Paper No: 29
Blind Signal Separation Methods for the Identification of Interstellar Carbonaceous Nanoparticles
Author(s): Olivier Berne, Yannick Deville, Christine Joblin
The use of Blind Signal Separation methods (ICA and other approaches)
for the analysis of astrophysical data remains quite unexplored. In this paper,
we present a new approach for analyzing
the infrared emission spectra of interstellar
dust, obtained with NASA's Spitzer Space Telescope, using FastICA and
Non-negative Matrix Factorization (NMF).
Using these two methods, we were able to unveil
the source spectra of three different types of carbonaceous nanoparticles
present in interstellar space.
These spectra can then constitute a basis for the interpretation of the mid-infrared
emission spectra of interstellar dust in the Milky Way and nearby galaxies.
We also show how to use these extracted spectra to derive the spatial
distribution of these nanoparticles.