  The Mars Curiosity rover carries an instrument, ChemCam, designed to measure
the composition of surface rocks and soil using laser-induced breakdown
spectroscopy (LIBS). The measured spectra from this instrument must be analyzed
to identify the component elements in the target sample, as well as their
relative proportions. This process, which we call disaggregation, is
complicated by so-called matrix effects, which describe nonlinear changes in
the relative heights of emission lines as an unknown function of composition
due to atomic interactions within the LIBS plasma. In this work we explore the
use of the plasma physics code ATOMIC, developed at Los Alamos National
Laboratory, for the disaggregation task. ATOMIC has recently been used to model
LIBS spectra and can robustly reproduce matrix effects from first principles.
The ability of ATOMIC to predict LIBS spectra presents an exciting opportunity
to perform disaggregation in a manner not yet tried in the LIBS community,
namely via Bayesian model calibration. However, using it directly to solve our
inverse problem is computationally intractable due to the large parameter space
and the computation time required to produce a single output. Therefore we also
explore the use of emulators as a fast solution for this analysis. We discuss a
proof of concept Gaussian process emulator for disaggregating two-element
compounds of sodium and copper. The training and test datasets were simulated
with ATOMIC using a Latin hypercube design. After testing the performance of
the emulator, we successfully recover the composition of 25 test spectra with
Bayesian model calibration.
