.57760/sciencedb.o00009.00106</identifier>
    <datestamp>2022-08-05T23:57:13Z</datestamp>
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  <dc:date>2022-08-05</dc:date>
  <dc:title>3D Earth Magnetospheric X-ray Emissivity Dataset Simulated by 3D PPMLR-MHD Model and Reconstructed by CTA Method (Beijing)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.o00009.00106</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Dataset SpecificationThe Data folder contains four subfolders (Checkpoint, Completion, MHD and Results) and an instruction file called Readme.txt.Below I will explain the meaning of the data contained in each sub-file.MHD folder:It contains two subfolders MHD_Ori and MHD_proj.	MHD_Ori subfolder: There are 24 3D magnetospheric X-ray emissivity output simulated by PPMLR-MHD 3D magnetosphere model under different solar wind conditions.	MHD_proj subfolder: Here is the CBCT integral projection data for the corresponding data in the above MHD_Ori subfolder.Checkpoint folder:It contains two .pth files.	netD_epoch_30000.pth: The parameter configuration data file of the discriminator D after the training is saved under the pytorch framework.	netG_epoch_30000.pth: The parameter configuration data file of generator G after training is saved under the pytorch framework.The 3D GAN can be run by loading the parameters contained in the above two files。Completion folder:It contains 8 subfolders (T1-T8):	T1(It contains 1 subfolder and 24 copies of data):		fixse_noise: There are 24 input data of generator G here, and the data size is 1&amp;times;512. By entering these data into the COPN in this article, the 24 best matching projection output under the T1 folder can be obtained.		24 mat data files:&amp;nbsp;24 best matching projection completion output, and the array size is 64&amp;times;64&amp;times;64.		...		...		...	T2-T8: The data composition under the T2-T8 folder is the same as the T1 folder.Results folder:	It contains 8 subfolders (T1-T8):		T1(It contains four subfolders, ASD_POCS, loss_ASD_POCS, FDK and loss_FDK):			ASD_POCS: It represents the Data 5 (ASD-POCS + 3D GAN) mentioned in Section 3.3 of the article, a total of 24 pieces of data, and the data size is 81&amp;times;81&amp;times;81.			loss_ASD_POCS: It represents the Data 7 ( Limited PPMLR-MHD + ASD-POCS) mentioned in Section 3.3 of the article, a total of 24 pieces of data, and the data size is 81&amp;times;81&amp;times;81.&amp;nbsp;			FDK：It represents the Data 4 (FDK + 3D GAN) mentioned in Section 3.3 of the article, a total of 24 pieces of data, and the data size is 81&amp;times;81&amp;times;81.			loss_FDK： It represents the Data 6 (Limited MHD+FDK) mentioned in Section 3.3 of the article, a total of 24 pieces of data, and the data size is 81&amp;times;81&amp;times;81.		T2-T8: The data composition under the T2-T8 folder is the same as the T1 folder.This dataset can be used for related research on reconstruction of the Earth's 3D magnetospheric structure using CT methods.</dc:description>
  <dc:subject>3D magnetospheric X-ray emissivity output;  PPMLR-MHD 3D magnetosphere model; 3D GANs model; CTA Method</dc:subject>
  <dc:creator>R.C Wang</dc:creator>
  <dc:creator>Dalin. Li</dc:creator>
  <dc:creator>Tianran. Sun</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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