Developing Single-Laser Sources for Multimodal Coherent Anti-Stokes Raman Scattering Microscopy

Coherent anti-Stokes Raman scattering (CARS) microscopy has developed rapidly and is opening the door to new types of experiments. This work describes the development of new laser sources for CARS microscopy and their use for different applications. It is specifically focused on multimodal nonlinear optical microscopy—the simultaneous combination of different imaging techniques. This allows us to address a diverse range of applications, such as the study of biomaterials, fluid inclusions, atherosclerosis, hepatitis C infection in cells, and ice formation in cells. For these applications new laser sources are developed that allow for practical multimodal imaging. For example, it is shown that using a single Ti:sapphire oscillator with a photonic crystal fiber, it is possible to develop a versatile multimodal imaging system using optimally chirped laser pulses. This system can perform simultaneous two photon excited fluorescence, second harmonic generation, and CARS microscopy. The versatility of the system is further demonstrated by showing that it is possible to probe different Raman modes using CARS microscopy simply by changing a time delay between the excitation beams. Using optimally chirped pulses also enables further simplification of the laser system required by using a single fiber laser combined with nonlinear optical fibers to perform effective multimodal imaging. While these sources are useful for practical multimodal imaging, it is believed that for further improvements in CARS microscopy sensitivity, new excitation schemes are necessary. This has led to the design of a new, high power, extended cavity oscillator that should be capable of implementing new excitation schemes for CARS microscopy as well as other techniques. Our interest in multimodal imaging has led us to other areas of research as well. For example, a fiber-coupling scheme for signal collection in the forward direction is demonstrated that allows for fluorescence lifetime imaging without significant temporal distortion. Also highlighted is an imaging artifact that is unique to CARS microscopy that can alter image interpretation, especially when using multimodal imaging. By combining expertise in nonlinear optics, laser development, fiber optics, and microscopy, we have developed systems and techniques that will be of benefit for multimodal CARS microscopy.

Single-Mode Fiber Refractive Index Sensor Based on Core-Offset Attenuators

Mach-Zehnder and Michelson interferometers using core-offset attenuators were demonstrated. As the relative offset direction of the two attenuators in the Mach-Zehnder interferometer can significantly affect the extinction ratio of the interference pattern, single core-offset attenuator-based sensors appear more robust and repeatable. A novel fiber Michelson interferometer refractive index (RI) sensor was subsequently realized by a single core-offset attenuator and a layer of ~ 500-nm gold coating. The device had a minimum insertion loss of 0.01 dB and maximum extinction ratio over 9 dB. The sensitivity (0.333 nm) of the new sensor to its surrounding RI change (0.01) was found to be comparable to that (0.252 nm) of an identical long period gratings pair Mach-Zehnder interferometric sensor, and its ease of fabrication makes it a low-cost alternative to existing sensing applications.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.