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| 1 | A review:Photonics devices,architectures,and algorithms for optical neural computing显示文摘The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural computing in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives. | Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao | 2021 | Journal of Semiconductors2021，42，2： | 7 |
| 2 | Recent progress of integrated circuits and optoelectronic chips显示文摘Integrated circuits(ICs)and optoelectronic chips are the foundation stones of the modern information society.The IC industry has been driven by the so-called'Moore's law'in the past 60 years,and now has entered the post Moore's law era.In this paper,we review the recent progress of ICs and optoelectronic chips.The research status,technical challenges and development trend of devices,chips and integrated technologies of typical IC and optoelectronic chips are focused on.The main contents include the development law of IC and optoelectronic chip technology,the IC design and processing technology,emerging memory and chip architecture,brain-like chip structure and its mechanism,heterogeneous integration,quantum chip technology,silicon photonics chip technology,integrated microwave photonic chip,and optoelectronic hybrid integrated chip. | Yue HAO Shuiying XIANG Genquan HAN Jincheng ZHANG Xiaohua MA Zhangming ZHU Xingxing GUO Yahui ZHANG Yanan HAN Ziwei SONG Yan LIU Ling YANG Hong ZHOU Jiangyi SHI Wei ZHANG Min XU Weisheng ZHAO Biao PAN Yangqi HUANG Qi LIU Yimao CAI Jian ZHU Xin OU Tiangui YOU Huaqiang WU Bin GAO Zhiyong ZHANG Guoping GUO Yonghua CHEN Yong LIU Xiangfei CHEN Chunlai XUE Xingjun WANG Lixia ZHAO Xihua ZOU Lianshan YAN Ming LI | 2021 | Science China(Information Sciences)2021，64，10： | 7 |
| 3 | Generation of multi-channel chaotic signals with time delay signature concealment and ultrafast photonic decision making based on a globally-coupled semiconductor laser network显示文摘We propose and demonstrate experimentally and numerically a network of three globally coupled semiconductor lasers(SLs)that generate triple-channel chaotic signals with time delayed signature(TDS)concealment.The effects of the coupling strength and bias current on the concealment of the TDS are investigated.The generated chaotic signals are further applied to reinforcement learning,and a parallel scheme is proposed to solve the multiarmed bandit(MAB)problem.The influences of mutual correlation between signals from different channels,the sampling interval of signals,and the TDS concealment on the performance of decision making are analyzed.Comparisons between the proposed scheme and two existing schemes show that,with a simplified algorithm,the proposed scheme can perform as well as the previous schemes or even better.Moreover,we also consider the robustness of decision making performance against a dynamically changing environment and verify the scalability for MAB problems with different sizes.This proposed globally coupled SL network for a multi-channel chaotic source is simple in structure and easy to implement.The attempt to solve the MAB problem in parallel can provide potential values in the realm of the application of ultrafast photonics intelligence. | Yanan Han Shuiying Xiang Yang Wang Yuanting Ma Bo Wang Aijun Wen Yue Hao | 2020 | Photonics Research2020，8，11： | 6 |
| 4 | Enhanced memory capacity of a neuromorphic reservoir computing system based on a VCSEL with double optical feedbacks显示文摘In this paper,a neuromorphic reservoir computing(RC)system with enhanced memory capacity(MC)based on a vertical-cavity surface-emitting laser(VCSEL)subject to double optical feedbacks(DOF)is proposed and investigated numerically.The aim of this study is to explore the MC of the proposed system.For the purpose of comparison,the MC of the VCSEL-based RC system with single optical feedback(SOF)is also taken into account.It is found that,compared with the VCSEL-based RC system subject to SOF,enhanced MC can be obtained for the VCSEL-based RC system with DOF.Besides,the effects of feedback strength,injected strength,frequency detuning as well as injection current on the MC of the VCSEL-based RC system with DOF are considered.Moreover,the influence of feedback delays is also carefully examined.Thus,such proposed VCSEL-based RC system with DOF provides a prospect for the further development of the neuromorphic photonic system based on RC. | Xingxing GUO Shuiying XIANG Yahui ZHANG Aijun WEN Yue HAO | 2020 | Science China(Information Sciences)2020，63，6： | 5 |
