Publications

Displaying 1 - 6 of 6

Modeling Spiking Neurons without Spikes

August 2, 2024

Author(s)

Jeff Shainline, Bryce Primavera, Ryan O'Loughlin

While spiking neuromorphic hardware holds promise for efficient implementations of artificial intelligence, the impact has been limited due in part to a lack of learning algorithms that achieve performance superior to conventional deep learning. One

Programmable Synapses and Dendritic Circuits for Superconducting Optoelectronic Neuromorphic Computing

May 3, 2024

Author(s)

Bryce Primavera, Saeed Khan, Samuel Adler, Jeff Shainline

Superconducting optoelectronic hardware is promising for large-scale neuromorphic computing. In this work, analog circuits combining Josephson junctions and superconducting single-photon detectors are fabricated and shown to exhibit a variety of

Dendritic Learning in Superconducting Optoelectronic Networks - Elastic Weight Collision at Dynamical Boundaries and Intermittent Validation for Early Convergence

August 28, 2023

Author(s)

Ryan O'Loughlin, Bryce Primavera, Jeff Shainline

Superconducting Optoelectronic Networks (SOENs) combine pho- tonics and superconductors to instantiate computing systems that approach the fundamental limits of information processing in terms of speed and scalability. Overcoming the engineering challenges

Demonstration of Superconducting Optoelectronic Single-Photon Synapses

October 6, 2022

Author(s)

Saeed Khan, Bryce Primavera, Jeff Chiles, Adam McCaughan, Sonia Buckley, Alexander Tait, Adriana Lita, John Biesecker, Anna Fox, David Olaya, Richard Mirin, Sae Woo Nam, Jeff Shainline

Superconducting optoelectronic hardware is being explored as a path towards artificial spiking neural networks with unprecedented scales of complexity and computational ability. Such hardware combines integrated-photonic components for few-photon, light

An active dendritic tree can mitigate fan-in limitations in superconducting neurons

December 13, 2021

Author(s)

Bryce Primavera, Jeff Shainline

Superconducting electronic circuits have much to o er with regard to neuromorphic hardware. Superconducting quantum interference devices (SQUIDs) can serve as an active element to perform the thresholding operation of a neuron's soma. However, a SQUID has

Considerations for neuromorphic supercomputing in semiconducting and superconducting optoelectronic hardware

September 6, 2021

Author(s)

Bryce Primavera, Jeff Shainline

Any large-scale neuromorphic system striving for complexity at the level of the human brain and beyond will need to be co-optimized for communication and computation. Such reasoning leads to the proposal for optoelectronic neuro- morphic platforms that

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