The discovery and characterization of exoplanetary systems is a new exciting field. At just over two decades old, it has already fundamentally reshaped our knowledge of planet and solar system formation. We now know that there is a vast diversity of planetary systems, in highly varied, even bizarre, configurations. Known planetary bodies span all masses from objects less massive and smaller than Earth to objects as large as the smallest stars or brown dwarfs. They exhibit periods of but a few hours to periods spanning millennia, from nearly perfectly circular orbits to highly elliptical, from fluffy gas giants to dense rocky worlds, from purely metallic worlds to water worlds. Exoplanets come in all sizes, compositions and varieties. These new discoveries have fundamentally changed the way we approach planetary science. With such a great diversity in exoplanets, we look extend our knowledge to including understanding their individual composition. We wish to understand the climate of these exoplanets and to resolve the differences between, for example, Earth-like and Venus-like planets.
To facilitate these discoveries several methods of exoplanery detection and characterization have been developed. Among them are indirect methods that infer the existence of exoplanets from their influence on their star, and direct methods that detect the light from the exoplanets themselves. Direct detection of exoplanets allows not only for a determination of the existence of the object, but also for the determination of its composition and climate through the measurement of its atmosphere's chemical composition. Using purely high-contrast direct imaging methods, coarse spectra can now be measured for exoplanets with a relative brightness 10⁻⁴-10⁻⁵ below that of the host star. Below this contrast level the companion is at the same level of brightness as the noise caused by optical defects and wave front errors in the observed light, called speckles.
In this thesis, I demonstrate the usage and optimization of a new novel technique, S4_Spectrum, to model and remove speckle noise from directly imaged systems. S4_Spectrum is capable of reducing 99% of the speckle noise. This allows for the detection and spectral characterization of exoplanets as faint as 10⁻⁶-10⁻⁷ times the brightness of their host stars. This represents two orders of magnitude gain in sensitivity. I present the design of one of these high-contrast systems, Project 1640, as well as the data collection method, including the data pipeline and analysis techniques. Also, I describe the S4_Spectrum technique in detail, as implemented in Project 1640, and present its operation and optimization. Additionally, I present the application of this new tool to obtain several spectral characterizations of objects found in the Project 1640 survey.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8TT4QWM |
| Date | January 2016 |
| Creators | Veicht, Aaron Michael |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
Page generated in 0.0019 seconds