| 5 | Delay-weight plasticity-based supervised learning in optical spiking neural networks显示文摘We propose a modified supervised learning algorithm for optical spiking neural networks,which introduces synaptic time-delay plasticity on the basis of traditional weight training.Delay learning is combined with the remote supervised method that is incorporated with photonic spike-timing-dependent plasticity.A spike sequence learning task implemented via the proposed algorithm is found to have better performance than via the traditional weight-based method.Moreover,the proposed algorithm is also applied to two benchmark data sets for classification.In a simple network structure with only a few optical neurons,the classification accuracy based on the delay-weight learning algorithm is significantly improved compared with weight-based learning.The introduction of delay adjusting improves the learning efficiency and performance of the algorithm,which is helpful for photonic neuromorphic computing and is also important specifically for understanding information processing in the biological brain. | Yanan Han Shuiying Xiang Zhenxing Ren Chentao Fu Aijun Wen Yue Hao | 2021 | Photonics Research2021，9，4： | 4 |
| 6 | All-optical neuromorphic binary convolution with a spiking VCSEL neuron for image gradient magnitudes显示文摘All-optical binary convolution with a photonic spiking vertical-cavity surface-emitting laser(VCSEL) neuron is proposed and demonstrated experimentally for the first time, to the best of our knowledge. Optical inputs, extracted from digital images and temporally encoded using rectangular pulses, are injected in the VCSEL neuron,which delivers the convolution result in the number of fast(<100 ps long) spikes fired. Experimental and numerical results show that binary convolution is achieved successfully with a single spiking VCSEL neuron and that alloptical binary convolution can be used to calculate image gradient magnitudes to detect edge features and separate vertical and horizontal components in source images. We also show that this all-optical spiking binary convolution system is robust to noise and can operate with high-resolution images. Additionally, the proposed system offers important advantages such as ultrafast speed, high-energy efficiency, and simple hardware implementation,highlighting the potentials of spiking photonic VCSEL neurons for high-speed neuromorphic image processing systems and future photonic spiking convolutional neural networks. | YAHUI ZHANG JOSHUA ROBERTSON SHUIYING XIANG MATĚJ HEJDA JULIÁN BUENO ANTONIO HURTADO | 2021 | Photonics Research2021，9，5： | 4 |
| 7 | Real-time optical spike-timing dependent plasticity in a single VCSEL with dual-polarized pulsed optical injection显示文摘We propose and numerically realize an optical spike-timing dependent plasticity(STDP)scheme by using a single vertical-cavity surface-emitting laser(VCSEL).In the scheme,the VCSEL is subjected to an orthogonally-polarized continuous-wave optical injection(OPCWOI)and dual-polarized pulsed optical injections(DPPOI).Based on the widely used spin-flip model,the response spiking dynamics of VCSEL is numerically studied,and then the optical STDP in a single VCSEL is explored.The roles of bias current,the strength of OPCWOI and DPPOI,and the frequency detuning on the optical STDP curve are numerically analyzed.It is found that,by simultaneously utilizing the response spiking dynamics in two orthogonal polarization modes,an optical STDP could be achieved by using a single VCSEL.Furthermore,the weight update of STDP curve can be calculated in real-time.Additionally,the STDP curves can also be controlled by adjusting some controllable parameters.The real-time optical STDP based on a single VCSEL is numerically realized for the first time,which paves the way towards fully VCSELs-based photonic neuromorphic systems with low power consumption. | Shuiying XIANG Yanan HAN Xingxing GUO Aijun WEN Genquan HAN Yue HAO | 2020 | Science China(Information Sciences)2020，63，6： | 3 |
