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Activity Number: 83
Type: Invited
Date/Time: Sunday, July 30, 2017 : 8:30 PM to 10:30 PM
Sponsor: Astrostatistics Special Interest Group
Abstract #324148
Title: Computer Model Calibration to Enable Disaggregation of Large Parameter Spaces, with Application to Mars Rover Data
Author(s): David Craig Stenning* and Working Group 1 ASTRO Program
Companies: SAMSI/Duke University and SAMSI
Keywords: emulation ; calibration ; uncertainty quantification ; Bayesian methods ; MCMC ; astrostatistics
Abstract:

We have developed a novel statistical method to address a fundamental scientific goal: disaggregation, or estimation of the composition of an unknown aggregate target. By combining forward (computer) models of the target of interest with measured data, our approach enables computer-model calibration techniques to directly solve the disaggregation problem. We develop our method in the context of chemical spectra generated by laser-induced breakdown spectroscopy (LIBS), used by instruments such as ChemCam on the Mars Rover Curiosity. Because a single run of the LIBS computer model may take hours on parallel computing platforms, we build fast emulators for single-compound targets. We then construct multi-compound emulators by combining the single-compound emulators in a hierarchical model. Our approach yields the first statistical characterization of matrix effects, i.e. spectral peaks that are amplified or suppressed when compounds are combined in a target versus measured in isolation, and the first capability in uncertainty quantification (UQ) that addresses the unique challenges of chemical spectra.


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