Analysis of Active Neutron Measurements From the Mars Science Laboratory Dynamic Albedo of Neutrons Instrument: Intrinsic Variability, Outliers, and Implications for Future Investigations

H. R. Kerner, C. J. Hardgrove, S. Czarnecki, T. S.J. Gabriel, I. G. Mitrofanov, M. L. Litvak, A. B. Sanin, D. I. Lisov

Research output: Contribution to journalArticle

Abstract

The Dynamic Albedo of Neutrons (DAN) instrument onboard Mars Science Laboratory uses neutron die-away, an active nuclear spectroscopy technique, to measure the abundance and depth distribution of hydrogen and neutron-absorbing elements (e.g., Fe and Cl) in the top ∼0.5 m of the Mars subsurface. We examined the intrinsic variability in neutron die-away data using simulated DAN measurements with a range of compositions relevant to equatorial and high-latitude environments on Mars. Our analysis shows that the total neutron counts and timing of neutron arrival explain most variability in thermal neutron die-away curves for a DAN-like instrument configuration over homogeneous subsurfaces. We analyzed the variability in thermal neutron die-away across a variety of elemental compositions that might be observed by DAN or future instruments. We found that when H concentration is low (e.g., in equatorial regions including Gale crater), neutron die-away is most sensitive to variations in H. Conversely, when H concentration is high (e.g., in poleward regions of Mars or icy bodies), neutron die-away is most sensitive to variations in neutron absorbers. We estimated that the H and neutron absorber concentrations in DAN measurements acquired Sols 1–2080 in Gale crater and found that most measurements had low H and moderate absorber content. We presented an outlier analysis of these measurements to identify targets with high potential scientific impact and found that most outliers along the traverse corresponded with abnormally low or high neutron absorber content measurements, some of which may be associated with high-silica fracture-associated halos and felsic igneous material.

Original languageEnglish (US)
Article numbere2019JE006264
JournalJournal of Geophysical Research: Planets
Volume125
Issue number5
DOIs
StatePublished - May 1 2020

Keywords

  • machine learning
  • Mars
  • Mars Science Laboratory
  • nuclear spectroscopy
  • outlier detection
  • statistical analysis

ASJC Scopus subject areas

  • Geophysics
  • Forestry
  • Oceanography
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Palaeontology

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