{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/125605"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/125605","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Signal models and computational methods for robust exoplanet detection","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_has_math":false,"creators":["Taaki, Jamila Serena"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Kamalabadi, Farzad","Kemball, Athol","Shomorony, Ilan","Zhao, Zhizhen Jane"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-08","date_published":"2024-08","updated_at":"2026-07-22T22:25:02Z","subjects":["Optics","Exoplanets","Telescopes","Data Processing","Detection Methods","Light Curve"],"languages":["en","eng"],"rights":["Copyright 2024 Jamila Taaki"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/125605","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kamalabadi, Farzad","Kemball, Athol","Shomorony, Ilan","Zhao, Zhizhen Jane"]},{"key":"dc:creator","label":"Author","values":["Taaki, Jamila Serena"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-08","2024-07-11"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Optics","Exoplanets","Telescopes","Data Processing","Detection Methods","Light Curve"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Jamila Taaki"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/125605"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Jamila Taaki, accepted the attached license on 2024-07-10 at 12:45.","The student, Jamila Taaki, submitted this Dissertation for approval on 2024-07-10 at 12:55.","This Dissertation was approved for publication on 2024-07-11 at 16:43.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21044 on 2025-02-04 at 21:04:52","If an exoplanet is in orbit around a star and in geometric alignment to eclipse the star, time-series flux density measurements of the star-planet system contain a detectable exoplanet signal. Exoplanet signals are masked by various complex instrument and astrophysical noise of fundamentally unknown form. This thesis demonstrates that more realistic and complete signal models improve the detection of exoplanets through two new approaches; i) detection with complete Bayesian noise models and ii) robust, physically motivated, instrument noise models. The first part of this thesis focuses on data analysis for transiting exoplanet instruments. We develop a detector for exoplanet signals, which incorporates a complete noise model. In a typical exoplanet detection pipeline, multiple stages of processing are performed prior to exoplanet signal detection with the goal of reducing noise to an approximate white noise form. Pre-processing of this form can overfit exoplanet signals and lower the detection performance. Our detector uses Bayesian priors to model complex instrument noise in a Neyman-Pearson detection test, without pre-processing. Exoplanet detection is a data- and compute-intensive process requiring a brute-force search through a template set of exoplanet transit signals; we design computational strategies to tractably perform this search. The statistical performance of our Bayesian detector is analyzed by injecting simulated exoplanet signals into Kepler data. This detector demonstrates a relative 3% detection improvement at an equivalent false-alarm rate compared to multi-stage processing; the detection improvement is concentrated in short-orbital-period, low-radius exoplanets. We use joint-detection to analyze three years of short-cadence data from the Transiting Exoplanet Survey Satellite (TESS), and have found 16 new exoplanet candidates. Furthermore, we develop a robust low-rank instrumental noise model to reduce overfitting of astrophysical signals. Target light curves that are physically close (with respect to sensor position) exhibit highly correlated noise signatures. A modified total variation based prior, which encourages correlation among noise estimates for targets that are spatially close on the wide-field imaging sensor, but that also allows discontinuities along sensor boundaries, is used to constrain a low-rank noise model. This constraint is introduced foundationally, such that the full instrumental noise model is solved for based on the spatial correlation prior and jointly for all light curves. We validate the spatial model with both Kepler light curves as well as simulated light curves and the spatial correlation model demonstrates robustness to overfitting of slow-varying astrophysical signals as compared to PCA. The second half of this thesis is focused on direct-exoplanet imaging with starshades. A starshade is a future mission concept where an occulting mask flies in free formation with a telescope to block the light of a star so that dim exoplanets can be imaged in a high-contrast environment. This thesis develops a computationally efficient approach to compute starshade optical simulations using the Bluestein FFT to select spectral samples as per Fourier diffraction theory. This simulation approach is demonstrated using two mission design concepts, the Nancy Grace Roman Space Telescope (NGRST) starshade rendezvous and the Habitable Exoplanet Observatory (HabEx), with realistic simulated exoplanetary scenes comprised of exo-zodiacal dust and a realistic distribution of exoplanet companions."