Frontiers in Artificial Intelligence (Aug 2021)

On Topological Analysis of fs-LIMS Data. Implications for in Situ Planetary Mass Spectrometry

  • Rustam A. Lukmanov,
  • Andreas Riedo,
  • David Wacey,
  • Niels F. W. Ligterink,
  • Valentine Grimaudo,
  • Marek Tulej,
  • Coenraad de Koning,
  • Anna Neubeck,
  • Peter Wurz

DOI
https://doi.org/10.3389/frai.2021.668163
Journal volume & issue
Vol. 4

Abstract

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In this contribution, we present results of non-linear dimensionality reduction and classification of the fs laser ablation ionization mass spectrometry (LIMS) imaging dataset acquired from the Precambrian Gunflint chert (1.88 Ga) using a miniature time-of-flight mass spectrometer developed for in situ space applications. We discuss the data generation, processing, and analysis pipeline for the classification of the recorded fs-LIMS mass spectra. Further, we define topological biosignatures identified for Precambrian Gunflint microfossils by projecting the recorded fs-LIMS intensity space into low dimensions. Two distinct subtypes of microfossil-related spectra, a layer of organic contamination and inorganic quartz matrix were identified using the fs-LIMS data. The topological analysis applied to the fs-LIMS data allows to gain additional knowledge from large datasets, formulate hypotheses and quickly generate insights from spectral data. Our contribution illustrates the utility of applying spatially resolved mass spectrometry in combination with topology-based analytics in detecting signatures of early (primitive) life. Our results indicate that fs-LIMS, in combination with topological methods, provides a powerful analytical framework and could be applied to the study of other complex mineralogical samples.

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