Mars Sample Return (MSR) mission: Bayesian statistics for planetary protection

Abstract

The Mars Sample Return (MSR) mission of NASA and ESA (European Space Agency) involves the collection and return to Earth circa 2040 of samples from the surface and atmosphere of Mars. A “Tiger Team” of scientists submitted a report to NASA/ESA in 2024 on planetary protection from potential biohazards in the returned sample tubes. This talk develops the Bayesian statistical design used to determine how many subsamples per tube will be needed for biohazard testing. There are no data available since the samples are still on Mars; however, there is prior astro-biological knowledge, and a Bayesian statistical approach can direct how that knowledge can be used. The optimal number of subsamples is seen to depend on a prespecified risk-tolerance threshold (e.g., one in a million) and on three other quantities that originate from the Bayesian design. Monte Carlo simulation is used in a digital twin to compute the optimal number of subsample