Design, fabrication and evaluation of chalcogenide glass Luneburg lenses for LiNbO3 integrated optical devices

Optical waveguide Luneburg lenses of arsenic trisulfide glass are described. The lenses are formed by thermal evaporation of As2S3 through suitably placed masks onto the surface of LiNbO3:Ti indiffused waveguides. The lenses are designed for input apertures up to 1 cm and for speeds of f/5 or better. They are designed to focus the TM sub 0 guided mode of a beam of wavelength, external to the guide, of 633 nm. The refractive index of the As2S3 films and the changes induced in the refractive index by exposure to short wavelength light were measured. Some correlation between film thickness and optical properties was noted. The short wavelength photosensitivity was used to shorten the lens focal length from the as deposited value. Lenses of rectangular shape, as viewed from above the guide, as well as conventional circular Luneburg lenses, were made. Measurements made on the lenses include thickness profile, general optical quality, focal length, quality of focal spot, and effect of ultraviolet irradiation on optical properties

Co-Optimization of Communication, Motion and Sensing in Mobile Robotic Operations

In recent years, there has been considerable interest in wireless sensor networks and networked robotic systems. In order to achieve the full potential of such systems, integrative approaches that design the communication, navigation and sensing aspects of the systems simultaneously are needed. However, most of the existing work in the control and robotic communities uses over-simplified disk models or path-loss-only models to characterize the communication in the network, while most of the work in networkingand communication communities does not fully explore the benefits of motion.This dissertation thus focuses on co-optimizing these three aspects simultaneously in realistic communication environments that experience path loss, shadowing and multi-path fading. We show how to integrate the probabilistic channel prediction framework, which allows the robots to predict the channel quality at unvisited locations, into the co-optimization design. In particular, we consider four different scenarios: 1) robotic routerformation, 2) communication and motion energy co-optimization along a pre-defined trajectory, 3) communication and motion energy co-optimization with trajectory planning, and 4) clustering and path planning strategies for robotic data collection. Our theoretical, simulation and experimental results show that the proposed framework considerably outperforms the cases where the communication, motion and sensing aspects of the system are optimized separately, indicating the necessity of co-optimization. They furthershow the significant benefits of using realistic channel models, as compared to the case of using over-simplified disk models

The Holland broadcast language

The broadcast language is a programming formalism devised by Holland in 1975, which aims at allowing Genetic Algorithms (GAs) to use an adaptable representation. A GA may provide an efficient method for adaption but still depends on the efficiency of the fitness function used. During long-term evolution, this efficiency could be limited by the fixed representation used by the GA to encode the problem. When a fitness function is very complex, it is desirable to adapt the problem representation employed by the fitness function. By adapting the representation, the broadcast language may overcome the deficiencies caused by fixed problem representation in GAs. This report describes an initial detailed specification and implementation of the broadcast language. Our first motivation is the fact that there is currently no published implementation of broadcast systems (broadcast language-based systems) available. Despite Holland presented the broadcast language in his book “Adaptation in Natural and Artificial systems”, he did not support this approach with experimental studies. Our second motivation is the affirmation made by Holland that broadcast systems could model biochemical networks. Indeed Holland also described how the broadcast language could provide a straightforward representation to a variety of biochemical networks (Genetic Regulatory Networks, Neural Networks, Immune system etc). As these biochemical models share many similarities with Cell Signaling Networks (CSNs), broadcast systems may also be considered to model CSNs. One of our goals, within the ESIGNET project, is to develop an evolutionary system to realize and evolve CSNs in Silico. Examining the broadcast language may provide us with valuable insights to the development of such a system. In this paper, we initially review the Holland broadcast language, we then propose a specification and implementation of the language which is later illustrated with an experiment: modeling different chemical reactions

Device Modeling and Circuit Design of Neuromorphic Memory Structures

The downscaling of CMOS technology and the benefits gleaned thereof have made it the cornerstone of the semiconductor industry for many years. As the technology reaches its fundamental physical limits, however, CMOS is expected to run out of steam instigating the exploration of new nanoelectronic devices. Memristors have emerged as promising candidates for future computing paradigms, specifically, memory arrays and neuromorphic circuits. Towards this end, this dissertation will explore the use of two memristive devices, namely, Transition Metal Oxide (TMO) devices and Insulator Metal Transition (IMT) devices in constructing neuromorphic circuits. A compact model for TMO devices is first proposed and verified against experimental data. The proposed model, unlike most of the other models present in the literature, leverages the instantaneous resistance of the device as the state variable which facilitates parameter extraction. In addition, a model for the forming voltage of TMO devices is developed and verified against experimental data and Monte Carlo simulations. Impact of the device geometry and material characteristics of the TMO device on the forming voltage is investigated and techniques for reducing the forming voltage are proposed. The use of TMOs in syanptic arrays is then explored and a multi-driver write scheme is proposed that improves their performance. The proposed technique enhances voltage delivery across the selected cells via suppressing the effective line resistance and leakage current paths, thus, improving the performance of the crossbar array. An IMT compact model is also developed and verified against experiemntal data and electro-thermal device simulations. The proposed model describes the device as a memristive system with the temperature being the state variable, thus, capturing the temperature dependent resistive switching of the IMT device in a compact form suitable for SPICE implementation. An IMT based Integrate-And-Fire neuron is then proposed. The IMT neuron leverages the temperature dynamics of the device to deliver the functionality of the neuron. The proposed IMT neuron is more compact than its CMOS counterparts as it alleviates the need for complex CMOS circuitry. Impact of the IMT device parameters on the neuron\u27s performance is then studied and design considerations are provided

S/W Fault-tolerant OFP System for UAVs based on Partition Computing

AbstractPartition computing of the new Integrated Modular Avionics architecture reduces the heavy cabling of traditional federated architecture. On the other hand, fault-tolerant Operational Flight Programs (OFP) for unmanned aerial vehicles have usually been implemented as primary-backup systems based on dual nodes. However, in the case of a small UAV, it is preferred to implement a S/W fault-tolerant system that runs primary and recovery systems together in a single flight control computer to reduce the payload. In this case, because the primary and backup must not interfere with each other in using CPU and memory, it is common to use virtualization-based partitions. In this paper, a new S/W fault-tolerant OFP based on the real-time-object partition, TMO.p, is presented to overcome the large overheads of virtualization approaches

Dimensionality Control of Electronic Phase Transitions in Nickel-Oxide Superlattices

The competition between collective quantum phases in materials with strongly correlated electrons depends sensitively on the dimensionality of the electron system, which is difficult to control by standard solid-state chemistry. We have fabricated superlattices of the paramagnetic metal LaNiO3 and the wide-gap insulator LaAlO3 with atomically precise layer sequences. Using optical ellipsometry and low-energy muon spin rotation, superlattices with LaNiO3 as thin as two unit cells are shown to undergo a sequence of collective metalinsulator and antiferromagnetic transitions as a function of decreasing temperature, whereas samples with thicker LaNiO3 layers remain metallic and paramagnetic at all temperatures. Metal-oxide superlattices thus allow control of the dimensionality and collective phase behavior of correlated-electron systems