The Mars rover Curiosity carries an instrument called ChemCam to determine the composition of the soil and rocks via laser-induced breakdown spectroscopy (LIBS). Los Alamos National Laboratory has developed a simulation capability that can predict spectra from ChemCam, but there are major-scale differences between the prediction and observation. This presents a challenge when using Bayesian model calibration to determine the unknown physical parameters that describe the LIBS observations. We present an analysis of LIBS data to support ChemCam based on including a structured discrepancy model in a Bayesian model-calibration scheme. This is both a novel application and an illustration of the importance of setting scientifically informed and constrained discrepancy models within Bayesian model calibration.
"Structured discrepancy in Bayesian model calibration for ChemCam on the Mars Curiosity rover." Ann. Appl. Stat. 14 (4) 2020 - 2036, December 2020. https://doi.org/10.1214/20-AOAS1373