Pluto surface composition from spectral model inversion with metaheuristics

Leila R Gabasova (1) , B Schmitt (1) , Nikola K Blanchard (2) , W.M. Grundy (3) , C. B. Olkin (4) , J.R. R Spencer (4) , L.A. Young (4) , K. Ennico (5) , H.A. Weaverc (6) , S.A. Stern (4)

1 IPAG - Institut de Planétologie et d'Astrophysique de Grenoble
2 LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
3 Lowell Observatory [Flagstaff]
4 SwRI - Southwest Research Institute [Boulder]
5 ARC - NASA Ames Research Center
6 APL - Johns Hopkins University Applied Physics Laboratory [Laurel, MD]

The New Horizons mission has returned hyperspectral data for Pluto's surface consisting of complex, not directly modelisable spectra. A radiative transfer model that accurately represents the complexity of the putative surface structure and mix of components poses a high-dimensional inverse problem, with 50-60 independent variables. We develop an efficient resolution method using progressive metaheuristics, and present the most accurate quantitative data on Pluto's surface composition to date.

Mots clés: Pluto; infrared spectra; hyperspectral observations; surface; ices; data inversion

Domaines: Planétologie et astrophysique de la terre [astro-ph.EP]; Mathématiques [math]

Leila R Gabasova, B Schmitt, Nikola K Blanchard, W.M. Grundy, C. B. Olkin, et al.. Pluto surface composition from spectral model inversion with metaheuristics. EPSC-DPS Joint Meeting 2019, Sep 2019, Geneve, Switzerland. ⟨hal-03099265⟩