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DC Field | Value | Language |
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dc.contributor.advisor | Kasdin, N. Jeremy | - |
dc.contributor.author | Sun, He | - |
dc.contributor.other | Mechanical and Aerospace Engineering Department | - |
dc.date.accessioned | 2020-07-13T02:19:52Z | - |
dc.date.available | 2020-07-13T02:19:52Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01g445ch067 | - |
dc.description.abstract | One of the most important scientific goals of the next generation of large space telescopes is the imaging and characterization of earth-like exoplanets, which are a billion times fainter than their host stars. This requires that telescopes be equipped with high-contrast instruments such as coronagraphs to suppress the star light and wavefront sensing and control systems to cancel the aberrations induced by imperfect telescope optics. Early successes of such a system in ground-based telescopes, employing what is known as extreme adaptive optics, have revealed its potential for future high-contrast imaging in space. The first space-based coronagraph and wavefront sensing and control system will soon fly with NASA’s Wide Field Infra-Red Survey Telescope (WFIRST) in the mid 2020s. In this thesis, we focus on the developments of efficient focal plane wavefront sensing and control (FPWFSC) methods for future space-based coronagraph instruments. FPWFSC is a typical stochastic optimal control problem: it first estimates the aberrated light field based on the deformable mirror (DM) probing commands and images, and then it controls the deformable mirrors to correct the estimated wavefront aberrations. Its performance not only depends on the DM control commands, but also the system modeling accuracy and the DM probing policies. The major contribution of this thesis is improving FPWFSC from these two aspects. We first discuss the application of machine learning methods to the FPWFSC data to correct the system modeling errors. Then, we propose new approaches to efficiently collect wavefront sensing commands and images based on optimal experiment design theory. Simulations and experiments on prototype telescope systems prove that all these new algorithms significantly improve the FPWFSC speed, consequently increasing the available time for exoplanet observations in space. We also discuss the future research directions related to our current work, including but not limited to, the broadband FPWFSC using an integral field spectrograph and the optimal dark hole maintenance using optimal experiment design theory. | - |
dc.language.iso | en | - |
dc.publisher | Princeton, NJ : Princeton University | - |
dc.relation.isformatof | The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu> catalog.princeton.edu </a> | - |
dc.subject | exoplanet | - |
dc.subject | high-contrast imaging | - |
dc.subject | optimal experiment design | - |
dc.subject | system identification | - |
dc.subject | variational Bayesian method | - |
dc.subject | wavefront sensing and control | - |
dc.subject.classification | Aerospace engineering | - |
dc.subject.classification | Optics | - |
dc.subject.classification | Applied physics | - |
dc.title | Efficient wavefront sensing and control for space-based high-contrast imaging | - |
dc.type | Academic dissertations (Ph.D.) | - |
Appears in Collections: | Mechanical and Aerospace Engineering |
Files in This Item:
File | Description | Size | Format | |
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Sun_princeton_0181D_13173.pdf | 4.08 MB | Adobe PDF | View/Download |
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