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Andrishak A, Jacob B, L Alves T, Maibohm C, Romeira B, B Nieder J. Free-standing millimeter-range 3D waveguides for on-chip optical interconnects. Sci Rep 2024; 14:18899. [PMID: 39143181 PMCID: PMC11324902 DOI: 10.1038/s41598-024-69522-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 08/06/2024] [Indexed: 08/16/2024] Open
Abstract
Next-generation energy-efficient photonic integrated systems, such as neuromorphic computational chips require efficient heterogeneous integration of ultracompact light sources and photodetectors through highly dense waveguide circuits. However, interconnecting these devices in emitter-receiver communication circuits remains a challenge and an obstacle towards upscaling heterogeneous photonic chips. Here we report on versatile air-cladded free-standing 3D polymer waveguides (OrmoCore, n≈1.5) spanning up to 900 µm in length without intermediate mechanical support structures, microprinted via two-photon polymerization. The presented waveguides are suitable for on-chip out-of-plane light coupling as well as non-connected 3D crossings, needed for high density optical circuits. The waveguides show optical transmission losses of 1.93 dB mm-1 at λ = 635 nm, and of 3.71 dB mm-1 at λ = 830 nm in the wavelength range of GaAs-based microLEDs spectral emission. On-chip imaging for high-precision alignment and TPP microfabrication are performed seamlessly by utilizing the same laser source for both steps, allowing accurate 3D printing on microstructured substrates. As proof of concept, we interconnect two GaAs-based microLEDs via an on-chip microprinted 3D waveguide. Such combined systems can serve as building blocks of future complex integrated heterogeneous photonic networks.
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Affiliation(s)
- Artur Andrishak
- INL - International Iberian Nanotechnology Laboratory, Ultrafast Bio- and Nanophotonics Group, Av. Mestre Veiga, s.n., 4715-330, Braga, Portugal
| | - Bejoys Jacob
- INL - International Iberian Nanotechnology Laboratory, Ultrafast Bio- and Nanophotonics Group, Av. Mestre Veiga, s.n., 4715-330, Braga, Portugal
| | - Tiago L Alves
- INL - International Iberian Nanotechnology Laboratory, Ultrafast Bio- and Nanophotonics Group, Av. Mestre Veiga, s.n., 4715-330, Braga, Portugal
| | - Christian Maibohm
- INL - International Iberian Nanotechnology Laboratory, Ultrafast Bio- and Nanophotonics Group, Av. Mestre Veiga, s.n., 4715-330, Braga, Portugal
| | - Bruno Romeira
- INL - International Iberian Nanotechnology Laboratory, Ultrafast Bio- and Nanophotonics Group, Av. Mestre Veiga, s.n., 4715-330, Braga, Portugal
| | - Jana B Nieder
- INL - International Iberian Nanotechnology Laboratory, Ultrafast Bio- and Nanophotonics Group, Av. Mestre Veiga, s.n., 4715-330, Braga, Portugal.
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2
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Su L, Tian H, Xu Z, Zhang L, Zeng Z, Zhang Y, Zhang Z, Zhang Y, Zhang S, Li H, Liu Y. Controllable non-uniformly distributed spiking cluster generation in broadband optoelectronic oscillator. OPTICS EXPRESS 2024; 32:15573-15585. [PMID: 38859205 DOI: 10.1364/oe.520246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/02/2024] [Indexed: 06/12/2024]
Abstract
An approach to achieve controllable non-uniformly distributed spiking cluster generation is proposed and demonstrated based on an externally-triggered broadband optoelectronic oscillator (OEO). The theory of controlling the distribution of the spiking pulses in a spiking cluster is established. Based on the theory, the dynamic and the distribution characteristics are analyzed and revealed in the stable spiking oscillation state under different externally-injected trigger signal voltages. The peak-voltage envelop of the cluster and the interval of the spiking pulses are demonstrated to have an approximate negative linearity relationship with the externally-injected trigger signal voltage in both the numerical simulation and the experiment, where a square waveform, a trapezoidal waveform, a parabola waveform, and a half-sinusoidal waveform are used as the externally-injected trigger signals. The results indicate that the spiking pulse distribution in the generated spiking cluster can be well controlled through tuning the externally-injected trigger signal voltage. The proposed scheme can be utilized in spiking encoding and reservoir computing.
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3
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Bile A, Tari H, Pepino R, Nabizada A, Fazio E. Photorefraction Simulates Well the Plasticity of Neural Synaptic Connections. Biomimetics (Basel) 2024; 9:231. [PMID: 38667243 PMCID: PMC11047923 DOI: 10.3390/biomimetics9040231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 04/09/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
In recent years, the need for systems capable of achieving the dynamic learning and information storage efficiency of the biological brain has led to the emergence of neuromorphic research. In particular, neuromorphic optics was born with the idea of reproducing the functional and structural properties of the biological brain. In this context, solitonic neuromorphic research has demonstrated the ability to reproduce dynamic and plastic structures capable of learning and storing through conformational changes in the network. In this paper, we demonstrate that solitonic neural networks are capable of mimicking the functional behaviour of biological neural tissue, in terms of synaptic formation procedures and dynamic reinforcement.
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Affiliation(s)
- Alessandro Bile
- Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, Via Scarpa 16, 00161 Roma, Italy; (H.T.); (R.P.); (A.N.); (E.F.)