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Signal models and computational methods for robust exoplanet detection"]}]}],"canonical_facts":{"dc:contributor":["Kamalabadi, Farzad","Kemball, Athol","Shomorony, Ilan","Zhao, Zhizhen Jane"],"dc:creator":["Taaki, Jamila Serena"],"dc:date":["2024-08","2024-07-11"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Jamila Taaki, accepted the attached license on 2024-07-10 at 12:45.","The student, Jamila Taaki, submitted this Dissertation for approval on 2024-07-10 at 12:55.","This Dissertation was approved for publication on 2024-07-11 at 16:43.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21044 on 2025-02-04 at 21:04:52","If an exoplanet is in orbit around a star and in geometric alignment to eclipse the star, time-series flux density measurements of the star-planet system contain a detectable exoplanet signal. Exoplanet signals are masked by various complex instrument and astrophysical noise of fundamentally unknown form. This thesis demonstrates that more realistic and complete signal models improve the detection of exoplanets through two new approaches; i) detection with complete Bayesian noise models and ii) robust, physically motivated, instrument noise models. The first part of this thesis focuses on data analysis for transiting exoplanet instruments. We develop a detector for exoplanet signals, which incorporates a complete noise model. In a typical exoplanet detection pipeline, multiple stages of processing are performed prior to exoplanet signal detection with the goal of reducing noise to an approximate white noise form. Pre-processing of this form can overfit exoplanet signals and lower the detection performance. Our detector uses Bayesian priors to model complex instrument noise in a Neyman-Pearson detection test, without pre-processing. Exoplanet detection is a data- and compute-intensive process requiring a brute-force search through a template set of exoplanet transit signals; we design computational strategies to tractably perform this search. The statistical performance of our Bayesian detector is analyzed by injecting simulated exoplanet signals into Kepler data. This detector demonstrates a relative 3% detection improvement at an equivalent false-alarm rate compared to multi-stage processing; the detection improvement is concentrated in short-orbital-period, low-radius exoplanets. We use joint-detection to analyze three years of short-cadence data from the Transiting Exoplanet Survey Satellite (TESS), and have found 16 new exoplanet candidates. Furthermore, we develop a robust low-rank instrumental noise model to reduce overfitting of astrophysical signals. Target light curves that are physically close (with respect to sensor position) exhibit highly correlated noise signatures. A modified total variation based prior, which encourages correlation among noise estimates for targets that are spatially close on the wide-field imaging sensor, but that also allows discontinuities along sensor boundaries, is used to constrain a low-rank noise model. This constraint is introduced foundationally, such that the full instrumental noise model is solved for based on the spatial correlation prior and jointly for all light curves. We validate the spatial model with both Kepler light curves as well as simulated light curves and the spatial correlation model demonstrates robustness to overfitting of slow-varying astrophysical signals as compared to PCA. The second half of this thesis is focused on direct-exoplanet imaging with starshades. A starshade is a future mission concept where an occulting mask flies in free formation with a telescope to block the light of a star so that dim exoplanets can be imaged in a high-contrast environment. This thesis develops a computationally efficient approach to compute starshade optical simulations using the Bluestein FFT to select spectral samples as per Fourier diffraction theory. This simulation approach is demonstrated using two mission design concepts, the Nancy Grace Roman Space Telescope (NGRST) starshade rendezvous and the Habitable Exoplanet Observatory (HabEx), with realistic simulated exoplanetary scenes comprised of exo-zodiacal dust and a realistic distribution of exoplanet companions."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/125605"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Jamila Taaki"],"dc:subject":["Optics","Exoplanets","Telescopes","Data Processing","Detection Methods","Light Curve"],"dc:title":["Signal models and computational methods for robust exoplanet detection"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}