Circumstellar Disk Modeling with Bayesian Statistics and Marginal Probabilities
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2006
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Swarthmore College. Dept. of Physics & Astronomy
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Thesis (B.A.)
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Abstract
This paper summarizes current knowledge of circumstellar debris disks and presents methods of
modeling optically thin disks. The techniques of Bayesian statistics and marginal probabilities are
applied to the disk modeling problem so that I can construct probability distributions for individual
disk parameters. I apply these methods and interpret the results for three stars: HD 105, HD
107146, and HD 115043.
In the introduction, I give background information on circumstellar disks, and their possible
connection with dust in the Solar System. I describe the general technique of modeling infrared
excesses, and present the goals of this paper. Because the stars I study are unresolved in the
wavelength range of dust emission, the flux contributions of a star and its disk must be separated
before I can model the disk parameters. To do that, I model the star's photosphere, and subtract
its contribution from the data.
In the body of the paper, I describe the data and the modeling procedures for the photosphere
and the circumstellar disk. I present the methods of Bayesian statistics and marginal probabilities
as they apply to this paper, and I use the techniques to analyze the three star sample. The methods
of Bayesian/ marginal statistics reveal probability distributions of seven disk modeling parameters
for each star, and in many cases, place constraints on important parameters such as inner radius
and disk mass. HD 107146 has a resolved disk in scattered light, and the results of my marginal
distributions are compared to the resolved data. I also examine the results of HD 107146 with
and without millimeter data to demonstrate the usefulness of long-wavelength observations for
constraining the disk's inner radius and dust absorption/ emission parameters. I conclude the paper
with a list of future steps- both short-term and long-term.