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4
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Wen J, Zhang H, Wu Z, Wang Q, Yu H, Sun W, Liang B, He C, Xiong K, Pan Y, Zhang Y, Liu Z. All-optical spiking neural network and optical spike-time-dependent plasticity based on the self-pulsing effect within a micro-ring resonator. APPLIED OPTICS 2023; 62:5459-5466. [PMID: 37706863 DOI: 10.1364/ao.493466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/19/2023] [Indexed: 09/15/2023]
Abstract
In this paper, we proposed an all-optical version of photonic spiking neurons and spike-time-dependent plasticity (STDP) based on the nonlinear optical effects within a micro-ring resonator. In this system, the self-pulsing effect was exploited to implement threshold control, and the equivalent pulse energy required for spiking, calculated by multiplying the input pulse power amplitude with its duration, was about 14.1 pJ. The positive performance of the neurons in the excitability and cascadability tests validated the feasibility of this scheme. Furthermore, two simulations were performed to demonstrate that such an all-optical spiking neural network incorporated with STDP could run stably on a stochastic topology. The essence of such an all-optical spiking neural network is a nonlinear spiking dynamical system that combines the advantages of photonics and spiking neural networks (SNNs), promising access to the high speed and lower consumption inherent to optical systems.
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5
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López C. Artificial Intelligence and Advanced Materials. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2208683. [PMID: 36560859 DOI: 10.1002/adma.202208683] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/01/2022] [Indexed: 06/09/2023]
Abstract
Artificial intelligence (AI) is gaining strength, and materials science can both contribute to and profit from it. In a simultaneous progress race, new materials, systems, and processes can be devised and optimized thanks to machine learning (ML) techniques, and such progress can be turned into innovative computing platforms. Future materials scientists will profit from understanding how ML can boost the conception of advanced materials. This review covers aspects of computation from the fundamentals to directions taken and repercussions produced by computation to account for the origins, procedures, and applications of AI. ML and its methods are reviewed to provide basic knowledge of its implementation and its potential. The materials and systems used to implement AI with electric charges are finding serious competition from other information-carrying and processing agents. The impact these techniques have on the inception of new advanced materials is so deep that a new paradigm is developing where implicit knowledge is being mined to conceive materials and systems for functions instead of finding applications to found materials. How far this trend can be carried is hard to fathom, as exemplified by the power to discover unheard of materials or physical laws buried in data.
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Affiliation(s)
- Cefe López
- Instituto de Ciencia de Materiales de Madrid (ICMM), Consejo Superior de Investigaciones Científicas (CSIC), Calle Sor Juana Inés de la Cruz 3, Madrid, 28049, Spain
- Donostia International Physics Centre (DIPC), Paseo Manuel de Lardizábal 4, San Sebastián, 20018, España
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6
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Li T, Li Y, Wang Y, Liu Y, Liu Y, Wang Z, Miao R, Han D, Hui Z, Li W. Neuromorphic Photonics Based on Phase Change Materials. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:nano13111756. [PMID: 37299659 DOI: 10.3390/nano13111756] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 04/19/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
Neuromorphic photonics devices based on phase change materials (PCMs) and silicon photonics technology have emerged as promising solutions for addressing the limitations of traditional spiking neural networks in terms of scalability, response delay, and energy consumption. In this review, we provide a comprehensive analysis of various PCMs used in neuromorphic devices, comparing their optical properties and discussing their applications. We explore materials such as GST (Ge2Sb2Te5), GeTe-Sb2Te3, GSST (Ge2Sb2Se4Te1), Sb2S3/Sb2Se3, Sc0.2Sb2Te3 (SST), and In2Se3, highlighting their advantages and challenges in terms of erasure power consumption, response rate, material lifetime, and on-chip insertion loss. By investigating the integration of different PCMs with silicon-based optoelectronics, this review aims to identify potential breakthroughs in computational performance and scalability of photonic spiking neural networks. Further research and development are essential to optimize these materials and overcome their limitations, paving the way for more efficient and high-performance photonic neuromorphic devices in artificial intelligence and high-performance computing applications.
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Affiliation(s)
- Tiantian Li
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Yijie Li
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Yuteng Wang
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Yuxin Liu
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Yumeng Liu
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Zhan Wang
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Ruixia Miao
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Dongdong Han
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Zhanqiang Hui
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
| | - Wei Li
- Los Alamos National Laboratory, Computer, Computational, and Statistical Sciences Division, Los Alamos, NM 87545, USA
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7
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Buckley SM, Tait AN, McCaughan AN, Shastri BJ. Photonic online learning: a perspective. NANOPHOTONICS 2023; 12:833-845. [PMID: 36909290 PMCID: PMC9995662 DOI: 10.1515/nanoph-2022-0553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/31/2022] [Accepted: 12/03/2022] [Indexed: 06/18/2023]
Abstract
Emerging neuromorphic hardware promises to solve certain problems faster and with higher energy efficiency than traditional computing by using physical processes that take place at the device level as the computational primitives in neural networks. While initial results in photonic neuromorphic hardware are very promising, such hardware requires programming or "training" that is often power-hungry and time-consuming. In this article, we examine the online learning paradigm, where the machinery for training is built deeply into the hardware itself. We argue that some form of online learning will be necessary if photonic neuromorphic hardware is to achieve its true potential.
