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dc.contributor.advisorKerri Cahoy.en_US
dc.contributor.authorXin, Yeyuan(Yeyuan Yinzi)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.en_US
dc.date.accessioned2020-09-03T17:47:35Z
dc.date.available2020-09-03T17:47:35Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/127114
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020en_US
dc.descriptionCataloged from the official PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 71-76).en_US
dc.description.abstractHigh contrast astronomy has yielded the direct observations of over a dozen exoplanets and a multitude of brown dwarfs and circumstellar disks. Despite advances in coronagraphy and wavefront control, high contrast observations are still plagued by residual wavefront aberrations. Post-processing techniques can provide an additional boost in separating residual aberrations from an astrophysical signal. This work explores using a coronagraph instrument model to guide post-processing. We consider the propagation of signals and wavefront error through a coronagraphic instrument, and approach the post-processing problem using "robust observables." We model and approximate the instrument response function of a classical Lyot coronagraph (CLC) and find from it a projection that removes the dominant error modes.en_US
dc.description.abstractWe use this projection to post-process synthetically generated data, and assess the performance of the new model-based post-processing approach compared to using the raw intensity data by calculating their respective flux ratio detection limits. We extend our analysis to include the presence of a dark hole using a simulation of the CLC on the High-contrast imager for complex aperture telescopes (HiCAT) testbed. We find that for non-time-correlated wavefront errors, using the robust observables modestly increases our sensitivity to the signal of a binary companion for most of the range of separations over which our treatment is valid, for example, by up to 50% at 7.5[lambda]/D. For time-correlated wavefront errors, the results vary depending on the test statistic used and degree of correlation. The modest improvement using robust observables with non-time-correlated errors is shown to extend to a CLC with a dark hole created by the stroke minimization algorithm.en_US
dc.description.abstractFuture work exploring the inclusion of statistical whitening processes will allow for a more complete characterization of the robust observables with time-correlated noise. We discuss the dimensionality of coronagraph self-calibration problem and motivate future directions in the joint study of coronagraphy and post-processing.en_US
dc.description.statementofresponsibilityby Yeyuan (Yinzi) Xin.en_US
dc.format.extent76 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectAeronautics and Astronautics.en_US
dc.titleCoronagraphic data post-processing using projections on instrumental modesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.identifier.oclc1191836232en_US
dc.description.collectionS.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronauticsen_US
dspace.imported2020-09-03T17:47:35Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentAeroen_US


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