Electromagnetic waves carry information in multiple degrees of freedom, such as amplitude, phase, polarization, coherence, etc. When light encounters physical matter, its properties generally fluctuate in the spatial or the temporal domain. If the structure of matter is complex, these fluctuations may appear random at first glance. However, information about the light-matter interaction can still be recovered from such noise-like signals under certain conditions. Optical sensing or imaging tasks of different approaches can be taken depending on the specific physical problem. In this dissertation, we provide original solutions to several sensing problems based on measurements of intensity fluctuations. First, we will discuss how temporal intensity fluctuations can be used to infer the structural evolution of dynamic scattering media. Then, we will introduce a new and efficient experimental approach for retrieving this dynamic information from complex media in a geometry-independent manner and across a broad range of scattering regimes. In addition, using the process of protein polymerization/depolymerization as an example, we will demonstrate how temporal fluctuations of scattered light can be used to quantify the dynamics of a thermal hysteresis process. The second part of the thesis will discuss the characteristics of intensity fluctuations in both spatial and temporal domains. We will theoretically propose and experimentally demonstrate the statistical nonstationarity of intensity fluctuations in strong scattering media where the mechanisms of recurrent scattering and the near field coupling compete. Furthermore, we will present an experimental procedure for simultaneously assessing the mechanical and optical properties of complex media experiencing structural phase transitions.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2697 |
| Date | 01 January 2022 |
| Creators | Wu, Ruitao |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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