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Affiliation(s)
- Sonia Mary Buckley
- Applied Physics Division, National Institute of Standards and Technology, Boulder, CO80305, USA
| | - Alexander N. Tait
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON, Canada
| | - Adam N. McCaughan
- Applied Physics Division, National Institute of Standards and Technology, Boulder, CO80305, USA
| | - Bhavin J. Shastri
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON, Canada
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8
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Tamura M, Morison H, Shastri BJ. Inducing optical self-pulsation by electrically tuning graphene on a silicon microring. NANOPHOTONICS 2022; 11:4017-4025. [PMID: 36081448 PMCID: PMC9394513 DOI: 10.1515/nanoph-2022-0077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 04/19/2022] [Indexed: 06/15/2023]
Abstract
A mechanism for self-pulsation in a proposed graphene-on-silicon microring device is studied. The relevant nonlinear effects of two photon absorption, Kerr effect, saturable absorption, free carrier absorption, and dispersion are included in a coupled mode theory framework. We look at the electrical tunability of absorption and the Kerr effect in graphene. We show that the microring can switch from a stable rest state to a self-pulsation state by electrically tuning the graphene under constant illumination. This switching is indicative of a supercritical Hopf bifurcation since the frequency of the pulses is approximately constant at 7 GHz and the amplitudes initial grow with increasing Fermi level. The CMOS compatibility of graphene and the opto-electronic mechanism allows this to device to be fairly easily integrated with other silicon photonic devices.
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Affiliation(s)
- Marcus Tamura
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, Canada
| | - Hugh Morison
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, Canada
| | - Bhavin J. Shastri
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, Canada
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9
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Numerical Demonstration of the Transmission of Low Frequency Fluctuation Dynamics Generated by a Semiconductor Laser with Optical Feedback. PHOTONICS 2022. [DOI: 10.3390/photonics9070483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this paper, the transmission mechanism of the spike information embedded in the low frequency fluctuation (LFF) dynamic in a cascaded laser system is numerically demonstrated. In the cascaded laser system, the LFF waveform is first generated by a drive laser with optical feedback and is then injected into a response laser. The range of crucial system parameters that can make the response laser generate the LFF dynamic is studied, and the effect of parameter mismatch on the transmission of LFF dynamics is explored through a method of symbolic time-series analysis and the index, such as the spike rate and the cross-correlation coefficient. The results show that the mismatch of the pump current has a more significant influence on the transmission of LFF waveforms than that of the internal physical parameter of the laser, such as the linewidth enhancement factor. Moreover, increasing the injection strength can enhance the robustness of LFF transmission. As spikes of the LFF dynamic generated by lasers with optical feedback is similar to the spike of neurons, the results of this paper can help understanding the information transporting and processing inside the photonic neurons.
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10
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Liu B, Xie Y, Jiang X, Ye Y, Song T, Chai J, Tang Q, Feng M. Forecasting stock market with nanophotonic reservoir computing system based on silicon optomechanical oscillators. OPTICS EXPRESS 2022; 30:23359-23381. [PMID: 36225018 DOI: 10.1364/oe.454973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/06/2022] [Indexed: 06/16/2023]
Abstract
The essence of stock market forecasting is to reveal the intrinsic operation rules of stock market, however it is a terribly arduous challenge for investors. The application of nanophotonic technology in the intelligence field provides a new approach for stock market forecasting with its unique advantages. In this work, a novel nanophotonic reservoir computing (RC) system based on silicon optomechanical oscillators (OMO) with photonic crystal (PhC) cavities for stock market forecasting is implemented. The long-term closing prices of four representative stock indexes are accurately forecast with small prediction errors, and the forecasting results with distinct characteristics are exhibited in the mature stock market and emerging stock market separately. Our work offers solutions and suggestions for surmounting the concept drift problem in stock market environment. The comprehensive influence of RC parameters on forecasting performance are displayed via the mapping diagrams, while some intriguing results indicate that the mature stock markets are more sensitive to the variation of RC parameters than the emerging stock markets. Furthermore, the direction trend forecasting results illustrate that our system has certain direction forecasting ability. Additionally, the stock forecasting problem with short listing time and few data in the stock market is solved through transfer learning (TL) in stock sector. The generalization ability (GA) of our nanophotonic reservoir computing system is also verified via four stocks in the same region and industry. Therefore, our work contributes to a novel RC model for stock market forecasting in the nanophotonic field, and provides a new prototype system for more applications in the intelligent information processing field.
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11
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Lu Y, Zhang W, Fu B, He Z. Frequency-switched photonic spiking neurons. OPTICS EXPRESS 2022; 30:21599-21608. [PMID: 36224875 DOI: 10.1364/oe.456583] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 05/20/2022] [Indexed: 06/16/2023]
Abstract
We propose an approach to generate neuron-like spikes of vertical-cavity surface-emitting laser (VCSEL) by multi-frequency switching. A stable temporal spiking sequence has been realized both by numerical simulations and experiments with a pulse width of sub-nanosecond, which is 8 orders of magnitude faster than ones from biological neurons. Moreover, a controllable spiking coding scheme using multi-frequency switching is designed and a sequence with 20 symbols is generated at the speed of up to 1 Gbps by experiment. Furthermore, we investigate the factors related to time delay of spiking generation, including injection strength and frequency detuning. With proper manipulation of detuning frequency, the spiking generation delay can be controlled upto 60 ns, which is 6 times longer than the delay controlled by intensity. The multi-frequency switching provides another manipulation dimension for spiking generation and will be helpful to exploit the abundant spatial-temporal features of spiking neural network. We believe the proposed VCSEL-neuron, as a single physical device for generating spiking signals with variable time delay, will pave the way for future photonic spiking neural networks.
