A delay model for noise-induced bi-directional switching

Many biological systems can switch between two distinct states. Once switched, the system remains stable for a period of time and may switch back to its original state. A gene network with bistability is usually required for the switching and stochastic effect in the gene expression may induce such switching. A typical bistable system allows one-directional switching, in which the switch from the low state to the high state or from the high state to the low state occurs under different conditions. It is usually difficult to enable bi-directional switching such that the two switches can occur under the same condition. Here, we present a model consisting of standard positive feedback loops and an extra negative feedback loop with a time delay to study its capability to produce bi-directional switching induced by noise. We find that the time delay in the negative feedback is critical for robust bi-directional switching and the length of delay affects its switching frequency.

Phase control of switching from positive to negative index material in a four-level atomic system

Electric and magnetic responses of the medium to the probe field are analysed in a four-level loop atomic system by taking into account the relative phase of the applied fields. An interesting phenomenon is found: under suitable conditions, a change of the refractive index from positive to negative can occur by modulating the relative phase of the applied fields. Then the medium can be switched from a positive index material to a negative index material in our scheme. In addition, a negative index material can be realized in different frequency regions by adjusting the relative phase. It may give us a convenient way to obtain the desired material with positive or negative index.

Neural network design for switching network control

A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.

Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.

Exploring the Kinetics of Domain Switching in Ferroelectrics for Structural Applications

The complex domain structure in ferroelectrics gives rise to electromechanical coupling, and its evolution (via domain switching) results in a time-dependent (i.e. viscoelastic) response. Although ferroelectrics are used in many technological applications, most do not attempt to exploit the viscoelastic response of ferroelectrics, mainly due to a lack of understanding and accurate models for their description and prediction. Thus, the aim of this thesis research is to gain better understanding of the influence of domain evolution in ferroelectrics on their dynamic mechanical response. There have been few studies on the viscoelastic properties of ferroelectrics, mainly due to a lack of experimental methods. Therefore, an apparatus and method called Broadband Electromechanical Spectroscopy (BES) was designed and built. BES allows for the simultaneous application of dynamic mechanical and electrical loading in a vacuum environment. Using BES, the dynamic stiffness and loss tangent in bending and torsion of a particular ferroelectric, viz. lead zirconate titanate (PZT), was characterized for different combinations of electrical and mechanical loading frequencies throughout the entire electric displacement hysteresis. Experimental results showed significant increases in loss tangent (by nearly an order of magnitude) and compliance during domain switching, which shows promise as a new approach to structural damping. A continuum model of the viscoelasticity of ferroelectrics was developed, which incorporates microstructural evolution via internal variables and associated kinetic relations. For the first time, through a new linearization process, the incremental dynamic stiffness and loss tangent of materials were computed throughout the entire electric displacement hysteresis for different combinations of mechanical and electrical loading frequencies. The model accurately captured experimental results. Using the understanding gained from the characterization and modeling of PZT, two applications of domain switching kinetics were explored by using Micro Fiber Composites (MFCs). Proofs of concept of set-and-hold actuation and structural damping using MFCs were demonstrated.

Experimental study of nonlinear switching characteristics of conventional 2×2 fused tapered couplers

The nonlinear switching characteristics of fused fiber directional couplers were studied experimentally. By using femtosecond laser pulses with pulse width of 100 fs and wavelength of about 1550 nm from a system of Ti:sapphire laser and optical parametric amplifier (OPA), the nonlinear switching properties of a null coupler and a 100% coupler were measured. The experimental results were coincident with the simulations based on nonlinear propagation equations in fiber by using super-mode theory. Nonlinear loss in fiber was also measured to get the injected power at the coupler. After deducting the nonlinear loss and input efficiency, the nonlinear switching critical peak powers for a 100% and a null fused couplers were calculated to be 9410 and 9440 W, respectively. The nonlinear loss parameter P_(N) in an expression of α_(NL)=αP/P_(N) was obtained to be P_(N)=0.23 W.

Design and evaluation of an optical switching node

[EN]For a good development of elastic optical networks, the design of flexible optical switching nodes is required. This work analyses the previously proposed flexible architectures and, based on the most appropriate, which is the Architecture on Demand (AoD), proposes a specific configuration of the node that includes spatial and spectral switching and the wavelength conversion functionality with a low blocking probability and the minimum amount of modules; the characteristics of the traffic that the designed node is able to cope with are specified in the last chapter. An evaluation of the designed node is also done, and, compared to the other architectures, it is shown that the Architecture on Demand gives better results than others and that it has a higher potential for future developments.