A near-infrared photon-counting system using an InGaAs avalanche photodiode

Maruyama, Tomoyuki; Narusawa, Fumio; Kudo, Makoto; Tanaka, M.; Saito, Yasunori; Yoshida, T; Nomura, Akio

doi:10.1109/cleo.2000.906827

Cited by 3 publications

(3 citation statements)

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“…Among various III-V compound semiconductors, InGaAs is one of the most promising candidates as a NIR sensor [19] due to its high sensitivity to the NIR spectrum. [20][21][22] Therefore, we have employed the InGaAs p-i-n diode as a NIR sensor integrated with an artificial synapse for in-sensor computing.…”

Section: Introductionmentioning

confidence: 99%

Hetero‐Integrated InGaAs Photodiode and Oxide Memristor‐Based Artificial Optical Nerve for In‐Sensor NIR Image Processing

Bae

Park

Lee

et al. 2022

Advanced Optical Materials

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between the sensory and computing nodes in terms of energy consumption, time delay, and system footprint. [4] To alleviate the issue, in-sensor computing has been proposed that can fuse the data acquisition and computing units within a sensory domain. [5] In-sensor computing enables simultaneous sensing and computing on a single chip, reducing data transportation between the building blocks and minimizing the overall system footprint. However, because sensing, memory, and computing functionalities need to be performed in each pixel, in-sensor computing usually requires complicated backplane circuitry compared to the conventional active-matrix image sensor array that detects and stores optical signals in the two-dimensional (2D) structured pixels. [5] In particular, conventional computing units consist of multiple electronic components to effectively process the acquired signals. The complementary-metal-oxide semiconductor (CMOS) technology-based architectures require more than five transistors even for simple arithmetic computation, [6] which significantly increases the complexity of backplane circuitry for in-sensor computing. [5] Unlike the CMOS architectures that process the signals in the digital domain, emerging neuromorphic computing allows in-memory processing in the analog domain, reducing the energy consumption, data processing time, and footprint of the computing devices. [7][8][9] One key component of neuro morphic computing is a non-volatile memristor (NVM) that can store information as a resistance of the active medium. [10,11] The stored information as an analog form (resistance) is deployable to realize the multiply-accumulate (MAC) operation via Ohm's and Kirchhoff's laws. The general mechanisms of resistive switching are the formation (SET) and rupture (RESET) of metal cations or oxygen vacancies. The stochastic distribution of atomic transitions allows the analog resistive switching of the NVM. [12] Based on NVM as a pixel, the memristor crossbar array can process matrix-form information (images), by using an electrical signal as an input. Such a memristor array architecture can be realized for in-sensor neuromorphic vision computing by employing photo-responsive NVMs. [1,13] However, most of the photo-responsive NVMs feature a three-terminal structure, requiring multiple interconnections and a transport channel for each pixel.In-sensor computing is an emerging architectural paradigm that fuses data acquisition and processing within a sensory domain. The integration of multiple functions into a single domain reduces the system footprint while it minimizes the energy and time for data transfer between sensory and computing units. However, it is challenging for a simple and compact image sensor array to achieve both sensing and computing in each pixel. Here, this work demonstrates a focal plane array with a heterogeneously integrated onephotodiode one-resistor (1P-1R)-based artificial optical neuron that emulates the sensing, computing, and memorization of a biological retina system. This work emp...

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Section: Introductionmentioning

confidence: 99%

Hetero‐Integrated InGaAs Photodiode and Oxide Memristor‐Based Artificial Optical Nerve for In‐Sensor NIR Image Processing

Bae

Park

Lee

et al. 2022

Advanced Optical Materials

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“…[7] However, the equivalent input noise of the read-out integrated circuit (ROIC), which determines the detection limit of the PIN-PDs, has been nearly constant over the past 20 years. [8] Fortunately, detectors with an internal amplification mechanism can reduce the input ROIC noise, such as linear-mode APDs, [9] which can enhance the overall system sensitivity compared to PIN-PDs. However, APDs work at high bias voltage and induce excess avalanche noise in the amplification process.…”

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confidence: 99%

Numerical and Experimental Study on the Device Geometry Dependence of Performance of Heterjunction Phototransistors^*

Lu¹,

Chen²,

Li³

et al. 2019

Chinese Phys. Lett.

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Heterojunction phototransistors (HPTs) with scaling emitters have a higher optical gain compared to HPTs with normal emitters. However, to quantitatively describe the relationship between the emitter-absorber area ratio (Ae/Aa) and the performance of HPTs, and to find the optimum value of A e /A a for the geometric structure design, we develop an analytical model for the optical gain of HPTs. Moreover, five devices with different A e/Aa are fabricated to verify the numerical analysis result. As is expected, the measurement result is in good agreement with the analysis model, both of them confirmed that devices with a smaller A e /A a exhibit higher optical gain. The device with area ratio of 0.0625 has the highest optical gain, which is two orders of magnitude larger than that of the device with area ratio of 1 at 3 V. However, the dark current of the device with the area ratio of 0.0625 is forty times higher than that of the device with the area ratio of 1. By calculating the signal-to-noise ratios (SNRs) of the devices, the optimal value of A e /A a can be obtained to be 0.16. The device with the area ratio of 0.16 has the maximum SNR. This result can be used for future design principles for high performance HPTs.

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“…Breakdown voltage V B , an important parameter for APDs applied in both linear mode and Geiger mode, is theoretically defined as the voltage threshold above which the gain is infinite. When experimentally determining the breakdown voltage, other approximate definitions are used, typically defining V B as the reverse bias voltage 1) when the dark current I dark reaches 100 µA [3,4] ; 2) when the multiplication factor (or mean gain) G m reaches 100 [5] ; and 3) when the output pulses exceed 100 mV (0.5 mV at the device) [6] . These definitions are good approximations but will meet their limitations when the APD is used as a SPAD.…”

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confidence: 99%

Determination of breakdown voltage of In0.53Ga0.47As/InP single photon avalanche diodes

Zhou¹,

Liao²,

Wei³

et al. 2011

中国光学快报

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A near-infrared photon-counting system using an InGaAs avalanche photodiode

Cited by 3 publications

References 1 publication

Hetero‐Integrated InGaAs Photodiode and Oxide Memristor‐Based Artificial Optical Nerve for In‐Sensor NIR Image Processing

Hetero‐Integrated InGaAs Photodiode and Oxide Memristor‐Based Artificial Optical Nerve for In‐Sensor NIR Image Processing

Numerical and Experimental Study on the Device Geometry Dependence of Performance of Heterjunction Phototransistors^*

Determination of breakdown voltage of In0.53Ga0.47As/InP single photon avalanche diodes

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A near-infrared photon-counting system using an InGaAs avalanche photodiode

Cited by 3 publications

References 1 publication

Hetero‐Integrated InGaAs Photodiode and Oxide Memristor‐Based Artificial Optical Nerve for In‐Sensor NIR Image Processing

Hetero‐Integrated InGaAs Photodiode and Oxide Memristor‐Based Artificial Optical Nerve for In‐Sensor NIR Image Processing

Numerical and Experimental Study on the Device Geometry Dependence of Performance of Heterjunction Phototransistors*

Determination of breakdown voltage of In0.53Ga0.47As/InP single photon avalanche diodes

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Numerical and Experimental Study on the Device Geometry Dependence of Performance of Heterjunction Phototransistors^*