On-chip photonic synapse

Cheng, Zengguang; Rı́os, Carlos; Pernice, Wolfram H. P.; Wright, C. David; Bhaskaran, Harish

doi:10.1126/sciadv.1700160

Cited by 475 publications

(375 citation statements)

References 33 publications

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“…Cheng et al fabricated a completely integrated photonic synaptic device based on chalcogenide Ge 2 Sb 2 Te 5 (GST), one kind of well‐studied phase change material . The synapse is prepared on the Si 3 N 4 /SiO 2 platform, on which discrete GST and ITO are sputter‐deposited.…”

Section: Emerging Materials‐based Synaptic Devicesmentioning

confidence: 99%

Recent Progress in Photonic Synapses for Neuromorphic Systems

Zhang

Dai

Zhao

et al. 2020

Advanced Intelligent Systems

165

118

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Implementing synaptic functions with electronic devices is critical to achieve neuromorphic systems on the hardware platform, as synapses play important roles in brain computing and memory. Synapses modulated by light signals, which are also referred as photonic synapses, can not only make effective use of the outstanding properties of light to provide devices with ultrahigh propagation speed, high bandwidth and low crosstalk but also provide a noncontact writing method, which can facilitate the evolution of optical wireless communication and operation. More importantly, real‐time image processing can also be performed by photonic synapses which possess temporary memory. Thus far, tremendous efforts have been taken to design and fabricate photonic synapses. Herein, a summary of the development of different kinds of emerging materials utilized in photonic synaptic devices including memristors, field‐effect transistors, and phase change memory is presented, followed by the innovative applications of photonic synapses for neuromorphic systems. Finally, some current challenges and future study directions are discussed.

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Section: Emerging Materials‐based Synaptic Devicesmentioning

confidence: 99%

Recent Progress in Photonic Synapses for Neuromorphic Systems

Zhang

Dai

Zhao

et al. 2020

Advanced Intelligent Systems

165

118

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“…Owing to the complementary metal‐oxide semiconductor (CMOS) compatibility, silicon‐based photonic integrated circuits have shown huge potentials for optical interconnects in the power‐hungry high‐performance computers and data centers. Recently, growing efforts have been directed toward a series of emerging applications in field‐programmable gate arrays, artificial intelligence, quantum optics, optical processor, optical phased array, and so forth. Phase shifter is one of the fundamental building blocks for its diverse variety of functionalities including modulation, wavelength detuning, beam steering, etc.…”

Section: Introductionmentioning

confidence: 99%

Highly Efficient Silicon Photonic Microheater Based on Black Arsenic–Phosphorus

Liu

Wang

et al. 2020

Advanced Optical Materials

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While black phosphorus has shown excellent optoelectronic properties in many aspects, the environmental instability ultimately places limits on its practical applications. Black arsenic–phosphorus (b‐AsP), an alloy of black phosphorus with arsenic atoms, has emerged as a new 2D material with better stability. Recently, the heterostructure via integration of 2D material with nanophotonic waveguides is opening an avenue for many on‐chip applications of phosphorene. However, the thermo‐optic (TO) properties, which are widely used for waveguide heaters, are not studied on b‐AsP yet. Herein, the TO effects of a b‐AsP/silicon van der Waals heterostructure are first investigated and its application as a transparent waveguide heater is demonstrated. A high efficiency of 0.74 nm mW−1 is achieved with a nonresonant and broadband heater based on 20 nm thick b‐AsP, which eliminates the need for enhancement by cavity‐assisted light–matter interaction, and thus allows for compact footprint, broadband operation, and low latency.

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“…[10][11][12][13] Therefore, the emulated synaptic plasticity of STP and LTP render themselves supportive to the sophisticated cognitive function and adaptive behavior pattern.The emphasis on neuroinspired computing so far has been predominantly in electrical stimulation-induced resistance state switching in phase change memories, [14,15] memristors, [16][17][18][19][20][21][22][23][24] as well as transistor-based memories. To achieve artificial synaptic recognition for learning and memory in electronic devices, concomitant plasticity with different timescale is essential.…”

mentioning

confidence: 99%

“…The emphasis on neuroinspired computing so far has been predominantly in electrical stimulation-induced resistance state switching in phase change memories, [14,15] memristors, [16][17][18][19][20][21][22][23][24] as well as transistor-based memories. [25][26][27][28][29][30] In contrast with the existing electrical interconnect power loss as well as the limitation in trigger selectivity and spatially confinement inherently from the computing by electric signal, emerging optical stimulation based synaptic devices can tune the synaptic plasticity enormously by photons with low-power and high-efficiency.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Near‐Infrared‐Irradiation‐Mediated Synaptic Behavior from Tunable Charge‐Trapping Dynamics

Wang

Yang

Fraser

et al. 2019

Adv Elect Materials

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of stimulation will transfer the shortterm memory into long-term memory. To achieve artificial synaptic recognition for learning and memory in electronic devices, concomitant plasticity with different timescale is essential. As a result, the short-term plasticity (STP) modulates the transient dynamical efficacy during the synaptic transmission, while the longterm plasticity (LTP) shows the stabilizing effect by the given stimulation. [10][11][12][13] Therefore, the emulated synaptic plasticity of STP and LTP render themselves supportive to the sophisticated cognitive function and adaptive behavior pattern.The emphasis on neuroinspired computing so far has been predominantly in electrical stimulation-induced resistance state switching in phase change memories, [14,15] memristors, [16][17][18][19][20][21][22][23][24] as well as transistor-based memories. [25][26][27][28][29][30] In contrast with the existing electrical interconnect power loss as well as the limitation in trigger selectivity and spatially confinement inherently from the computing by electric signal, emerging optical stimulation based synaptic devices can tune the synaptic plasticity enormously by photons with low-power and high-efficiency. Therefore, the photonic synapse architecture is considered to be more favorable in handling the von Neumann bottleneck. [31][32][33][34] In addition, photonic synapse based on Parallel information storage coupled with storage density is a major focus for non-volatile memory devices to achieve neuromorphic computing that can work at low power. In this regard, a photoactive charge-trapping medium consisting of inorganic heteronanosheets for the fabrication of a synaptic transistor is demonstrated. This synaptic device senses and responds to near-infrared (NIR) light signals and mimics the memorization and dynamic forgetting process due to the reversible nature of photogenerated charge interaction. Device-level synaptic evolutions from short-term plasticity to long-term plasticity, paired pulse facilitation, and paired pulse depression are realized with light modulation on the weight update terminal. To understand the underlying mechanism of the synaptic behavior under NIR signals, systematic analysis is carried out using in situ atomic force microscopy based electrical techniques. With its photoactive architecture, this information processing analogue is validated for visual object recognition, which paves the way for implementing NIR-controlled neuromorphic computing.

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On-chip photonic synapse

Abstract: An on-chip photonic device mimics the function of synaptic connections between neurons.

Cited by 475 publications

References 33 publications

Recent Progress in Photonic Synapses for Neuromorphic Systems

Recent Progress in Photonic Synapses for Neuromorphic Systems

Highly Efficient Silicon Photonic Microheater Based on Black Arsenic–Phosphorus

Near‐Infrared‐Irradiation‐Mediated Synaptic Behavior from Tunable Charge‐Trapping Dynamics

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