Many space probes have conducted in situ explorations of asteroids, in recent decades, intent on identifying evidence of the solar system's earliest processes of formation within the asteroids' interiors. Several future asteroid missions are planned, among which include ESA's Hera mission to explore the Didymos binary asteroid pair. An ion mass analyzer is currently being designed at the Swedish Institute of Space Physics for use as part of the Hera mission.

This thesis aims to optimize the instrument such that each of its parameters meets the requirement for performance. A computer simulation is used to calculate the trajectories of low-energy ions inside the instrument, where the electrostatic potential are imposed by grids and electrodes embedded inside the instrument. From the data analysis of the simulation results, the performance for each parameter can be derived. By changing the settings of the grids and electrodes (e.g., positions and voltages), the instrument parameters are to be optimized. Two tasks are set up in this project--- the first task is to optimize the focusing system of the incoming ions at the instrument's entrance, and the second task is to investigate the reflectron system so that the mass resolution of the instrument can be optimized via reducing the spread of the ions' time of flight spectra.

The focusing system is found to already be optimized, but instead, a relation between its position of the grid at the instrument's entrance and the instrument's performance is derived. The method of and parameters for optimization within the reflectron are extensively tested individually during this project. Although several performances in each trial from the reflectron analysis cannot meet at least one of the requirements, enough scenarios are examined such that every parameter tested ends with a value suitable to be applied individually to optimize the ion mass analyzer. The findings from the individual tests done in this project can be applied to further optimization, particularly to optimize multiple parameters simultaneously in the near future.