Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing. (C) 2017 Author(s).Fundacao para a Ciencia e a Tecnologia (FCT) [UID/Multi/00631/2013]European Structural and Investment Funds (FEEI) through the Competitiveness and Internationalization Operational Program - COMPETE 2020National Funds through FCT [ALG-01-0145-FEDER-016432/POCI-01-0145-FEDER-016432]European Commission under the project iBROW [645369]project COMBINA [TEC2015-65212-C3-3-PAEI/FEDER UE]Ramon y Cajal fellowshipinfo:eu-repo/semantics/publishedVersio

Symmetry-breaking transitions in networks of nonlinear circuit elements

We investigate a nonlinear circuit consisting of N tunnel diodes in series, which shows close similarities to a semiconductor superlattice or to a neural network. Each tunnel diode is modeled by a three-variable FitzHugh-Nagumo-like system. The tunnel diodes are coupled globally through a load resistor. We find complex bifurcation scenarios with symmetry-breaking transitions that generate multiple fixed points off the synchronization manifold. We show that multiply degenerate zero-eigenvalue bifurcations occur, which lead to multistable current branches, and that these bifurcations are also degenerate with a Hopf bifurcation. These predicted scenarios of multiple branches and degenerate bifurcations are also found experimentally.Comment: 32 pages, 11 figures, 7 movies available as ancillary file

Chaos-based true random number generators

Random number (bit) generators are crucial to secure communications, data transfer and storage, and electronic transactions, to carry out stochastic simulations and to many other applications. As software generated random sequences are not truly random, fast entropy sources such as quantum systems or classically chaotic systems can be viable alternatives provided they generate high-quality random sequences sufficiently fast. The discovery of spontaneous chaos in semiconductor superlattices at room temperature has produced a valuable nanotechnology option. Here we explain a mathematical model to describe spontaneous chaos in semiconductor superlattices at room temperature, solve it numerically to reveal the origin and characteristics of chaotic oscillations, and discuss the limitations of the model in view of known experiments. We also explain how to extract verified random bits from the analog chaotic signal produced by the superlattice.This work has been supported by the Spanish Ministerio de Economía y Competitividad grants FIS2011-28838-C02-01 and MTM2014-56948-C2-2-P

Resonant Tunnelling Optoelectronic Circuits

Nowadays, most communication networks such as local area networks (LANs), metropolitan area networks (MANs), and wide area networks (WANs) have replaced or are about to replace coaxial cable or twisted copper wire with fiber optical cables. Light-wave communication systems comprise a transmitter based on a visible or near-infrared light source, whose carrier is modulated by the information signal to be transmitted, a transmission media such as an optical fiber, eventually utilizing in-line optical amplification, and a receiver based on a photo-detector that recovers the information signal (Liu, 1996)(Einarsson, 1996). The transmitter consists of a driver circuit along a semiconductor laser or a light emitting diode (LED). The receiver is a signal processing circuit coupled to a photo-detector such as a photodiode, an avalanche photodiode (APD), a phototransistor or a high speed photoconductor that processes the photo-detected signal and recovers the primitive information signa

Dynamics of resonant tunneling diode optoelectronic oscillators

Tese de dout., Física, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2012The nonlinear dynamics of optoelectronic integrated circuit (OEIC) oscillators comprising semiconductor resonant tunneling diode (RTD) nanoelectronic quantum devices has been investigated. The RTD devices used in this study oscillate in the microwave band frequency due to the negative di erential conductance (NDC) of their nonlinear current voltage characteristics, which is preserved in the optoelectronic circuit. The aim was to study RTD circuits incorporating laser diodes and photo-detectors to obtain novel dynamical operation regimes in both electrical and optical domains taking advantage of RTD's NDC characteristic. Experimental implementation and characterization of RTD-OEICs was realized in parallel with the development of computational numerical models. The numerical models were based on ordinary and delay di erential equations consisting of a Li enard's RTD oscillator and laser diode single mode rate equations that allowed the analysis of the dynamics of RTD-OEICs. In this work, several regimes of operation are demonstrated, both experimentally and numerically, including generation of voltage controlled microwave oscillations and synchronization to optical and electrical external signals providing stable and low phase noise output signals, and generation of complex oscillations that are characteristic of high-dimensional chaos. Optoelectronic integrated circuits using RTD oscillators are interesting alternatives for more e cient synchronization, generation of stable and low phase noise microwave signals, electrical/optical conversion, and for new ways of optoelectronic chaos generation. This can lead to simpli cation of communication systems by boosting circuits speed while reducing the power and number of components. The applications of RTD-OEICs include operation as optoelectronic voltage controlled oscillators in clock recovery circuit systems, in wireless-photonics communication systems, or in secure communication systems using chaotic waveforms

Intermittency route to chaos and broadband high-frequency generation in semiconductor superlattice coupled to external resonator

We investigate the onset of broadband microwave chaos in the miniband semiconductor superlattice coupled to an external resonator. Our analysis shows that the transition to chaos, which is confirmed by calculation of Lyapunov exponents, is associated with the intermittency scenario. The evolution of the laminar phases and the corresponding Poincare maps with variation of a supercriticality parameter suggest that the observed dynamics can be classified as type I intermittency. We study the spatiotemporal patterns of the charge concentration and discuss how the frequency band of the chaotic current oscillations in semiconductor superlattice depends on the voltage applied

