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INFRARED ASTRONOMICAL SOURCES: CLASSIFICATION BASED ON SCALING PROPERTIES OF THE RADIATIVE TRANSFER PROBLEM

DOI: 10.1615/ICHMT.1995.RadTransfProc.570

Zeljko Ivezic
Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055, USA

Moshe Elitzur
Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055, USA

Abstrakt

Astronomical objects usually appear as point sources since most observations are incapable of resolving them. Thus the only way to infer the nature of a source is spectral analysis of observed flux. Many objects are embedded in a dusty envelope which scatters, absorbs and re-radiates the radiation emitted by the underlying source. As a result, spectra of these objects are shifted toward the infrared wavelengths.
For dust heated only by the radiation field we show that the resulting spectral shape does not depend on the spatial dimensions of the underlying source and envelope. The only parameters that specify the radiative transfer problem are the overall optical depth and, unlike for plan-parallel geometry, the functional form of the dust spatial distribution. The properties of the central source enter only through its spectral shape and are not important at the infrared wavelengths considered here. Consequently, for a given dust chemical composition, the resulting spectrum is fully determined by the dust spatial distribution and overall optical depth. This conclusion is of great importance since objects of different nature are expected to have different dust spatial distributions, dependent mainly on whether the envelope is collapsing onto or expanding away from the central source. Thus, detailed radiative transfer modeling can provide efficient methods to determine the amount of dust, its chemical composition and the nature of the object which emitted the observed spectrum.
Our models show that observations obtained by the Infrared Astronomical Satellite (IRAS) can indeed be interpreted in terms of the overall optical depth and dust spatial distributions. Preliminary comparison with results obtained for some sources by other methods verify the basic premises and show that reliable classification of all sources observed by IRAS is feasible.

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