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The Mars Curiosity rover carries an instrument, ChemCam, designed to measurethe composition of surface rocks and soil using laser-induced breakdownspectroscopy (LIBS). The measured spectra from this instrument must be analyzedto identify the component elements in the target sample, as well as theirrelative proportions. This process, which we call disaggregation, iscomplicated by so-called matrix effects, which describe nonlinear changes inthe relative heights of emission lines as an unknown function of compositiondue to atomic interactions within the LIBS plasma. In this work we explore theuse of the plasma physics code ATOMIC, developed at Los Alamos NationalLaboratory, for the disaggregation task. ATOMIC has recently been used to modelLIBS spectra and can robustly reproduce matrix effects from first principles.The ability of ATOMIC to predict LIBS spectra presents an exciting opportunityto perform disaggregation in a manner not yet tried in the LIBS community,namely via Bayesian model calibration. However, using it directly to solve ourinverse problem is computationally intractable due to the large parameter spaceand the computation time required to produce a single output. Therefore we alsoexplore the use of emulators as a fast solution for this analysis. We discuss aproof of concept Gaussian process emulator for disaggregating two-elementcompounds of sodium and copper. The training and test datasets were simulatedwith ATOMIC using a Latin hypercube design. After testing the performance ofthe emulator, we successfully recover the composition of 25 test spectra withBayesian model calibration.

An Initial Exploration of Bayesian Model Calibration for Estimating the Composition of Rocks and Soils on Mars