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12
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Lee YJ, On MB, Xiao X, Proietti R, Yoo SJB. Photonic spiking neural networks with event-driven femtojoule optoelectronic neurons based on Izhikevich-inspired model. OPTICS EXPRESS 2022; 30:19360-19389. [PMID: 36221716 DOI: 10.1364/oe.449528] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/16/2022] [Indexed: 06/16/2023]
Abstract
Photonic spiking neural networks (PSNNs) potentially offer exceptionally high throughput and energy efficiency compared to their electronic neuromorphic counterparts while maintaining their benefits in terms of event-driven computing capability. While state-of-the-art PSNN designs require a continuous laser pump, this paper presents a monolithic optoelectronic PSNN hardware design consisting of an MZI mesh incoherent network and event-driven laser spiking neurons. We designed, prototyped, and experimentally demonstrated this event-driven neuron inspired by the Izhikevich model incorporating both excitatory and inhibitory optical spiking inputs and producing optical spiking outputs accordingly. The optoelectronic neurons consist of two photodetectors for excitatory and inhibitory optical spiking inputs, electrical transistors' circuits providing spiking nonlinearity, and a laser for optical spiking outputs. Additional inclusion of capacitors and resistors complete the Izhikevich-inspired optoelectronic neurons, which receive excitatory and inhibitory optical spikes as inputs from other optoelectronic neurons. We developed a detailed optoelectronic neuron model in Verilog-A and simulated the circuit-level operation of various cases with excitatory input and inhibitory input signals. The experimental results closely resemble the simulated results and demonstrate how the excitatory inputs trigger the optical spiking outputs while the inhibitory inputs suppress the outputs. The nanoscale neuron designed in our monolithic PSNN utilizes quantum impedance conversion. It shows that estimated 21.09 fJ/spike input can trigger the output from on-chip nanolasers running at a maximum of 10 Gspike/second in the neural network. Utilizing the simulated neuron model, we conducted simulations on MNIST handwritten digits recognition using fully connected (FC) and convolutional neural networks (CNN). The simulation results show 90% accuracy on unsupervised learning and 97% accuracy on a supervised modified FC neural network. The benchmark shows our PSNN can achieve 50 TOP/J energy efficiency, which corresponds to 100 × throughputs and 1000 × energy-efficiency improvements compared to state-of-art electrical neuromorphic hardware such as Loihi and NeuroGrid.
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13
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Demertzis K, Papadopoulos GD, Iliadis L, Magafas L. A Comprehensive Survey on Nanophotonic Neural Networks: Architectures, Training Methods, Optimization, and Activations Functions. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22030720. [PMID: 35161464 PMCID: PMC8839671 DOI: 10.3390/s22030720] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 01/15/2022] [Accepted: 01/17/2022] [Indexed: 05/15/2023]
Abstract
In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides and other passive optical elements of nanostructured materials, which eliminate the time of simultaneous processing of big groups of data, taking advantage of the quantum perspective, and thus highly increasing the potentials of contemporary intelligent computational systems. This article is an effort to record and study the research that has been conducted concerning the methods of development and materialization of neuromorphic circuits of neural networks of nanophotonic arrangements. In particular, an investigative study of the methods of developing nanophotonic neuromorphic processors, their originality in neuronic architectural structure, their training methods and their optimization was realized along with the study of special issues such as optical activation functions and cost functions. The main contribution of this research work is that it is the first time in the literature that the most well-known architectures, training methods, optimization and activations functions of the nanophotonic networks are presented in a single paper. This study also includes an extensive detailed meta-review analysis of the advantages and disadvantages of nanophotonic networks.
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Affiliation(s)
- Konstantinos Demertzis
- Department of Physics, Faculty of Sciences, Kavala Campus, International Hellenic University, St. Loukas, 654 04 Kavala, Greece; (G.D.P.); (L.M.)
- School of Science & Technology, Informatics Studies, Hellenic Open University, 263 35 Patra, Greece
- Correspondence: or
| | - Georgios D. Papadopoulos
- Department of Physics, Faculty of Sciences, Kavala Campus, International Hellenic University, St. Loukas, 654 04 Kavala, Greece; (G.D.P.); (L.M.)
| | - Lazaros Iliadis
- School of Civil Engineering, Faculty of Mathematics Programming and General Courses, Democritus University of Thrace, Kimmeria, 691 00 Xanthi, Greece;
| | - Lykourgos Magafas
- Department of Physics, Faculty of Sciences, Kavala Campus, International Hellenic University, St. Loukas, 654 04 Kavala, Greece; (G.D.P.); (L.M.)
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Lee G, Baek JH, Ren F, Pearton SJ, Lee GH, Kim J. Artificial Neuron and Synapse Devices Based on 2D Materials. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2021; 17:e2100640. [PMID: 33817985 DOI: 10.1002/smll.202100640] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 03/05/2021] [Indexed: 06/12/2023]
Abstract
Neuromorphic systems, which emulate neural functionalities of a human brain, are considered to be an attractive next-generation computing approach, with advantages of high energy efficiency and fast computing speed. After these neuromorphic systems are proposed, it is demonstrated that artificial synapses and neurons can mimic neural functions of biological synapses and neurons. However, since the neuromorphic functionalities are highly related to the surface properties of materials, bulk material-based neuromorphic devices suffer from uncontrollable defects at surfaces and strong scattering caused by dangling bonds. Therefore, 2D materials which have dangling-bond-free surfaces and excellent crystallinity have emerged as promising candidates for neuromorphic computing hardware. First, the fundamental synaptic behavior is reviewed, such as synaptic plasticity and learning rule, and requirements of artificial synapses to emulate biological synapses. In addition, an overview of recent advances on 2D materials-based synaptic devices is summarized by categorizing these into various working principles of artificial synapses. Second, the compulsory behavior and requirements of artificial neurons such as the all-or-nothing law and refractory periods to simulate a spike neural network are described, and the implementation of 2D materials-based artificial neurons to date is reviewed. Finally, future challenges and outlooks of 2D materials-based neuromorphic devices are discussed.
