DocumentCode :
3389318
Title :
Bayesian Source Separation Applied to Identifying Complex Organic Molecules in Space
Author :
Knuth, Kevin H. ; Tse, Man Kit ; Choinsky, Joshua ; Maunu, Haley A. ; Carbon, Duane F.
Author_Institution :
University at Albany, Department of Physics, Albany NY USA
fYear :
2007
fDate :
26-29 Aug. 2007
Firstpage :
346
Lastpage :
350
Abstract :
Emission from a class of benzene-based molecules known as Polycyclic Aromatic Hydrocarbons (PAHs) dominates the infrared spectrum of star-forming regions. The observed emission appears to arise from the combined emission of numerous PAH species, each with its unique spectrum. Linear superposition of the PAH spectra identifies this problem as a source separation problem. It is, however, of a formidable class of source separation problems given that different PAH sources potentially number in the hundreds, even thousands, and there is only one measured spectral signal for a given astrophysical site. Fortunately, the source spectra of the PAHs are known, but the signal is also contaminated by other spectral sources. We describe our ongoing work in developing Bayesian source separation techniques relying on nested sampling in conjunction with an ON/OFF mechanism enabling simultaneous estimation of the probability that a particular PAH species is present and its contribution to the spectrum.
Keywords :
Bayesian methods; Extraterrestrial measurements; Hydrocarbons; Infrared spectra; Ionization; NASA; Pollution measurement; Sampling methods; Source separation; Temperature; Astrophysics; Bayesian; Biochemistry; Source Separation; Spectral Estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2007. SSP '07. IEEE/SP 14th Workshop on
Conference_Location :
Madison, WI, USA
Print_ISBN :
978-1-4244-1198-6
Electronic_ISBN :
978-1-4244-1198-6
Type :
conf
DOI :
10.1109/SSP.2007.4301277
Filename :
4301277
Link To Document :
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