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arXiv · 0704.2179

Spitzer spectral line mapping of supernova remnants: I. Basic data and principal component analysis

Abstract

We report the results of spectroscopic mapping observations carried out toward small (1 x 1 arcmin) regions within the supernova remnants W44, W28, IC443, and 3C391 using the Infrared Spectrograph of the Spitzer Space Telescope. These observations, covering the 5.2 - 37 micron spectral region, have led to the detection of a total of 15 fine structure transitions of Ne+, Ne++, Si+, P+, S, S++, Cl+, Fe+, and Fe++; the S(0) - S(7) pure rotational lines of molecular hydrogen; and the R(3) and R(4) transitions of hydrogen deuteride. In addition to these 25 spectral lines, the 6.2, 7.7, 8.6, 11.3 and 12.6 micron PAH emission bands were also observed. Most of the detected line transitions have proven strong enough to map in several sources, providing a comprehensive picture of the relative distribution of the various line emissions observable in the Spitzer/IRS bandpass. A principal component analysis of the spectral line maps reveals that the observed emission lines fall into five distinct groups, each of which may exhibit a distinct spatial distribution: (1) lines of S and H2 (J > 2); (2) the H2 S(0) line; (3) lines of ions with appearance potentials less than 13.6 eV; (4) lines of ions with appearance potentials greater than 13.6 eV, not including S++; (5) lines of S++. Lines of group (1) likely originate in molecular material subject to a slow, nondissociative shock that is driven by the overpressure within the supernova remnant, and lines in groups (3) - (5) are associated primarily with dissociative shock fronts with a range of (larger) shock velocities. The H2 S(0) line shows a low-density diffuse emission component, and - in some sources - a shock-excited component.

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BibTeXRIS

David A. Neufeld, David J. Hollenbach, Michael J. Kaufman, Ronald L. Snell, Gary J. Melnick, Edwin A. Bergin, Paule Sonnentrucker. 2007-04-17. Spitzer spectral line mapping of supernova remnants: I. Basic data and principal component analysis. https://doi.org/10.1086/518857

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