| 8 | Photonic integrated spiking neuron chip based on a self-pulsating DFB laser with a saturable absorber显示文摘We proposed and experimentally demonstrated a simple and novel photonic spiking neuron based on a distributed feedback(DFB)laser chip with an intracavity saturable absorber(SA).The DFB laser with an intracavity SA(DFBSA)contains a gain region and an SA region.The gain region is designed and fabricated by the asymmetric equivalentπ-phase shift based on the reconstruction-equivalent-chirp technique.Under properly injected current in the gain region and reversely biased voltage in the SA region,periodic self-pulsation was experimentally observed due to the Q-switching effect.The self-pulsation frequency increases with the increase of the bias current and is within the range of several gigahertz.When the bias current is below the self-pulsation threshold,neuronlike spiking responses appear when external optical stimulus pulses are injected.Experimental results show that the spike threshold,temporal integration,and refractory period can all be observed in the fabricated DFB-SA chip.To numerically verify the experimental findings,a time-dependent coupled-wave equation model was developed,which described the physics processes inside the gain and SA regions.The numerical results agree well with the experimental measurements.We further experimentally demonstrated that the weighted sum output can readily be encoded into the self-pulsation frequency of the DFB-SA neuron.We also benchmarked the handwritten digit classification task with a simple single-layer fully connected neural network.By using the experimentally measured dependence of the self-pulsation frequency on the bias current in the gain region as an activation function,we can achieve a recognition accuracy of 92.2%,which bridges the gap between the continuous valued artificial neural networks and spike-based neuromorphic networks.To the best of our knowledge,this is the first experimental demonstration of a photonic integrated spiking neuron based on a DFB-SA,which shows great potential to realizing large-scale multiwavelength photonic spiking neural network chips. | YUECHUN SHI SHUIYING XIANG XINGXING GUO YAHUI ZHANG HONGJI WANG DIANZHUANG ZHENG YUNA ZHANG YANAN HAN YONG ZHAO XIAOJUN ZHU XIANGFEI CHEN XUN LI YUE HAO | 2023 | Photonics Research2023，11，8： | 2 |
| 9 | Experimental demonstration of pyramidal neuron-like dynamics dominated by dendritic action potentials based on a VCSEL for all-optical XOR classification task显示文摘We experimentally and numerically demonstrate an approach to optically reproduce a pyramidal neuron-like dynamics dominated by dendritic Ca^(2+) action potentials(dCaAPs)based on a vertical-cavity surface-emitting laser(VCSEL)for the first time.The biological pyramidal neural dynamics dominated by dCaAPs indicates that the dendritic electrode evoked somatic spikes with current near threshold but failed to evoke(or evoked less)somatic spikes for higher current intensity.The emulating neuron-like dynamics is performed optically based on the injection locking,spiking dynamics,and damped oscillations in the optically injected VCSEL.In addition,the exclusive OR(XOR)classification task is examined in the VCSEL neuron equipped with the pyramidal neuronlike dynamics dominated by dCaAPs.Furthermore,a single spike or multiple periodic spikes are suggested to express the result of the XOR classification task for enhancing the processing rate or accuracy.The experimental and numerical results show that the XOR classification task is achieved successfully in the VCSEL neuron enabled to mimic the pyramidal neuron-like dynamics dominated by dCaAPs.This work reveals valuable pyramidal neuron-like dynamics in a VCSEL and offers a novel approach to solve XOR classification task with a fast and simple all-optical spiking neural network,and hence shows great potentials for future photonic spiking neural networks and photonic neuromorphic computing. | YAHUI ZHANG SHUIYING XIANG XINGYU CAO SHIHAO ZHAO XINGXING GUO AIJUN WEN YUE HAO | 2021 | Photonics Research2021，9，6： | 2 |
