Real-time optical spike-timing dependent plasticity in a single VCSEL with dual-polarized pulsed optical injection

Xiang, Shuiying; Han, Yanan; Guo, Xingxing; Wen, Aijun; Han, Genquan; Hao, Yue

doi:10.1007/s11432-020-2820-y

Cited by 9 publications

(4 citation statements)

References 47 publications

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“…8(e) shows that the STDP curve can be achieved in VC-SOA with low bias current. The calculated STDP window was about 1 ns, indicating that the STDP operation rate was nearly 1 GHz, which is higher than the conventional electronics [45,46] . Furthermore, such photonic STDP curve can also be achieved in real-time with a single VCSEL with dual-polarized pulsed optical injection [47] .…”

Section: Photonic Stdp Based On Vcsoamentioning

confidence: 85%

“…In our experiment, the VCSOA was biased at 1.42 mA, the optical pulse power (width) was 70 μW (100 ps). The energy consumption for biasing the VCSOA and triggering the STDP function could be estimated as several femtojoules per spike, which is much lower than the microelectronic counterparts [45,46] . The experimental measurements are shown in Fig.…”

Section: Photonic Stdp Based On Vcsoamentioning

confidence: 99%

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A review: Photonics devices, architectures, and algorithms for optical neural computing

et al. 2021

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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.

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Section: Photonic Stdp Based On Vcsoamentioning

confidence: 85%

Section: Photonic Stdp Based On Vcsoamentioning

confidence: 99%

A review: Photonics devices, architectures, and algorithms for optical neural computing

et al. 2021

Self Cite

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“…In the past decade, tremendous impressive exploratory studies have been completed, ranging from physical mechanisms, devices, architecture, algorithms, and systems to advance the field of photonic neuromorphic computing, as shown in Figure 17. From the device perspective, it has been proved that various optical devices can emulate the neuron-like [179][180][181] and synapse-like functions [182,183]. There have been numerous attempts to implement photonics spiking neurons like graphene excitable lasers, distributed feedback lasers, vertical-cavity surface-emitting lasers, or micropillars [174,178].…”

Section: Photonic Neuromorphic Computing Chips: From Devices To Integrated Circuitsmentioning

confidence: 99%

Recent progress of integrated circuits and optoelectronic chips

Xiang

Han

Zhang

et al. 2021

Sci. China Inf. Sci.

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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.

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“…Then the brain-like computing system based on photonic spiking neural network (SNN) is expected to replace the traditional electronic system due to ultrafast information processing speed with about 6 orders of magnitude faster than the traditional electronic approaches. Correspondingly, different excitable lasers including vertical-cavity surface-emitting laser (VCSEL) [4][5] , vertical-cavity surface-emitting laser with an embedded saturation absorber (VCSEL-SA) [6][7] , vertical-cavity surface semiconductor optical amplifier (VCSOA) [8][9] , micro-ring laser 10 , micro-disk laser 11 , micro-pillar laser 12 , quantum dot laser 13 have attracted increasing interest and exhibited promising prospect in constructing future ultrafast photonic neural networks 14 . Among these excitability lasers, VCSEL has many advantages, such as low cost 15 , low power consumption, high coupling efficiency to optical fibers, easy integration into two-dimensional or three-dimensional arrays and technology maturity [16][17][18][19][20] .…”

Section: Introductionmentioning

confidence: 99%

Theoretical investigation of ultrafast binary data patterns recognition based on VCSEL-SA

Wang

Xie

Lin

et al. 2022

Optoelectronic Devices and Integration XI

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Based on a vertical-cavity surface-emitting laser with saturated absorber (VCSEL-SA) subject to optical injection, we proposed an ultrafast pattern recognition scheme of four-bit binary data and theoretically investigated the recognition performances. The results show that, patterns recognition of different four-bit binary data at Gb/s rate can be realized by adjusting the injection weight of each bit number and optimal weight values can be determined. Although noise has some influences on the patterns recognition speed and accuracy, this proposed system has a certain robustness to noise on the whole. These results provide a promising application prospect for VCSEL-SA based ultrafast photonic neuromorphic system in pattern recognition field.

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Real-time optical spike-timing dependent plasticity in a single VCSEL with dual-polarized pulsed optical injection

Cited by 9 publications

References 47 publications

A review: Photonics devices, architectures, and algorithms for optical neural computing

A review: Photonics devices, architectures, and algorithms for optical neural computing

Recent progress of integrated circuits and optoelectronic chips

Theoretical investigation of ultrafast binary data patterns recognition based on VCSEL-SA

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