Joint modelling of preliminary Comet Interceptor flyby scenarios with photorealistic 3D tools for OPIC, MIRMIS Hyperspectral Imager and EnVisS instruments (CI3D)

Contributors

Andris Slavinskis

Karina Šķirmante

Kristaps Blumbergs

Antti Penttilä

Mihkel Pajusalu

Datasets

INSTRUMENTNAME_close_0_phase: Exaggeratedly close flyby for demonstration purposes (500 km farthest approach, 25 km closest)

INSTRUMENTNAME_close_90_phase: Same flyby with 90° phase angle

INSTRUMENTNAME_far_0_phase: Realistic Comet Interceptor scenario (700 km farthest approach, 200 km closest approach)

INSTRUMENTNAME_far_90_phase: Same flyby with 90° phase angle


Inside each dataset:

comp_low: composition of surface + low intensity coma

comp_mid: composition of surface + higher intensity coma

exr_comp: composition in EXR multilayer format

only_surface: this layer contains only the surface of the target body

only_coma_low: this layer contains only the low intensity coma, with a transparent hole in place of the surface, showing the coma in front but not the coma behind.

only_coma_mid: same as before but with the higher intensity coma

Note: OPIC has been rendered at 25% resolution, for demonstration purposes.

Commode models

In order to produce the volume density grids, a modified ComMoDE (https://www.cosmos.esa.int/web/comet-interceptor/comet-model-of-dust-environments-commode-) algorithm is used and packaged in the commode_deliver.py script. It also includes a example YAML input parameter file as seen in config.yaml. Directory also includes example simulation results, used by the dataset rendering pipeline for various dust and gas production rates. Included are also the the precomputed wavelength independent scattering properties for various cometary dust materials distributed by the original ComMoDE pipeline. Script may be ran by calling " python commode_deliver.py ", which will produce a directory named simulation_results, in which the currently ran simulation density grids will be generated along with meta data about simulation parameters and computed physical properties.
Third party libraries in the Python script may be installed using pip install numpy numba imageio pyyaml .
For detailed description of the ComMoDE algorithm, see thesis written by Nico Haslebacher - https://boristheses.unibe.ch/5178/4/24haslebacher_n.pdf .

Since ComMoDE is licensed under the ESA Public License v2.4, the CI3D pipeline implementation code is also released under the same license.