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

arXiv: https://arxiv.org/abs/2107.05777 · HTML: https://mlsanity.com/paper/2107.05777/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 63 references that are in the map.
- First posted on arXiv 12 Jul 2021.

## Builds on (most cited first, 7 of 7)

- [A Survey of Neuromorphic Computing and Neural Networks in Hardware](https://mlsanity.com/paper/1705.06963/) (2017)
- [Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex](https://mlsanity.com/paper/1511.00083/) (2015)
- [Superconducting optoelectronic circuits for neuromorphic computing](https://mlsanity.com/paper/1610.00053/) (2016)
- [Synchronization dynamics on the picosecond timescale in coupled Josephson junction neurons](https://mlsanity.com/paper/1608.04680/) (2016)
- [Optoelectronic Intelligence](https://mlsanity.com/paper/2010.08690/) (2020)
- [Circuit designs for superconducting optoelectronic loop neurons](https://mlsanity.com/paper/1805.01947/) (2018)
- [Fluxonic Processing of Photonic Synapse Events](https://mlsanity.com/paper/1904.02807/) (2019)

## Built on by (most cited first, 2 of 2)

- [The Promise of Analog Deep Learning: Recent Advances, Challenges and Opportunities](https://mlsanity.com/paper/2406.12911/) (2024)
- [Demonstration of Superconducting Optoelectronic Single-Photon Synapses](https://mlsanity.com/paper/2204.09665/) (2022)

## Abstract (arXiv)

Superconducting electronic circuits have much to offer 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 a response function that is periodic in the applied signal. We show theoretically that if one restricts the total input to a SQUID to maintain a monotonically increasing response, a large fraction of synapses must be active to drive a neuron to threshold. We then demonstrate that an active dendritic tree (also based on SQUIDs) can significantly reduce the fraction of synapses that must be active to drive the neuron to threshold. In this context, the inclusion of a dendritic tree provides the dual benefits of enhancing the computational abilities of each neuron and allowing the neuron to spike with sparse input activity.