Modeling the Surface Composition of 67/P Churyumov-Gerasimenko: Expected Performance of the VIRTIS-M Spectrometer Onboard the Rosetta Spacecraft.

The Rosetta spacecraft will encounter comet 67P/Churyumov-Gerasimenko in the second half of 2014. The present study investigates the capabilities of the VIRTIS-M imaging spectrometer onboard Rosetta to detect and characterize the cometary nucleus surface composition; this is one of the major scientific objectives of the spectrometer that covers the range 0.25-5 μm. A radiative transfer model is applied to mixtures of plausible endmembers to determine the spectral radiance as a function of the observing conditions. We simulated surfaces composed of different types of ices mixtures assuming areal or intimate mixing. For the time being, we have assumed mixtures including water ice, carbon dioxide ice and methanol, but a wide range organics and other compounds (of known optical constants) can be used to generate mixtures. The ices are mixed with a dark opaque featureless component, having a spectral reflectance derived from the dark terrains of Tempel 1 as detected from HRII aboard Deep Impact. The I/F spectra for the areal and intimate mixing are calculated using Hapke's model.

The VIRTIS-M Simulator is an essential tool to calculate the instrumental signal / noise ratio (S/N) for different input signals and different observing conditions in which the spectrometer will operate during the mission. Its main aim is to obtain the optimal integration time, which allows to reach the best S/N while avoiding the saturation. Given a radiance in input, the simulator's output is the retrieved error on the signal. Moreover, given the heliocentric distance, it calculates the reflectance with its error.. Detection criteria for the various icy components are based on the evaluation of the error on the band area of diagnostic absorption features.

As expected, factors that increase the detectability of a spectral feature for a given endmember are: 1) longer integration time; 2) larger endmember abundance; 3) areal mixing with the dark terrain; 4) shorter heliocentric distance. On the other hand, if the signal is too high there is the possibility to reach saturation. Therefore, the simulator, allows to identify the optimal integration time for balancing the other factors. Finally, we plan to use the simulator to identify detection limits for the various components of the surface during the various phases of the mission.