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Activity Number:
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11
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Type:
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Topic Contributed
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Date/Time:
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Sunday, August 8, 2004 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #300696 |
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Title:
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Using Ultra-high-resolution Spectra to Reconstruct the Temperature and Composition of an Astronomical Source
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Author(s):
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David A. van Dyk*+ and Hosung Kang and Vinay Kashyap and Alanna Connors
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Companies:
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University of California, Irvine and Harvard University and Harvard-Smithsonian Center for Astrophysics and Eurika Scientific
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Address:
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, Irvine , CA, 92697-1250,
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Keywords:
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astronomy ; Bayesian methods ; missing data ; MCMC ; EM algorithm ; spectral analysis
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Abstract:
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An astronomical spectrum is essentially a histogram of the wavelength of the electromagnetic radiation from an astronomical source. In empirical high-energy astrophysics data is collected on the wavelength/energy of each photon that arrives at a detector. High-resolution spectra carry subtle information as to the physical environment of the cosmological source. For example, when an electron jumps down from one quantum state of an atom to another, the energy of the electron decreases. This energy is radiated away from the atom in the form of a photon with energy equal to difference of the energies associated with the two quantum states. These differences are unique to the ion that produced the photon and can be used to identify the ion. If the source is relatively hot, the emission corresponding to more energetic quantum states will be relatively strong. Thus, a spectrum carries information as to the temperature of the source. We describe the model-based statistical methods developed by the California-Harvard Astrostatistics Collaboration that aim to use spectral data to reconstruct the physical environment of an astronomical source.
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