SuperCam Raman Activities at Jezero Crater, Mars: Observational Strategies, Data Processing, and Mineral Detections During the First 1000 Sols
Bibliographic record
Abstract
Abstract The Mars 2020 Perseverance rover introduced Raman spectroscopy to in situ planetary exploration for the first time when it landed in Jezero crater on Mars in February 2021. The SuperCam instrument onboard Perseverance is a multi‐analytical tool capable of acquiring time‐resolved Raman data from Martian targets at standoff distances of a few meters. This is a particularly challenging task due to the operational constraints, the harsh conditions on the Martian surface, and especially the very fine‐grained nature of the Martian soil. To address these challenges, the SuperCam Raman team has invested significant effort into optimizing both the acquisition and post‐processing of Raman data collected on Mars, as detailed in this work. Additionally, this paper reviews and discusses the detections made by SuperCam Raman during the first 1,000 sols (almost 3 Earth years) of the Mars 2020 mission. During this period, SuperCam Raman data provided key insights into the mineralogy of Jezero throughout the Crater, Delta, and Margin Campaigns. Key detections include olivine, carbonates, perchlorates, and sulfates (such as anhydrite), identified in both abraded patches and natural surfaces. The high specificity of Raman spectroscopy enables the unequivocal identification of these minerals, allowing for rapid and direct interpretation of Jezero's mineralogy, especially when combined with other techniques from SuperCam or others on the rover. Furthermore, this paper compiles the spectra acquired from the SuperCam Calibration Target samples on Mars, including studies on the degradation of the Ertalyte (PET), an organic polymer sample and analyses of diamond, apatite, and other reference materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".