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Record W3117126124 · doi:10.1007/s11214-020-00777-5

The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests

2020· review· en· W3117126124 on OpenAlexaff
R. C. Wiens, S. Maurice, S. Robinson, Anthony Nelson, Philippe Caïs, Pernelle Bernardi, Raymond Newell, S. M. Clegg, Shiv K. Sharma, S. A. Storms, Jonathan Deming, Darrel Beckman, A. Ollila, O. Gasnault, R. B. Anderson, Yves André, S. M. Angel, Gorka Arana, Elizabeth C. Auden, Pierre Beck, Joseph F. Becker, Karim Benzerara, Sylvain Bernard, Olivier Beyssac, Louis Borges, Bruno Bousquet, Kerry Boyd, Michael Caffrey, Jeffrey J. Carlson, Kepa Castro, Jorden Celis, Baptiste Chide, Kevin B. Clark, E. A. Cloutis, Elizabeth Córdoba-Lanús, A. Cousin, Magdalena Dale, Lauren DeFlores, D. Delapp, M. Deleuze, Matthew Dirmyer, Christophe Donny, Gilles Dromart, M. George Duran, Miles J. Egan, Joan Ervin, C. Fabre, A. Fau, Woodward W. Fischer, O. Forni, Thierry Fouchet, Reuben Fresquez, J. Frydenvang, Denine Gasway, Ivair Gontijo, J. P. Grotzinger, Xavier Jacob, S. Jacquinod, J. R. Johnson, Roberta Ann Klisiewicz, James Lake, N. Lanza, J. J. Laserna, J. Lasue, Stéphane Le Mouëlic, Carey Legett, Richard Léveillé, Éric Lewin, G. López-Reyes, R. D. Lorenz, Éric Lorigny, Steven P. Love, Briana Lucero, Juan Manuel Madariaga, M. B. Madsen, S.N. Madsen, N. Mangold, J. A. Manrique, Javier Martínez, Jesús Martínez‐Frías, Kevin McCabe, T. H. McConnochie, Justin McGlown, S. M. McLennan, Noureddine Melikechi, Pierre‐Yves Meslin, John Michel, D. Mimoun, A. K. Misra, Gilles Montagnac, Franck Montmessin, Valérie Mousset, Naomi Murdoch, H. E. Newsom, Logan Ott, Zachary R. Ousnamer, L. Parès, Yann Parot, Rafal Pawluczyk, C. G. Peterson, P. Pilleri, P. Pinet, G. Pont, F. Poulet, Cheryl Provost, Benjamin Quertier, Heather Quinn, W. Rapin, Jean-Michel Réess, A. Regan, A. Reyes‐Newell, Philip J. Romano, Clément Royer, F. Rull, Benigno Sandoval, Joseph H. Sarrao, V. Sautter, Marcel Schoppers, Susanne Schröder, Daniel Seitz, Terra Gudrun Shepherd, P. Sobrón, Bruno Dubois, Vishnu Sridhar, Michael J. Toplis, I. Torre-Fdez, Ian A. Trettel, M. L. Underwood, Andres Valdez, J. B. Valdez, Dawn Venhaus, Peter A. Willis

Bibliographic record

VenueSpace Science Reviews · 2020
Typereview
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsFiberTech Optica (Canada)McGill UniversityUniversity of Winnipeg
FundersLos Alamos National LaboratoryCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesAgence Nationale de la RechercheNational Aeronautics and Space Administration
KeywordsMars Exploration ProgramSuiteAstrobiologyPlanetary scienceAerospace engineeringExploration of MarsRemote sensingEnvironmental scienceGeologyMeteorologyPhysicsEngineeringGeography

Abstract

fetched live from OpenAlex

Abstract The SuperCam instrument suite provides the Mars 2020 rover, Perseverance, with a number of versatile remote-sensing techniques that can be used at long distance as well as within the robotic-arm workspace. These include laser-induced breakdown spectroscopy (LIBS), remote time-resolved Raman and luminescence spectroscopies, and visible and infrared (VISIR; separately referred to as VIS and IR) reflectance spectroscopy. A remote micro-imager (RMI) provides high-resolution color context imaging, and a microphone can be used as a stand-alone tool for environmental studies or to determine physical properties of rocks and soils from shock waves of laser-produced plasmas. SuperCam is built in three parts: The mast unit (MU), consisting of the laser, telescope, RMI, IR spectrometer, and associated electronics, is described in a companion paper. The on-board calibration targets are described in another companion paper. Here we describe SuperCam’s body unit (BU) and testing of the integrated instrument. The BU, mounted inside the rover body, receives light from the MU via a 5.8 m optical fiber. The light is split into three wavelength bands by a demultiplexer, and is routed via fiber bundles to three optical spectrometers, two of which (UV and violet; 245–340 and 385–465 nm) are crossed Czerny-Turner reflection spectrometers, nearly identical to their counterparts on ChemCam. The third is a high-efficiency transmission spectrometer containing an optical intensifier capable of gating exposures to 100 ns or longer, with variable delay times relative to the laser pulse. This spectrometer covers 535–853 nm ( $105\text{--}7070~\text{cm}^{-1}$ 105 – 7070 cm − 1 Raman shift relative to the 532 nm green laser beam) with $12~\text{cm}^{-1}$ 12 cm − 1 full-width at half-maximum peak resolution in the Raman fingerprint region. The BU electronics boards interface with the rover and control the instrument, returning data to the rover. Thermal systems maintain a warm temperature during cruise to Mars to avoid contamination on the optics, and cool the detectors during operations on Mars. Results obtained with the integrated instrument demonstrate its capabilities for LIBS, for which a library of 332 standards was developed. Examples of Raman and VISIR spectroscopy are shown, demonstrating clear mineral identification with both techniques. Luminescence spectra demonstrate the utility of having both spectral and temporal dimensions. Finally, RMI and microphone tests on the rover demonstrate the capabilities of these subsystems as well.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.047
GPT teacher head0.292
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

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".

Quick stats

Citations325
Published2020
Admission routes1
Has abstractyes

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