Objective
To understand the history of the chondritic asteroid Ryugu and whether it had a role in delivering volatiles and organic material to early Earth, SDR will constrain the mineral and geochemical variability of sediment samples from Ryugu on a grain and sub-grain scale. Because Ryugu is a rubble-pile asteroid made of re-accreted pieces of the parent body/bodies, near-surface sediment collected by the Hayabusa2 mission represents many depths within the interior of the parent. However, current analyses of collected reflectance spectra are done at the bulk sample scale which can average over interesting features to determine the major components. As individual grains are prepared to be sent out for proposed science, each grain is being documented from multiple viewing angles using the MicrOmega hyperspectral imager (0.99-3.65 micrometers) developed at IAS. This has created an enormous, rich dataset of ~20 hyperspectral images for each of 350 grains analyzed so far, and this dataset will continue to grow over the coming months. By conducting novel statistical analyses of this dataset of >7000 high-resolution image cubes (22 micrometers/pixel), I will identify co-occurring mineral phases, minor phases, and variation in organic phases that have implications for the aqueous alteration conditions within Ryugu and its parent body. Statistical analyses will include: principal component analysis, k-means clustering, distinctiveness measures, pixel-to-pixel correlation, edge detection, and network centrality. My experience publishing on statistical analyses of existing, noisy datasets has prepared me to extract meaningful information from this large, complicated dataset. This work will culminate in an updated model of formation and alteration on Ryugu’s parent body which relies on the types and position of minerals to infer alteration gradients and constrain the nature, number, and temperature of aqueous alteration events.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesphysical sciencesastronomyplanetary sciencesasteroids
- humanitieshistory and archaeologyhistory
- agricultural sciencesagriculture, forestry, and fisheriesagriculturegrains and oilseeds
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
91190 Gif-Sur-Yvette
France