High resolution and freeform optics
Optical testing and analysis
AdvisorKim, Dae Wook
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
EmbargoRelease after 11/02/2019
AbstractThe demand for increasingly sophisticated optics continues to grow for a wide variety of applications, such as in astronomy, industrial manufacturing, medical imaging, and commercial photography. As more advanced fabrication methods are invented, especially for high-resolution or freeform designs, the tools and techniques for optical metrology and analysis must be made more precise, efficient, and robust. This study discusses various approaches for adaptive and dynamic surface or wavefront metrology and analysis which would aid in the ability to have more advanced and innovative optics. Three techniques for improving optical testing and analysis are discussed in this work. The first two are mathematical frameworks, applied in software codes that provide new and improved solutions to challenges arising during optical metrology, e.g., deflectometry measurements and data analysis. Both are based on polynomial basis sets, and are optimized for systems with rectangular apertures. The first is used for reconstructing surfaces or wavefronts from measured slope data and the second uses the measured data to obtain information about possible misalignments or systematic errors in metrology systems. The third is the development of a sensor for measuring wavefront slope data, which allows solutions for optical testing and analysis problems that occur from a limited dynamic range of measurements. The dynamic range of measurement is the range of wavefront slope values (largest and smallest values) that can be measured by a system. The aforementioned sensor uses the modal data fitting methodology described in this work. Each of these topics has been researched, their main concepts tested, and software and (where applicable) hardware solutions developed for them. Simulations and real data analysis are used for verification of these tools and techniques.
Degree ProgramGraduate College
Degree GrantorUniversity of Arizona
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