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Affiliation(s)
- Geonyeop Lee
- Department of Chemical and Biological Engineering, Korea University, Seoul, 02841, Korea
| | - Ji-Hwan Baek
- Department of Material Science and Engineering, Seoul National University, Seoul, 08826, Korea
| | - Fan Ren
- Department of Chemical Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Stephen J Pearton
- Department of Materials Science and Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Gwan-Hyoung Lee
- Department of Material Science and Engineering, Seoul National University, Seoul, 08826, Korea
- Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Korea
- Institute of Engineering Research, Seoul National University, Seoul, 08826, Korea
- Institute of Applied Physics, Seoul National University, Seoul, 08826, Korea
| | - Jihyun Kim
- Department of Chemical and Biological Engineering, Korea University, Seoul, 02841, Korea
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15
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D’Huys O, Veltz R, Dolcemascolo A, Marino F, Barland S. Canard resonance: on noise-induced ordering of trajectories in heterogeneous networks of slow-fast systems. JPHYS PHOTONICS 2021. [DOI: 10.1088/2515-7647/abcbe3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
We analyse the dynamics of a network of semiconductor lasers coupled via their mean intensity through a non-linear optoelectronic feedback loop. We establish experimentally the excitable character of a single node, which stems from the slow-fast nature of the system, adequately described by a set of rate equations with three well separated time scales. Beyond the excitable regime, the system undergoes relaxation oscillations where the nodes display canard dynamics. We show numerically that, without noise, the coupled system follows an intricate canard trajectory, with the nodes switching on one by one. While incorporating noise leads to a better correspondence between numerical simulations and experimental data, it also has an unexpected ordering effect on the canard orbit, causing the nodes to switch on closer together in time. We find that the dispersion of the trajectories of the network nodes in phase space is minimized for a non-zero noise strength, and call this phenomenon canard resonance.
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16
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Time-Multiplexed Spiking Convolutional Neural Network Based on VCSELs for Unsupervised Image Classification. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11041383] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In this work, we present numerical results concerning a multilayer “deep” photonic spiking convolutional neural network, arranged so as to tackle a 2D image classification task. The spiking neurons used are typical two-section quantum-well vertical-cavity surface-emitting lasers that exhibit isomorphic behavior to biological neurons, such as integrate-and-fire excitability and timing encoding. The isomorphism of the proposed scheme to biological networks is extended by replicating the retina ganglion cell for contrast detection in the photonic domain and by utilizing unsupervised spike dependent plasticity as the main training technique. Finally, in this work we also investigate the possibility of exploiting the fast carrier dynamics of lasers so as to time-multiplex spatial information and reduce the number of physical neurons used in the convolutional layers by orders of magnitude. This last feature unlocks new possibilities, where neuron count and processing speed can be interchanged so as to meet the constraints of different applications.
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Dillane M, Lingnau B, Viktorov EA, Dubinkin I, Fedorov N, Kelleher B. Asymmetric excitable phase triggering in an optically injected semiconductor laser. OPTICS LETTERS 2021; 46:440-443. [PMID: 33449048 DOI: 10.1364/ol.410085] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 11/24/2020] [Indexed: 06/12/2023]
Abstract
One of the defining characteristics of excitability is the existence of an excitable threshold: the minimum perturbation amplitude necessary to produce an excitable response. We analyze an optically injected dual state quantum dot laser, previously shown to display a dual state stochastic excitable dynamic. We show that deterministic triggering of this dynamic can be achieved via optical phase perturbations. Further, we demonstrate that there are in fact two asymmetric excitable thresholds in this system corresponding to the two possible directions of optical phase perturbations. For fast enough perturbations, an excitable interval arises, and there is a limit to the perturbation amplitude, above which excitations no longer arise, a phenomenon heretofore unobserved in studies of excitability.
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18
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Song ZW, Xiang SY, Ren ZX, Wang SH, Wen AJ, Hao Y. Photonic spiking neural network based on excitable VCSELs-SA for sound azimuth detection. OPTICS EXPRESS 2020; 28:1561-1573. [PMID: 32121864 DOI: 10.1364/oe.381229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 12/30/2019] [Indexed: 06/10/2023]
Abstract
We propose a photonic spiking neural network (SNN) based on excitable vertical-cavity surface-emitting lasers with an embedded saturable absorber (VCSELs-SA) for emulating the sound azimuth detection function of the brain for the first time. Here, the spike encoding and response properties based on the excitability of VCSELs-SA are employed, and the difference between spike timings of two postsynaptic neurons serves as an indication of sound azimuth. Furthermore, the weight matrix contributing to the successful sound azimuth detection is carefully identified, and the effect of the time interval between two presynaptic spikes is considered. It is found that the weight range that can achieve sound azimuth detection decreases gradually with the increase of the time interval between the sound arriving at the left and right ears. Besides, the effective detection range of the time interval between two presynaptic spikes is also identified, which is similar to that of the biological auditory system, but with a much higher resolution which is at the nanosecond time scale. We further discuss the effect of device variations on the photonic sound azimuth detection. Hence, this photonic SNN is biologically plausible, which has comparable low energy consumption and higher resolution compared with the biological system. This work is valuable for brain-inspired information processing and a promising foundation for more complex spiking information processing implemented by photonic neuromorphic computing systems.
