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Machine Learning Approaches in Lunar Mantle Heterogeneity Investigations
  • Kim Cone,
  • Richard Palin,
  • Kamini Singha
Kim Cone
Colorado School of Mines

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Richard Palin
University of Oxford
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Kamini Singha
Colorado School of Mines
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Lunar mare basalts are the products of their corresponding parent magma compositions, sourced from the lunar upper mantle. The lunar mantle has been repeatedly modeled through numeric simulations to reflect lunar magma ocean (LMO) crystallization, resulting in an early-stage anorthositic crust and immediately underlying, late-stage, KREEP-rich and ilmenite-rich layer. This negatively buoyant layer is expected to have induced mixing with the underlying mantle, potentially to the core-mantle boundary. The lunar mare basalts, in this context, reflect mantle sources that are variably mixed between pristine mantle compositions and the dense ilmenite-rich layer. In order to constrain the geometry of lunar mantle heterogeneity, we simultaneously examined multiple mare basalt characteristics to extract significant multivariate patterns that might lend insight into the nature of this mixing-induced heterogeneity. Using two fundamental machine learning approaches and a newly compiled database of Apollo basalt characteristics (ApolloBasaltDB), we conducted a preliminary investigation, holding the assumptions that 1) mare basalts are assumed to retain the majority of their original characteristics at the time of extrusion: texture, isotopic age, major element composition, mineral mode, and geographic occurrence; 2) negligible basalt alteration occurred due to the lack of an atmosphere; and 3) impact gardening did not have significant bearing on final geographic location of basalt samples based on our nearside spatial partitions. The results of cluster and principal component analyses over changing spatial basalt groupings suggest that lunar nearside changes in major element concentrations and mineral modes vary spatially. Al2O3 concentrations increase in diversity within the Procellarum KREEP Terrane (PKT) compared to older regions immediately exterior to the eastern PKT, while a general nearside trend appears to suggest that ilmenite (TiO2) diversity comes at the expense of plagioclase (Al2O3) diversity. Cluster analysis suggests PKT perimeter rifting may have tapped into increasingly Ti-rich sources as rifting proceeded SE to NW. By establishing such trends over varying spatial scales through multivariate processing, the changing strengths of these surface correlative patterns may indicate the changing conditions (including temporal) of the immediately underlying mantle at the time of extrusion.