Articles | Volume 4, issue 1
https://doi.org/10.5194/gi-4-45-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gi-4-45-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
COSIMA data analysis using multivariate techniques
J. Silén
Finnish Meteorological Institute, Erik Palmenin aukio 1, PB 503, 00101 Helsinki, Finland
H. Cottin
Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA), UMR7583 – CNRS, Université Paris Est – Créteil (UPEC), Université Paris Diderot (UPD), 61 Avenue du Général de Gaulle, 94010 Créteil, France
M. Hilchenbach
Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3, 37077 Göttingen, Germany
J. Kissel
Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3, 37077 Göttingen, Germany
H. Lehto
Tuorla Observatory Dept of Physics and Astronomy University of Turku, 21500 Piikkiö, Finland
S. Siljeström
Department of Chemistry, Materials and Surfaces, SP Technical Research Institute of Sweden, Borås, Sweden
K. Varmuza
Vienna University of Technology, Department of Statistics and Probability Theory, Wiedner Hauptstrasse 7/107, 1040 Vienna, Austria
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Geosci. Instrum. Method. Data Syst., 6, 239–256, https://doi.org/10.5194/gi-6-239-2017, https://doi.org/10.5194/gi-6-239-2017, 2017
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H. J. Lehto, B. Zaprudin, K. M. Lehto, T. Lönnberg, J. Silén, J. Rynö, H. Krüger, M. Hilchenbach, and J. Kissel
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M. Sampl, W. Macher, C. Gruber, T. Oswald, M. Kapper, H. O. Rucker, and M. Mogilevsky
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Y. V. Khotyaintsev, P.-A. Lindqvist, C. M. Cully, A. I. Eriksson, and M. André
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N. Doss, A. N. Fazakerley, B. Mihaljčić, A. D. Lahiff, R. J. Wilson, D. Kataria, I. Rozum, G. Watson, and Y. Bogdanova
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Geosci. Instrum. Method. Data Syst., 3, 49–58, https://doi.org/10.5194/gi-3-49-2014, https://doi.org/10.5194/gi-3-49-2014, 2014
C. G. Mouikis, L. M. Kistler, G. Wang, and Y. Liu
Geosci. Instrum. Method. Data Syst., 3, 41–48, https://doi.org/10.5194/gi-3-41-2014, https://doi.org/10.5194/gi-3-41-2014, 2014
J. S. Pickett, I. W. Christopher, and D. L. Kirchner
Geosci. Instrum. Method. Data Syst., 3, 21–27, https://doi.org/10.5194/gi-3-21-2014, https://doi.org/10.5194/gi-3-21-2014, 2014
K. H. Yearby, S. N. Walker, and M. A. Balikhin
Geosci. Instrum. Method. Data Syst., 2, 323–328, https://doi.org/10.5194/gi-2-323-2013, https://doi.org/10.5194/gi-2-323-2013, 2013
L. M. Kistler, C. G. Mouikis, and K. J. Genestreti
Geosci. Instrum. Method. Data Syst., 2, 225–235, https://doi.org/10.5194/gi-2-225-2013, https://doi.org/10.5194/gi-2-225-2013, 2013
N. I. Kömle, W. Macher, G. Kargl, and M. S. Bentley
Geosci. Instrum. Method. Data Syst., 2, 151–156, https://doi.org/10.5194/gi-2-151-2013, https://doi.org/10.5194/gi-2-151-2013, 2013
M. D. Paton, A.-M. Harri, T. Mäkinen, and S. F. Green
Geosci. Instrum. Method. Data Syst., 1, 7–21, https://doi.org/10.5194/gi-1-7-2012, https://doi.org/10.5194/gi-1-7-2012, 2012
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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.
COSIMA, an advanced TOF-SIMS instrument measuring the mass spectrum of dust grains collected at...