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Dillane M, Dubinkin I, Fedorov N, Erneux T, Goulding D, Kelleher B, Viktorov EA. Excitable interplay between lasing quantum dot states. Phys Rev E 2019; 100:012202. [PMID: 31499912 DOI: 10.1103/physreve.100.012202] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Indexed: 06/10/2023]
Abstract
The optically injected semiconductor laser system has proven to be an excellent source of experimental nonlinear dynamics, particularly regarding the generation of excitable pulses. Typically for low-injection strengths, these pulses are the result of a small above-threshold perturbation of a stable steady state, the underlying physics is well described by the Adler phase equation, and each laser intensity pulse is accompanied by a 2π phase rotation. In this article, we show how, with a dual-state quantum dot laser, a variation of type I excitability is possible that cannot be described by the Adler model. The laser is operated so that emission is from the excited state only. The ground state can be activated and phase locked to the master laser via optical injection while the excited state is completely suppressed. Close to the phase-locking boundary, a region of ground-state emission dropouts correlated to excited-state pulses can be observed. We show that the phase of the ground state undergoes bounded rotations due to interactions with the excited state. We analyze the system both experimentally and numerically and find excellent agreement. Particular attention is devoted to the bifurcation conditions needed for an excitable pulse as well as its time evolution.
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Affiliation(s)
- M Dillane
- Department of Physics, University College Cork, Cork, Ireland
- Tyndall National Institute, University College Cork, Lee Maltings, Dyke Parade, Cork, Ireland
| | - I Dubinkin
- National Research University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia
| | - N Fedorov
- National Research University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia
| | - T Erneux
- Optique Nonlinéaire Théorique, Campus Plaine, CP 231, 1050 Bruxelles, Belgium
| | - D Goulding
- Tyndall National Institute, University College Cork, Lee Maltings, Dyke Parade, Cork, Ireland
- Centre for Advanced Photonics and Process Analysis, Cork Institute of Technology, Cork, Ireland
- Department of Mathematics, Cork Institute of Technology, Cork, Ireland
| | - B Kelleher
- Department of Physics, University College Cork, Cork, Ireland
- Tyndall National Institute, University College Cork, Lee Maltings, Dyke Parade, Cork, Ireland
| | - E A Viktorov
- National Research University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia
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Otupiri R, Garbin B, Krauskopf B, Broderick NGR. Experimental and numerical characterization of an all-fiber laser with a saturable absorber. OPTICS LETTERS 2018; 43:4945-4948. [PMID: 30320790 DOI: 10.1364/ol.43.004945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 09/09/2018] [Indexed: 06/08/2023]
Abstract
We experimentally characterize the pulsing dynamics of a short all-fiber laser consisting of separate gain and absorber sections. Systematically varying the optical pump power for different lengths of the absorber section (ranging from 0.21 to 1.48 m) allows us to map out the qualitative behavior of the system. This identifies three main operational regions: nonlasing, stable Q-switching, and irregular pulsing. When interpreted in terms of the bifurcation structure of the Yamada model, the experimental results are in good qualitative agreement.
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21
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Tait AN, Jayatilleka H, De Lima TF, Ma PY, Nahmias MA, Shastri BJ, Shekhar S, Chrostowski L, Prucnal PR. Feedback control for microring weight banks. OPTICS EXPRESS 2018; 26:26422-26443. [PMID: 30469730 DOI: 10.1364/oe.26.026422] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 07/22/2018] [Indexed: 06/09/2023]
Abstract
Microring weight banks present novel opportunities for reconfigurable, high-performance analog signal processing in photonics. Controlling microring filter response is a challenge due to fabrication variations and thermal sensitivity. Prior work showed continuous weight control of multiple wavelength-division multiplexed signals in a bank of microrings based on calibration and feedforward control. Other prior work has shown resonance locking based on feedback control by monitoring photoabsorption-induced changes in resistance across in-ring photoconductive heaters. In this work, we demonstrate continuous, multi-channel control of a microring weight bank with an effective 5.1 bits of accuracy on 2Gbps signals. Unlike resonance locking, the approach relies on an estimate of filter transmission versus photo-induced resistance changes. We introduce an estimate still capable of providing 4.2 bits of accuracy without any direct transmission measurements. Furthermore, we present a detailed characterization of this response for different values of carrier wavelength offset and power. Feedback weight control renders tractable the weight control problem in reconfigurable analog photonic networks.
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22
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Ma PY, Shastri BJ, Ferreira de Lima T, Huang C, Tait AN, Nahmias MA, Peng HT, Prucnal PR. Simultaneous excitatory and inhibitory dynamics in an excitable laser. OPTICS LETTERS 2018; 43:3802-3805. [PMID: 30067683 DOI: 10.1364/ol.43.003802] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Accepted: 07/11/2018] [Indexed: 06/08/2023]
Abstract
Neocortical systems encode information in electrochemical spike timings, not just mean firing rates. Learning and memory in networks of spiking neurons is achieved by the precise timing of action potentials that induces synaptic strengthening (with excitation) or weakening (with inhibition). Inhibition should be incorporated into brain-inspired spike processing in the optical domain to enhance its information-processing capability. We demonstrate the simultaneous excitatory and inhibitory dynamics in an excitable (i.e., a pulsed) laser neuron, both numerically and experimentally. We investigate the bias strength effect, inhibitory strength effect, and excitatory and inhibitory input timing effect, based on the simulation platform of an integrated graphene excitable laser. We further corroborate these analyses with proof-of-principle experiments utilizing a fiber-based graphene excitable laser, where we introduce inhibition by directly modulating the gain of the laser. This technology may potentially open novel spike-processing functionality for future neuromorphic photonic systems.