| 10 | Simultaneous unidirectional and bidirectional chaos-based optical communication using hybrid coupling semiconductor lasers显示文摘A simultaneous unidirectional and bidirectional chaos-based optical communication scheme based on a hybrid coupling semiconductor laser system that consists of one center semiconductor laser(CSL)and multiple side semiconductor lasers(SSLs)is proposed numerically.In this scheme,the SSLs oriented in a linear chain mutually couple with the adjacent SSLs and they are subjected to identical unidirectional injections from the CSL which is a chaotic external cavity semiconductor laser.We theoretically analyze the conditions for diferent types of chaos synchronization based on the symmetry operation mechanism and injection-locking mechanism,and numerically investigate the influences of operation parameters,parameter mismatch robustness,chaos pass filtering efects and communication performance of the hybrid coupling semiconductor laser system.The simulation results demonstrate that with proper selection of the unidirectional and mutual coupling conditions,the SSLs can synchronize with each other isochronally and simultaneously synchronize to the CSL completely or laggardly,which enables the proposed system to achieve a unidirectional broadcasting communication from the CSL to the SSLs and a bidirectional communication among the SSLs simultaneously.The proposed scheme is beneficial to the implementation of optical chaos communication networks. | JIANG Ning PAN Wei LUO Bin YAN LianShan XIANG ShuiYing | 2014 | Science China(Information Sciences)2014，57，1： | 2 |
| 11 | Experimental demonstration of coherent photonic neural computing based on a Fabry–Perot laser with a saturable absorber显示文摘As Moore’s law has reached its limits,it is becoming increasingly difficult for traditional computing architectures to meet the demands of continued growth in computing power.Photonic neural computing has become a promising approach to overcome the von Neuman bottleneck.However,while photonic neural networks are good at linear computing,it is difficult to achieve nonlinear computing.Here,we propose and experimentally demonstrate a coherent photonic spiking neural network consisting of Mach–Zehnder modulators(MZMs)as the synapse and an integrated quantum-well Fabry–Perot laser with a saturable absorber(FP-SA)as the photonic spiking neuron.Both linear computation and nonlinear computation are realized in the experiment.In such a coherent architecture,two presynaptic signals are modulated and weighted with two intensity modulation MZMs through the same optical carrier.The nonlinear neuron-like dynamics including temporal integration,threshold,and refractory period are successfully demonstrated.Besides,the effects of frequency detuning on the nonlinear neuron-like dynamics are also explored,and the frequency detuning condition is revealed.The proposed hardware architecture plays a foundational role in constructing a large-scale coherent photonic spiking neural network. | DIANZHUANG ZHENG SHUIYING XIANG XINGXING GUO YAHUI ZHANG BILING GU HONGJI WANG ZHENZHEN XU XIAOJUN ZHU YUECHUN SHI YUE HAO | 2023 | Photonics Research2023，11，1： | 2 |
| 12 | Pattern recognition in multi-synaptic photonic spiking neural networks based on a DFB-SA chip显示文摘Spiking neural networks(SNNs)utilize brain-like spatiotemporal spike encoding for simulating brain functions.Photonic SNN offers an ultrahigh speed and power efficiency platform for implementing high-performance neuromorphic computing.Here,we proposed a multi-synaptic photonic SNN,combining the modified remote supervised learning with delayweight co-training to achieve pattern classification.The impact of multi-synaptic connections and the robustness of the network were investigated through numerical simulations.In addition,the collaborative computing of algorithm and hardware was demonstrated based on a fabricated integrated distributed feedback laser with a saturable absorber(DFB-SA),where 10 different noisy digital patterns were successfully classified.A functional photonic SNN that far exceeds the scale limit of hardware integration was achieved based on time-division multiplexing,demonstrating the capability of hardware-algorithm co-computation. | Yanan Han Shuiying Xiang Ziwei Song Shuang Gao Xingxing Guo Yahui Zhang Yuechun Shi Xiangfei Chen Yue Hao | 2023 | Opto-Electronic Science2023，2，9： | 1 |
| 13 | Quan- tifying chaotic unpredictability of vertical-cavity sur- face-emitting lasers with polarized optical feedback via permutation entropy 显示文摘 | Xiang Shuiying Wei Pan Yan Lianshan | 2011 | IEEE Journal of Selected Topics in Quantum Electronics2011，17，5： | 1 |
