Coupled blind signal separation and spectroscopic database fitting of the mid infrared PAH features^⋆

¹ Sterrewacht Leiden, Universiteit Leiden, Niels Bohrweg 2, 2333 CA Leiden, The Netherlands
e-mail: rosenberg@strw.leidenuniv.nl
² The International Space University, Parc d’Innovation, 1 rue Jean Dominique Cassini, 67400 Illkirch Graffenstaden, France
³ NASA Ames Research Center, Space Science Division, Mail Stop 245-6, Moffett Field, CA 94035, USA
e-mail: Louis.J.Allamandola@nasa.gov; Christiaan.Boersma@nasa.gov

Received: 16 December 2010
Accepted: 28 June 2011

Abstract

Context. The aromatic infrared bands (AIBs) observed in the mid infrared spectrum of galactic and extragalactic sources are attributed to polycyclic aromatic hydrocarbons (PAHs). Recently, two new approaches have been developed to analyze the variations of AIBs in terms of chemical evolution of PAH species: blind signal separation (BSS) and the NASA Ames PAH IR Spectroscopic Database fitting tool.

Aims. We aim to study AIBs in a photo-dissociation region (PDR) since in these regions, as the radiation environment changes, the evolution of AIBs are observed.

Methods. We observe the NGC 7023-north west (NW) PDR in the mid-infrared (10–19.5 μm) using the InfraRed Spectrometer (IRS), on board Spitzer, in the high-resolution, short wavelength mode. Clear variations are observed in the spectra, most notably the ratio of the 11.0 to 11.2 μm bands, the peak position of the 11.2 and 12.0 μm bands, and the degree of asymmetry of the 11.2 μm band. The observed variations appear to change as a function of position within the PDR. We aim to explain these variations by a change in the abundances of the emitting components of the PDR. A blind signal separation (BSS) method, i.e. a Non-Negative Matrix Factorization algorithm is applied to separate the observed spectrum into components. Using the NASA Ames PAH IR Spectroscopic Database, these extracted signals are fit. The observed signals alone were also fit using the database and these components are compared to the BSS components.

Results. Three component signals were extracted from the observation using BSS. We attribute the three signals to ionized PAHs, neutral PAHs, and very small grains (VSGs). The fit of the BSS extracted spectra with the PAH database further confirms the attribution to PAH⁺ and PAH⁰ and provides confidence in both methods for producing reliable results.

Conclusions. The 11.0 μm feature is attributed to PAH⁺ while the 11.2 μm band is attributed to PAH⁰. The VSG signal shows a characteristically asymmetric broad feature at 11.3 μm with an extended red wing. By combining the NASA Ames PAH IR Spectroscopic Database fit with the BSS method, the independent results of each method can be confirmed and some limitations of each method are overcome.