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23
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Sub-threshold signal encoding in coupled FitzHugh-Nagumo neurons. Sci Rep 2018; 8:8276. [PMID: 29844354 PMCID: PMC5974132 DOI: 10.1038/s41598-018-26618-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 05/15/2018] [Indexed: 11/09/2022] Open
Abstract
Despite intensive research, the mechanisms underlying the neural code remain poorly understood. Recent work has focused on the response of a single neuron to a weak, sub-threshold periodic signal. By simulating the stochastic FitzHugh-Nagumo (FHN) model and then using a symbolic method to analyze the firing activity, preferred and infrequent spike patterns (defined by the relative timing of the spikes) were detected, whose probabilities encode information about the signal. As not individual neurons but neuronal populations are responsible for sensory coding and information transfer, a relevant question is how a second neuron, which does not perceive the signal, affects the detection and the encoding of the signal, done by the first neuron. Through simulations of two stochastic FHN neurons we show that the encoding of a sub-threshold signal in symbolic spike patterns is a plausible mechanism. The neuron that perceives the signal fires a spike train that, despite having an almost random temporal structure, has preferred and infrequent patterns which carry information about the signal. Our findings could be relevant for sensory systems composed by two noisy neurons, when only one detects a weak external input.
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Abstract
Neurons communicate by brief bursts of spikes separated by silent phases and information may be encoded into the burst duration or through the structure of the interspike intervals. Inspired by the importance of bursting activities in neuronal computation, we have investigated the bursting oscillations of an optically injected quantum dot laser. We find experimentally that the laser periodically switches between two distinct operating states with distinct optical frequencies exhibiting either fast oscillatory or nearly steady state evolutions (two-color bursting oscillations). The conditions for their emergence and their control are analyzed by systematic simulations of the laser rate equations. By projecting the bursting solution onto the bifurcation diagram of a fast subsystem, we show how a specific hysteresis phenomenon explains the transitions between active and silent phases. Since size-controlled bursts can contain more information content than single spikes our results open the way to new forms of neuron inspired optical communication.
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25
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Neuromorphic photonic networks using silicon photonic weight banks. Sci Rep 2017; 7:7430. [PMID: 28784997 PMCID: PMC5547135 DOI: 10.1038/s41598-017-07754-z] [Citation(s) in RCA: 120] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Accepted: 06/29/2017] [Indexed: 12/03/2022] Open
Abstract
Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using “neural compiler” to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.
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Robertson J, Deng T, Javaloyes J, Hurtado A. Controlled inhibition of spiking dynamics in VCSELs for neuromorphic photonics: theory and experiments. OPTICS LETTERS 2017; 42:1560-1563. [PMID: 28409798 DOI: 10.1364/ol.42.001560] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
We report experimentally and theoretically on the controllable inhibition of spiking regimes in a 1300 nm wavelength vertical-cavity surface-emitting laser. Reproducible suppression of spiking dynamics is demonstrated at fast operation speeds (up to sub-ns rates) and with total control on the temporal duration of the spiking inhibition windows. This Letter opens new paths toward a photonic inhibitory neuronal model system for use in future neuromorphic photonic information processing modules and which are able to operate at speeds up to 8 orders of magnitude faster than biological neurons.
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27
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Garbin B, Dolcemascolo A, Prati F, Javaloyes J, Tissoni G, Barland S. Refractory period of an excitable semiconductor laser with optical injection. Phys Rev E 2017; 95:012214. [PMID: 28208426 DOI: 10.1103/physreve.95.012214] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Indexed: 06/06/2023]
Abstract
Injection-locked semiconductor lasers can be brought to a neuronlike excitable regime when parameters are set close to the unlocking transition. Here we study experimentally the response of this system to repeated optical perturbations and observe the existence of a refractory period during which perturbations are not able to elicit an excitable response. The results are analyzed via simulations of a set of dynamical equations which reproduced adequately the experimental results.
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Affiliation(s)
- B Garbin
- Université Côte d'Azur-CNRS, Institut Non Linéaire de Nice, France
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Physics, The University of Auckland, Auckland 1142, New Zealand
| | - A Dolcemascolo
- Université Côte d'Azur-CNRS, Institut Non Linéaire de Nice, France
- Dipartimento di Scienza e Alta Tecnologia, Università dell'Insubria, via Valleggio 11, I-22100 Como, Italy
| | - F Prati
- Dipartimento di Scienza e Alta Tecnologia, Università dell'Insubria, via Valleggio 11, I-22100 Como, Italy
- CNISM, Research Unit of Como, via Valleggio 11, I-22100 Como, Italy
| | - J Javaloyes
- Departament de Física, Universitat de les Illes Baleares, C/ Valldemossa km 7.5, 07122 Mallorca, Spain
| | - G Tissoni
- Université Côte d'Azur-CNRS, Institut Non Linéaire de Nice, France
| | - S Barland
- Université Côte d'Azur-CNRS, Institut Non Linéaire de Nice, France
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28
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Artificial Neuron Based on Integrated Semiconductor Quantum Dot Mode-Locked Lasers. Sci Rep 2016; 6:39317. [PMID: 27991574 PMCID: PMC5171909 DOI: 10.1038/srep39317] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Accepted: 10/19/2016] [Indexed: 11/08/2022] Open
Abstract
Neuro-inspired implementations have attracted strong interest as a power efficient and robust alternative to the digital model of computation with a broad range of applications. Especially, neuro-mimetic systems able to produce and process spike-encoding schemes can offer merits like high noise-resiliency and increased computational efficiency. Towards this direction, integrated photonics can be an auspicious platform due to its multi-GHz bandwidth, its high wall-plug efficiency and the strong similarity of its dynamics under excitation with biological spiking neurons. Here, we propose an integrated all-optical neuron based on an InAs/InGaAs semiconductor quantum-dot passively mode-locked laser. The multi-band emission capabilities of these lasers allows, through waveband switching, the emulation of the excitation and inhibition modes of operation. Frequency-response effects, similar to biological neural circuits, are observed just as in a typical two-section excitable laser. The demonstrated optical building block can pave the way for high-speed photonic integrated systems able to address tasks ranging from pattern recognition to cognitive spectrum management and multi-sensory data processing.
