SIMPEL: Circuit model for photonic spike processing laser neurons

We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber---a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into a circuit model, SPICE analysis can be used as an efficient and accurate engine for numerical calculations, capable of generalization to a variety of different laser neuron types found in literature. The development of this model parallels the Hodgkin--Huxley model of neuron biophysics, a circuit framework which brought efficiency, modularity, and generalizability to the study of neural dynamics. We employ the model to study various signal-processing effects such as excitability with excitatory and inhibitory pulses, binary all-or-nothing response, and bistable dynamics.Comment: 16 pages, 7 figure

Dynamical laser spike processing

Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser systems offer a rich repertoire of useful dynamical behaviors, including the excitable dynamics also found in the time-resolved "spiking" of neurons. Spiking reconciles the expressiveness and efficiency of analog processing with the robustness and scalability of digital processing. We demonstrate that graphene-coupled laser systems offer a unified low-level spike optical processing paradigm that goes well beyond previously studied laser dynamics. We show that this platform can simultaneously exhibit logic-level restoration, cascadability and input-output isolation---fundamental challenges in optical information processing. We also implement low-level spike-processing tasks that are critical for higher level processing: temporal pattern detection and stable recurrent memory. We study these properties in the context of a fiber laser system, but the addition of graphene leads to a number of advantages which stem from its unique properties, including high absorption and fast carrier relaxation. These could lead to significant speed and efficiency improvements in unconventional laser processing devices, and ongoing research on graphene microfabrication promises compatibility with integrated laser platforms.Comment: 13 pages, 7 figure

MAT-761: THE EFFECT OF TEMPERATURE ON THE LATERAL RESPONSE OF UNBONDED FIBER-REINFORCED ELASTOMERIC ISOLATORS

Base isolation is a method that can be employed to significantly reduce the demands on a structure during a seismic event. This method has shown considerable success in reducing the adverse effects of earthquakes, including damage and loss of life. The main concept of base isolation is to reduce the seismic demand on a structure by placing isolators beneath the superstructure at points where load is transferred to the foundation. One of the most commonly used types of isolator is the elastomeric isolator. These isolators are traditionally comprised of layers of elastomer and steel. More recently, research has been completed on the use of fibers as a replacement to the steel reinforcement layers, in order to reduce weight and potentially reduce costs. Fiber reinforced elastomeric isolators (FREI) can be placed (unbonded) between the superstructure and its foundation. This research investigates the behaviour of unbonded fiber-reinforced elastomeric isolators (U-FREI) under lateral deformations expected during seismic events. The objective of this study is to investigate the lateral behaviour of FREI under a range of temperatures, representative of those expected in various regions throughout Canada. Results from preliminary experimental tests show that the influence of temperature on the lateral response of U-FREI is negligible under the range of temperatures considered

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

NDM-563: THE VERTICAL, ROTATIONAL AND LATERAL RESPONSE OF UNBONDED FIBER REINFORCED ELASTOMERIC ISOLATORS

Bridge structures often experience damage during an earthquake, which is one of the most devastating types of natural disasters. Base isolation can be employed to mitigate earthquake-induced damage. The main concept of base isolation is to reduce the seismic demand on the structure by shifting its fundamental time period away from the predominant periods associate with earthquakes. Base isolation involves placing horizontally flexible isolators between the bridge superstructure (i.e. deck/girder) and the substructure (i.e. pier/column). There are two main types of seismic isolators: (1) elastomeric, and (2) sliding. A fiber reinforced elastomeric isolator (FREI) is a particular type of reinforced elastomeric isolator. In an FREI the steel reinforcement used in a traditional elastomeric isolator is replaced with fiber fabric, which results in a reduction in the weight and potentially the manufacturing cost. FREI can be either bonded (B-FREI) or unbonded (U-FREI) to the substructure and superstructure. This paper investigates the behaviour of U-FREI under combined vertical, rotational, and lateral loading, as bridge bearings are expected to experience this combination of loads. Accordingly, the test program includes different vertical loads, angles of rotation, as well as a number of lateral sinusoidal input motions varying in both frequency and amplitude. The objective of this study is to investigate the response of U-FREI under serviceability and extreme loading conditions. The findings of this paper also address the feasibility of using U-FREI as bridge bearings/isolators

Spike processing with a graphene excitable laser.

Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser systems offer a rich repertoire of useful dynamical behaviors, including the excitable dynamics also found in the time-resolved spiking of neurons. Spiking reconciles the expressiveness and efficiency of analog processing with the robustness and scalability of digital processing. We demonstrate a unified platform for spike processing with a graphene-coupled laser system. We show that this platform can simultaneously exhibit logic-level restoration, cascadability and input-output isolation--fundamental challenges in optical information processing. We also implement low-level spike-processing tasks that are critical for higher level processing: temporal pattern detection and stable recurrent memory. We study these properties in the context of a fiber laser system and also propose and simulate an analogous integrated device. The addition of graphene leads to a number of advantages which stem from its unique properties, including high absorption and fast carrier relaxation. These could lead to significant speed and efficiency improvements in unconventional laser processing devices, and ongoing research on graphene microfabrication promises compatibility with integrated laser platforms