Articles | Volume 4, issue 1
Research article
27 Feb 2015
Research article |  | 27 Feb 2015

COSIMA data analysis using multivariate techniques

J. Silén, H. Cottin, M. Hilchenbach, J. Kissel, H. Lehto, S. Siljeström, and K. Varmuza

Abstract. We describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections. The technique allows us to do full clustering and classification of the measured mass spectra. In this paper we use the tool for classification purposes. The presentation describes calibration experiments of 19 minerals on Ag and Au substrates using positive mode ion spectra. The discrimination between individual minerals gives a cross-validation Cohen κ for classification of typically about 80%. We intend to use the method as a fast tool to deduce a qualitative similarity of measurements.

Short summary
COSIMA, an advanced TOF-SIMS instrument measuring the mass spectrum of dust grains collected at comet P67 by the ROSETTA spacecraft, is predicted to encounter complex mixtures of minerals and organic compounds. To extract information from this data set, we have developed a multivariate technique tested on laboratory measurements made by an identical instrument under controlled conditions. We have shown that minerals can be identified and separated with high level of confidence.