Brain-inspired nanophotonic spike computing:challenges and prospects

Nanophotonic spiking neural networks (SNNs) based on neuron-like excitable subwavelength (submicrometre) devices are of key importance for realizing brain-inspired, power-efficient artificial intelligence (AI) systems with high degree of parallelism and energy efficiency. Despite significant advances in neuromorphic photonics, compact and efficient nanophotonic elements for spiking signal emission and detection, as required for spike-based computation, remain largely unexplored. In this invited perspective, we outline the main challenges, early achievements, and opportunities toward a key-enabling photonic neuro-architecture using III-V/Si integrated spiking nodes based on nanoscale resonant tunnelling diodes (nanoRTDs) with folded negative differential resistance. We utilize nanoRTDs as nonlinear artificial neurons capable of spiking at high-speeds. We discuss the prospects for monolithic integration of nanoRTDs with nanoscale light-emitting diodes and nanolaser diodes, and nanophotodetectors to realize neuron emitter and receiver spiking nodes, respectively. Such layout would have a small footprint, fast operation, and low power consumption, all key requirements for efficient nano-optoelectronic spiking operation. We discuss how silicon photonics interconnects, integrated photorefractive interconnects, and 3D waveguide polymeric interconnections can be used for interconnecting the emitter-receiver spiking photonic neural nodes. Finally, using numerical simulations of artificial neuron models, we present spike-based spatio-temporal learning methods for applications in relevant AI-based functional tasks, such as image pattern recognition, edge detection, and SNNs for inference and learning. Future developments in neuromorphic spiking photonic nanocircuits, as outlined here, will significantly boost the processing and transmission capabilities of next-generation nanophotonic spike-based neuromorphic architectures for energy-efficient AI applications. This perspective paper is a result of the European Union funded research project ChipAI in the frame of the Horizon 2020 Future and Emerging Technologies Open programme.</p

Nonlinear effects in low-dimensional systems: graphene membrane and electron transport in semiconductor superlattices

Mención Internacional en el título de doctorThis PhD dissertation deals with two different topics: Mechanics of graphene from a statistical mechanics approach, where internal interactions and effects due to temperature are considered. And electron dynamics and chaos in semiconductor superlattices, where we aim at enhancing the chaotic behavior, with its applicability to random number generation in mind. It is not our purpose to bridge these two different topics. But we do believe that with the rise of nanotechnology and the ever-increasing interdisciplinary of science, studies where different topics are approached and discussed are highly desirable. Nanotechnology already rules our life. However, it is still surprising how much progress has been achieved without a fully understanding of the physics governing these structures. In particular, out-of-equilibrium behavior and non-linear responses are present in every nanostructure, but, sometimes, it is possible to avoid their effects at large time scales or small interactions. However, the increasing demand of better and/or new performances makes them sometimes unavoidable, or even, desirable. Micro-metric samples of graphene or semiconductor superlattices cannot be studied taking into account every microscopic interaction, which makes it necessary to use mesoscopic models with a certain range of validity. Throughout this work, we have tried to improve our understanding of the topics stated above, using mesoscopic physical models and techniques from statistical mechanics and dynamical systems. We hope that the obtained results will help the scientific community to gain insight into these fascinating topics and will motivate new research in this direction.Spanish Ministerio de Economía y Competitividad (MINECO) Grant No. MTM2014-56948-C2-2-P and FIS2011-28838-C02-01 and Comunidad de Madrid Grant No. P2009/ENE-1597(HYSYCOMB)Programa Oficial de Doctorado en Ciencia e Ingeniería de MaterialesPresidente: Francisco Guinea López.- Secretario: Jesús Salas Martínez.- Vocal: Beatriz Olmos Sánche

Time-reversal symmetry relations for currents in quantum and stochastic nonequilibrium systems

An overview is given of recent advances in the nonequilibrium statistical mechanics of quantum systems and, especially, of time-reversal symmetry relations that have been discovered in this context. The systems considered are driven out of equilibrium by time-dependent forces or by coupling to large reservoirs of particles and energy. The symmetry relations are established for the exchange of energy and particles between the subsystem and its environment. These results have important consequences. In particular, generalizations of the Kubo formula and the Casimir-Onsager reciprocity relations can be deduced beyond linear response properties. Applications to electron quantum transport in mesoscopic semiconducting circuits are discussed.Comment: Chapter contributed to: R. Klages, W. Just, and C. Jarzynski (Eds.), Nonequilibrium Statistical Physics of Small Systems: Fluctuation Relations and Beyond (Wiley-VCH, Weinheim, 2012; ISBN 978-3-527-41094-1

Regenerative memory in time-delayed neuromorphic photonic resonators

We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the FitzHugh-Nagumo model with delayed feedback. This proof-of-concept photonic regenerative memory might constitute a building block for a new class of neuron-inspired photonic memories that can handle high bit-rate optical signals