Enhancing Optical Isolator Performance in Nonreciprocal Waveguide Arrays

We investigate the operation of optical isolators based on magneto-optics waveguide arrays beyond the coupled mode analysis. Semi-vectorial beam propagation simulations demonstrate that evanescent tail coupling and the effects of radiation are responsible for degrading the device’s performance. Our analysis suggests that these effects can be mitigated when the array size is scaled up. In addition, we propose the use of radiation blockers in order to offset some of these effects, and we show that they provide a dramatic improvement in performance. Finally, we also study the robustness of the system with respect to fabrication tolerances using the coupled mode theory. We show that small, random variations in the system’s parameters tend to average out as the number of optical guiding channels increases.

On-chip Non-reciprocal Optical Devices Based on Quantum Inspired Photonic Lattices

We propose integrated optical structures that can be used as isolators and polarization splitters based on engineered photonic lattices. Starting from optical waveguide arrays that mimic Fock space (quantum state with a well-defined particle number) representation of a non-interacting two-site Bose Hubbard Hamiltonian, we show that introducing magneto-optic nonreciprocity to these structures leads to a superior optical isolation performance. In the forward propagation direction, an input TM polarized beam experiences a perfect state transfer between the input and output waveguide channels while surface Bloch oscillations block the backward transmission between the same ports. Our analysis indicates a large isolation ratio of 75 dB after a propagation distance of 8mm inside seven coupled waveguides. Moreover, we demonstrate that, a judicious choice of the nonreciprocity in this same geometry can lead to perfect polarization splitting.

Accelerating Diffraction-free Beams in Photonic Lattices

We study nondiffracting accelerating paraxial optical beams in periodic potentials, in both the linear and the nonlinear domains. In particular, we show that only a unique class of z-dependent lattices can support a true accelerating diffractionless beam. Accelerating lattice solitons, autofocusing beams and accelerating bullets in optical lattices are systematically examined.

Supersymmetric Mode Converters

Originally developed in the context of quantum field theory, the concept of supersymmetry can be used to systematically design a new class of optical structures. In this work, we demonstrate how key features arising from optical supersymmetry can be exploited to control the flow of light for mode division multiplexing applications. Superpartner configurations are experimentally realized in coupled optical networks, and the corresponding light dynamics in such systems are directly observed. We show that supersymmetry can be judiciously utilized to remove the fundamental mode of a multimode optical structure, while establishing global phase matching conditions for the remaining set of modes. Along these lines, supersymmetry may serve as a promising platform for versatile optical components with desirable properties and functionalities.

Light Transport in PT-invariant Photonic Structures with Hidden Symmetries

We introduce a recursive bosonic quantization technique for generating classical PT photonic structures that possess hidden symmetries and higher order exceptional points. We study light transport in these geometries and we demonstrate that perfect state transfer is possible only for certain initial conditions. Moreover, we show that for the same propagation direction, left and right coherent transports are not symmetric with field amplitudes following two different trajectories. A general scheme for identifying the conservation laws in such PT-symmetric photonic networks is also presented.

Comparison of Computer-Based and Optical Face Recognition Paradigms

The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB © software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers an acceptable error rate, easy calculation, and a reasonable speed. Finally, in detection and recognition, the performance of the digital model is better than the performance of the optical model.

CHARACTERIZATION OF ASPHALT MATERIALS CONTAINING BIO OIL FROM MICHIGAN WOOD

The objective of this research is to develop sustainable wood-blend bioasphalt and characterize the atomic, molecular and bulk-scale behavior necessary to produce advanced asphalt paving mixtures. Bioasphalt was manufactured from Aspen, Basswood, Red Maple, Balsam, Maple, Pine, Beech and Magnolia wood via a 25 KWt fast-pyrolysis plant at 500 °C and refined into two distinct end forms - non-treated (5.54% moisture) and treated bioasphalt (1% moisture). Michigan petroleum-based asphalt, Performance Grade (PG) 58-28 was modified with 2, 5 and 10% of the bioasphalt by weight of base asphalt and characterized with the gas chromatography-mass spectroscopy (GC-MS), Fourier Transform Infra-red (FTIR) spectroscopy and the automated flocculation titrimetry techniques. The GC-MS method was used to characterize the Carbon-Hydrogen-Nitrogen (CHN) elemental ratio whiles the FTIR and the AFT were used to characterize the oxidative aging performance and the solubility parameters, respectively. For rheological characterization, the rotational viscosity, dynamic shear modulus and flexural bending methods are used in evaluating the low, intermediate and high temperature performance of the bio-modified asphalt materials. 54 5E3 (maximum of 3 million expected equivalent standard axle traffic loads) asphalt paving mixes were then prepared and characterized to investigate their laboratory permanent deformation, dynamic mix stiffness, moisture susceptibility, workability and constructability performance. From the research investigations, it was concluded that: 1) levo, 2, 6 dimethoxyphenol, 2 methoxy 4 vinylphenol, 2 methyl 1-2 cyclopentandione and 4-allyl-2, 6 dimetoxyphenol are the dominant chemical functional groups; 2) bioasphalt increases the viscosity and dynamic shear modulus of traditional asphalt binders; 3) Bio-modified petroleum asphalt can provide low-temperature cracking resistance benefits at -18 °C but is susceptible to cracking at -24 °C; 3) Carbonyl and sulphoxide oxidation in petroleum-based asphalt increases with increasing bioasphalt modifiers; 4) bioasphalt causes the asphaltene fractions in petroleum-based asphalt to precipitate out of the solvent maltene fractions; 5) there is no definite improvement or decline in the dynamic mix behavior of bio-modified mixes at low temperatures; 6) bio-modified asphalt mixes exhibit better rutting performance than traditional asphalt mixes; 7) bio-modified asphalt mixes have lower susceptibility to moisture damage; 8) more field compaction energy is needed to compact bio-modified mixes.