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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd http://dublincore.org/schemas/xmls/qdc/dcterms.xsd"><dc:language>eng</dc:language><dc:creator>Xiong, Zewei</dc:creator><dc:creator>Wu, Meng-Ru</dc:creator><dc:creator>Abbar, Sajad</dc:creator><dc:creator>Bhattacharyya, Soumya</dc:creator><dc:creator>George, Manu</dc:creator><dc:creator>Lin, Chun-Yu</dc:creator><dc:title>Dataset: Evaluating approximate asymptotic distributions for fast neutrino flavor conversions in a periodic 1D box</dc:title><dc:description>In this data package we include two txt files and two zip files. The file Gaussian.txt contains 4 columns. The first column shows the indices of the file numbers contained in the file Gaussian_100.zip. The second, third, and fourth columns list the corresponding \(I_{\bar\nu}\) , \(F_\nu\) , and \(F_{\bar\nu}\) , respectively. The file Maxent.txt contains 5 columns. The first column shows the indices of the file numbers contained in the file Maxent_100.zip while the second column lists the corresponding indices in the file Gaussian.txt. The third, fourth, and fifth columns list the corresponding \(I_{\bar\nu}\) , \(F_\nu\) , and \(F_{\bar\nu}\) , respectively. Files Gaussian_100 and Maxent_100 give the asymptotic simulated outcomes of fast neutrino flavor conversions with the initial Gaussian and maximum-entropy distributions, respectively. Each data file xxxx.dat lists four columns for \(v_z\) , \(P_{ee}(v_z)\) , \(g_\nu(v_z)\) , and \(g_{\bar\nu}(v_z)\) , respectively. We take 100 \(v_z\) grids for all data.</dc:description><dc:source>doi:10.5281/ZENODO.8167252</dc:source><dc:type>info:eu-repo/semantics/researchdata</dc:type><dc:type>info:eu-repo/semantics/publishedVersion</dc:type><dc:date>2023</dc:date><dc:rights>info:eu-repo/semantics/closedAccess</dc:rights><dc:coverage>DE</dc:coverage><dc:identifier>https://repository.gsi.de/record/354861</dc:identifier><dc:identifier>https://repository.gsi.de/search?p=id:%22GSI-2024-01294%22</dc:identifier><dc:audience>Researchers</dc:audience><dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.5281/ZENODO.8167252</dc:relation><dc:relation>info:eu-repo/grantAgreement/EC//885281</dc:relation></oai_dc:dc>

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