{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/127114"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/127114","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Coronagraphic data post-processing using projections on instrumental modes","abstract":"High 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.","abstract_html":"High 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.","abstract_has_math":false,"creators":["Xin, Yeyuan(Yeyuan Yinzi)"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Aeronautics and Astronautics","school":null,"contributors":[],"advisors":["Kerri Cahoy."],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020","date_published":"2020","updated_at":"2026-07-22T22:21:51Z","subjects":["Aeronautics and Astronautics."],"languages":["eng"],"rights":["MIT 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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/127114","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Kerri Cahoy."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Aeronautics and Astronautics","Aero"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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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.","We 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.","Future 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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Coronagraphic data post-processing using projections on instrumental modes"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kerri Cahoy."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Aeronautics and Astronautics","Aero"],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Aeronautics and Astronautics."],"dc:creator":["Xin, Yeyuan(Yeyuan Yinzi)"],"dc:date.accessioned":["2020-09-03T17:47:35Z"],"dc:date.available":["2020-09-03T17:47:35Z"],"dc:date.issued":["2020"],"dc:description":["Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020","Cataloged from the official PDF of thesis.","Includes bibliographical references (pages 71-76)."],"dc:description.abstract":["High 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.","We 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.","Future 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."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/127114"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT 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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Aeronautics and Astronautics."],"dc:title":["Coronagraphic data post-processing using projections on instrumental modes"],"dc:type":["Thesis"],"thesis:degree_name":["Master"]},"updated_at":"2026-07-22T22:21:51Z"}