| 14 | Photonic integrated neuro-synaptic core for convolutional spiking neural network显示文摘Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network(PSNN).However,they are separately implemented with different photonic materials and devices,hindering the large-scale integration of PSNN.Here,we propose,fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback(DFB)laser with a saturable absorber(DFB-SA).A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation.Furthermore,a fourchannel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network,achieving a recognition accuracy of 87%for the MNIST dataset.The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip. | Shuiying Xiang Yuechun Shi Yahui Zhang Xingxing Guo Ling Zheng Yanan Han Yuna Zhang Ziwei Song Dianzhuang Zheng Tao Zhang Hailing Wang Xiaojun Zhu Xiangfei Chen Min Qiu Yichen Shen Wanhua Zheng Yue Hao | 2023 | Opto-Electronic Advances2023，6，11： | 1 |
| 15 | Conversion of a single-layer ANN to photonic SNN for pattern recognition显示文摘This work presents a complete conversion scheme for photonic spiking neural networks(SNNs).We verified that the output of an artificial neural network(ANN)trained with the simulated optical activation function can be directly converted into the spike rate of a photonic spiking neuron model.To reveal the feasibility of hardware implementation,we considered the effects of different bit precisions of data and weight,noise level,and bias current mismatch on the converted results.The proposed scheme was evaluated using the Deterding vowel,IRIS,TIDIGITS,and MNIST datasets for pattern recognition,and achieved mean accuracies of 95.80%,98.67%,96.19%,and 92.33%,respectively.The proposed scheme can convert an ANN into a photonic SNN with almost no precision loss,and the performance was comparable to that of an ANN trained with the rectified linear unit function.The proposed scheme can enable the high-performance implementation of photonic SNNs. | Yanan HAN Shuiying XIANG Tianrui ZHANG Yahui ZHANG Xingxing GUO Yuechun SHI | 2024 | Science China(Information Sciences)2024，67，1： | 0 |
| 16 | Spiking information processing in a single photonic spiking neuron chip with double integrated electronic dendrites显示文摘Dendrites,branches of neurons that transmit signals between synapses and soma,play a vital role in spiking information processing,such as nonlinear integration of excitatory and inhibitory stimuli.However,the investigation of nonlinear integration of dendrites in photonic neurons and the fabrication of photonic neurons including dendritic nonlinear integration in photonic spiking neural networks(SNNs)remain open problems.Here,we fabricate and integrate two dendrites and one soma in a single Fabry–Perot laser with an embedded saturable absorber(FP-SA)neuron to achieve nonlinear integration of excitatory and inhibitory stimuli.Note that the two intrinsic electrodes of the gain section and saturable absorber(SA)section in the FP-SA neuron are defined as two dendrites for two ports of stimuli reception,with one electronic dendrite receiving excitatory stimulus and the other receiving inhibitory stimulus.The stimuli received by two electronic dendrites are integrated non-linearly in a single FP-SA neuron,which generates spikes for photonic SNNs.The properties of frequency encoding and spatiotemporal encoding are investigated experimentally in a single FP-SA neuron with two electronic dendrites.For SNNs equipped with FP-SA neurons,the range of weights between presynaptic neurons and postsynaptic neurons is varied from negative to positive values by biasing the gain and SA sections of FP-SA neurons.Compared with SNN with all-positive weights realized by only biasing the gain section of photonic neurons,the recognition accuracy of Iris flower data is improved numerically in SNN consisting of FP-SA neurons.The results show great potential for multi-functional integrated photonic SNN chips. | YAHUI ZHANG SHUIYING XIANG XINGXING GUO YANAN HAN YUECHUN SHI XIANGFEI CHEN GENQUAN HAN YUE HAO | 2023 | Photonics Research2023，11，12： | 0 |