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29
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Jia C, Shastri BJ, Abdukerim N, Rochette M, Prucnal PR, Saad M, Chen LR. Passively synchronized Q-switched and mode-locked dual-band Tm 3+:ZBLAN fiber lasers using a common graphene saturable absorber. Sci Rep 2016; 6:36071. [PMID: 27804993 PMCID: PMC5090962 DOI: 10.1038/srep36071] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 10/11/2016] [Indexed: 12/03/2022] Open
Abstract
Dual-band fiber lasers are emerging as a promising technology to penetrate new industrial and medical applications from their dual-band properties, in addition to providing compactness and environmental robustness from the waveguide structure. Here, we demonstrate the use of a common graphene saturable absorber and a single gain medium (Tm3+:ZBLAN fiber) to implement (1) a dual-band fiber ring laser with synchronized Q-switched pulses at wavelengths of 1480 nm and 1840 nm, and (2) a dual-band fiber linear laser with synchronized mode-locked pulses at wavelengths of 1480 nm and 1845 nm. Q-switched operation at 1480 nm and 1840 nm is achieved with a synchronized repetition rate from 20 kHz to 40.5 kHz. For synchronous mode-locked operation, pulses with full-width at half maximum durations of 610 fs and 1.68 ps at wavelengths of 1480 nm and 1845 nm, respectively, are obtained at a repetition rate of 12.3 MHz. These dual-band pulsed sources with an ultra-broadband wavelength separation of ~360 nm will add new capabilities in applications including optical sensing, spectroscopy, and communications.
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Affiliation(s)
- Chenglai Jia
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec H3A 0E9, Canada
| | - Bhavin J Shastri
- Department of Electrical Engineering, Princeton University, Princeton, NJ, 08544, USA
| | - Nurmemet Abdukerim
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec H3A 0E9, Canada
| | - Martin Rochette
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec H3A 0E9, Canada
| | - Paul R Prucnal
- Department of Electrical Engineering, Princeton University, Princeton, NJ, 08544, USA
| | - Mohammed Saad
- Thorlabs, Inc., 56 Sparta Ave., Newton, NJ, 07860, USA
| | - Lawrence R Chen
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec H3A 0E9, Canada
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30
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Selmi F, Braive R, Beaudoin G, Sagnes I, Kuszelewicz R, Erneux T, Barbay S. Spike latency and response properties of an excitable micropillar laser. Phys Rev E 2016; 94:042219. [PMID: 27841605 DOI: 10.1103/physreve.94.042219] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Indexed: 06/06/2023]
Abstract
We present experimental measurements concerning the response of an excitable micropillar laser with saturable absorber to incoherent as well as coherent perturbations. The excitable response is similar to the behavior of spiking neurons but with much faster time scales. It is accompanied by a subnanosecond nonlinear delay that is measured for different bias pump values. This mechanism provides a natural scheme for encoding the strength of an ultrafast stimulus in the response delay of excitable spikes (temporal coding). Moreover, we demonstrate coherent and incoherent perturbations techniques applied to the micropillar with perturbation thresholds in the range of a few femtojoules. Responses to coherent perturbations assess the cascadability of the system. We discuss the physical origin of the responses to single and double perturbations with the help of numerical simulations of the Yamada model and, in particular, unveil possibilities to control the relative refractory period that we recently evidenced in this system. Experimental measurements are compared to both numerical simulations of the Yamada model and analytic expressions obtained in the framework of singular perturbation techniques. This system is thus a good candidate to perform photonic spike processing tasks in the framework of novel neuroinspired computing systems.
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Affiliation(s)
- F Selmi
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N-Marcoussis, 91460 Marcoussis, France
| | - R Braive
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N-Marcoussis, 91460 Marcoussis, France
- Université Paris Diderot, 5 rue Thomas-Mann, 75013 Paris, France
| | - G Beaudoin
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N-Marcoussis, 91460 Marcoussis, France
| | - I Sagnes
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N-Marcoussis, 91460 Marcoussis, France
| | - R Kuszelewicz
- Neurophotonics Laboratory, CNRS/Université Paris Descartes, 45, rue des Saints-Pères, 75270 Paris, France
| | - T Erneux
- Université Libre de Bruxelles, Optique Nonlinéaire Théorique, Campus Plaine C.P. 231, 1050 Bruxelles, Belgium
| | - S Barbay
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N-Marcoussis, 91460 Marcoussis, France
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