2020
DOI: 10.1109/jstqe.2019.2927473
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Fluxonic Processing of Photonic Synapse Events

Abstract: Much of the information processing performed by a neuron occurs in the dendritic tree. For neural systems using light for communication, it is advantageous to convert signals to the electronic domain at synaptic terminals so dendritic computation can be performed with electrical circuits. Here we present circuits based on Josephson junctions and mutual inductors that act as dendrites, processing signals from synapses receiving single-photon communication events with superconducting detectors. We show simulatio… Show more

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Cited by 26 publications
(27 citation statements)
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“…Biological neurons are increasingly recognized as sophisticated computational units (Koch and Segev, 2000 ; Stuart and Spruston, 2015 ; Hawkins and Ahmad, 2016 ; Sardi et al, 2017 ). Emulating such complicated behavior has been the subject of extensive investigation in both semiconducting (Vogelstein et al, 2007 ; Indiveri et al, 2011 ; Brink et al, 2013 ; Pfeil et al, 2013 ; Benjamin et al, 2014 ; Abu-Hassan et al, 2019 ) and superconducting platforms (Crotty et al, 2010 ; Shainline, 2019 ; Toomey et al, 2019 ). We do not attempt a comprehensive review of circuitry, but rather draw attention to issues specific to optoelectronic networks in both cases.…”
Section: Electronic Neuronal Computationmentioning
confidence: 99%
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“…Biological neurons are increasingly recognized as sophisticated computational units (Koch and Segev, 2000 ; Stuart and Spruston, 2015 ; Hawkins and Ahmad, 2016 ; Sardi et al, 2017 ). Emulating such complicated behavior has been the subject of extensive investigation in both semiconducting (Vogelstein et al, 2007 ; Indiveri et al, 2011 ; Brink et al, 2013 ; Pfeil et al, 2013 ; Benjamin et al, 2014 ; Abu-Hassan et al, 2019 ) and superconducting platforms (Crotty et al, 2010 ; Shainline, 2019 ; Toomey et al, 2019 ). We do not attempt a comprehensive review of circuitry, but rather draw attention to issues specific to optoelectronic networks in both cases.…”
Section: Electronic Neuronal Computationmentioning
confidence: 99%
“…Like their CMOS counterparts, many superconducting circuits have now been designed to implement sophisticated neuronal dynamics. Superconducting neuromorphic circuits have been designed to implement a variety of bio-inspired neuron models (Crotty et al, 2010 ; Schneider et al, 2018a ; Toomey et al, 2019 ), dendritic processing (Shainline, 2019 ), and have performed image classification in simulation (Schneider et al, 2017 ). The natural spiking behavior of JJs may even require a lower device count than analogous CMOS circuits for various leaky-integrate-and-fire models (Crotty et al, 2010 ).…”
Section: Electronic Neuronal Computationmentioning
confidence: 99%
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“…Given that nanowires can interface with both CMOS and Josephson junction circuits (Zhao et al, 2017a), it may be possible for nanowire neurons to serve as intermediary devices in a network with both platforms. Indeed, a recently proposed neural network with hybrid technologies employed superconducting nanowires as photon detectors, relying instead on optical signals for facilitating high fan-out (Shainline et al, 2018; Shainline, 2019). Although our work uses nanowires solely as electrical components, they can easily be biased to act as photodetectors (Goltsman et al, 2001; Marsili et al, 2011) as well, illustrating that the two different architectures would be compatible for integration.…”
Section: The Synapsementioning
confidence: 99%
“…In contrast, synchronization is also used to explain brain processes which subserve for development of syntax and its perception [10][11][12]. In general, synchronization theory is highly important to analyze and understand musical acoustics and music psychology [13][14][15][16][17]. While the neurophysiological processes when listening to music remain ongoing research, it is presumed that a certain degree of synchrony can be observed while listening to music and building up expectations.…”
Section: Introductionmentioning
confidence: 99%