| 17 | Nonlinear neural computation in an integrated FP-SA spiking neuron subject to incoherent dual-wavelength optical pulse injections显示文摘Photonic nonlinear computation is the critical cornerstone of photonic neuromorphic computing.As one of the key information function units in the photonic spiking neural networks,the photonic spiking neurons are responsible for the nonlinear computation of the network.Recently,the neuron-like nonlinear computation of the photonic spiking neuron has attracted considerable attention. | Ziwei SONG Shuiying XIANG Xingxing GUO Shuang GAO Biling GU Dianzhuang ZHENG Xiangfei CHEN Yuechun SHI | 2023 | Science China(Information Sciences)2023，66，12： | 0 |
| 18 | Experimental and numerical demonstration of hierarchical time-delay reservoir computing based on cascaded VCSELs with feedback and multiple injections显示文摘In this paper,we propose and demonstrate experimentally and numerically a hierarchical timedelay optical reservoir computing(RC)system based on cascaded vertical-cavity surface-emitting lasers(VCSELs)with feedback and multiple injections.The prediction performance characteristics of the hierarchical time-delay RC system based on cascaded VCSELs under different reservoir layers are compared.Evidently,the prediction performance of the hierarchical time-delay RC system is first improved and saturates as the number of reservoir layers increases.Besides,the impacts of key factors on predicting the hierarchical time-delay RC system are also analyzed in detail experimentally and numerically.This proposed hierarchical time-delay RC system based on VCSELs is useful for the further development of RC systems and may be beneficial to improve the ability of RC systems to solve more complex problems. | Xingxing GUO Shuiying XIANG Xingyu CAO Biling GU | 2024 | Science China(Information Sciences)2024，67，2： | 0 |
| 19 | A modified supervised learning rule for training a photonic spiking neural network to recognize digital patterns显示文摘A modified supervised learning rule which is suitable for training photonic spiking neural networks(SNN)is proposed for the first time.The proposed learning rule is independent of the time intervals between actual spike and desired spike or between presynaptic spike and postsynaptic spike.Based on the proposed supervised learning rule,10 digital images are learned in photonic neural network which consists of 30 presynaptic neurons and 10 postsynaptic neurons.Presynaptic and postsynaptic neurons are photonic neurons based on vertical-cavity surface-emitting lasers with an embedded saturable absorber(VCSEL-SA).The results show that 10 digital images are recognized correctly in photonic SNN after enough training.Additionally,the effects of learning rate,the jitters of learning rate,initial weights distribution of SNN and bias current of postsynaptic neurons(VCSELs-SA)on the recognized error are examined carefully based on the proposed learning rule.To the best of our knowledge,such modified supervised learning rule has not yet been reported,which would contribute to training photonic neural networks,and hence is interesting for neuromorphic photonic systems and pattern recognition. | Yahui ZHANG Shuiying XIANG Xingxing GUO Aijun WEN Yue HAO | 2021 | Science China(Information Sciences)2021，64，2： | 0 |
| 20 | Experimental demonstration of photonic spike-timing-dependent plasticity based on a VCSOA显示文摘We experimentally design two photonic spike-timing-dependent plasticity(STDP) schemes based on a single vertical-cavity semiconductor optical amplifier(VCSOA) and demonstrate the photonic implementation of STDP characteristics. In the first scheme, a single-polarized optical pulse train is injected into the VCSOA, in which a pair of optical pulses with a time difference is designed to emulate the pre-synaptic and post-synaptic spikes. In the second scheme, dual-polarized optical pulses emulating the pre-synaptic and post-synaptic spikes are injected into the single VCSOA. Furthermore, the effects of the initial wavelength detuning and the power of the input optical pulse on the STDP curve are analyzed. The proposed photonic STDP schemes based on a single VCSOA need relatively low bias current and power consumption, and thus,are ideal optical synaptic devices forming key components in the construction of the photonic neuromorphic computing system. | Ziwei SONG Shuiying XIANG Xingyu CAO Shihao ZHAO Yue HAO | 2022 | Science China(Information Sciences)2022，65，8： | 0 |
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