Phobos and Deimos surface composition: search for spectroscopic analogues
Bibliographic record
Abstract
ABSTRACT Phobos and Deimos, the two satellites of Mars, were largely studied in the past using ground-based telescope and spacecraft data, although most of the data were obtained by opportunity observations performed by Mars dedicated orbiters. Despite the data available so far, the main composition of the two moons is not yet fully understood. The possible presence of hydrated minerals along with mafic minerals olivine and pyroxene seems to be the most plausible interpretation, but more investigations are needed. MIRS spectrometer on-board the future JAXA MMX sample return mission will help to unveil the open question on the composition of Phobos and Deimos. In this work, we review past spectroscopic observations of the Martian moons, both from ground observatories and spacecraft data set, aiming at better understanding the constraints in interpreting the Mars satellites composition and at identifying the best spectroscopic analogues. We also present new laboratory measurements on mineral mixing and meteorites to match the satellites spectral behaviour. New measurements were acquired at INAF-Astrophysical Observatory of Arcetri and IPAG laboratories at room conditions exploring different geometries and the results obtained set new constraints for future laboratory measurements. Our preliminary results confirm that the surface of Phobos and Deimos can be associated with samples characterized by a higher presence of dark components (e.g. amorphous carbon) or minerals produced by space weathering (e.g. Fe0 and FeS-bearing materials). Presence of dark component could also be totally responsible for the reduced hydrated band observed on the moons without invoking dehydration or OH-implantation on anhydrous surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".