Decoding Neutral Emission Mechanisms in Mercury’s Exosphere from STROFIO Mass Spectra

The Strofio neutral mass spectrometer aboard the BepiColombo Mercury Planetary Orbiter (MPO) will deliver unprecedented in situ mass-resolved measurements of Mercury’s exosphere. Designed to detect neutral atoms and molecules with high mass resolution via time-of-flight analysis (m/Δm ≥ 60), Strofio enables identification of exospheric constituents as the spacecraft traverses low-altitude polar orbits. Despite lacking intrinsic energy resolution, Strofio offers valuable directional sensitivity through its collimated field of view, spacecraft-relative velocity, and TOF measurements. These allow partial reconstruction of the particles’ distribution function. However, interpreting the resulting signals to infer exospheric source distributions requires a dedicated modeling framework that accounts for the ballistic, collisionless nature of Mercury’s exosphere and the instrument’s measurement geometry.

This work presents a signal inversion framework developed to translate Strofio’s detection count rates into surface production properties, including source location, emission mechanisms, and relative contribution of physical processes. The method is based on a Liouville Algorithm (LA), which propagates virtual particles backward in time from the point of detection through Mercury’s gravitational field to the planetary surface. Liouville’s theorem ensures that phase space density is conserved along these trajectories, allowing the surface source distribution to be mapped to the detector location. By integrating over the instrument’s known field of view, the algorithm calculates the expected count rate for a given surface emission model.

To support global exospheric context, the Exospheric Global Model or EGM (Leblanc et al., 2017) – a 3D Forward Monte Carlo model – is also included in the framework. EGM simulates large ensembles of particles launched from the surface, tracking their trajectories under gravity and/or optional forces. It is particularly useful for modeling multi-hop transport and determining steady-state surface coverage for volatile species. The LA model and EGM are used in a hybrid configuration where the FMC estimates the steady-state distribution of re-emitted particles, and the LA predicts the resulting Strofio signal. This combined approach ensures physical self-consistency and computational efficiency.

Importantly, the framework incorporates Strofio’s exact detection geometry and TOF characteristics. The instrument’s collimation angle, sensitivity function, and mass resolution are included in the integration to faithfully simulate the expected signal. Loss processes such as photoionization or detector dead time can also be included in the signal mapping, ensuring realistic comparison with observed data.

In summary, this framework enables Strofio to fulfill its science goals by linking count rates in time-of-flight spectra to the physical and spatial properties of Mercury’s surface sources. By combining Liouville-based inversion with targeted forward simulations and instrument-specific integration, the model transforms directional data into actionable scientific insight.