The superconducting Josephson junction shows spiking and bursting behaviors, which have
similarities with neuronal spiking and bursting. This phenomenon had been observed long …

The revolution in artificial intelligence (AI) brings up an enormous storage and data
processing requirement. Large power consumption and hardware overhead have become …

A variety of nonlinear circuits can be tamed to reproduce the main dynamical properties in
neural activities for biological neurons while designing reliable artificial synapses for …

Neuromorphic computing is a broad field that uses biological inspiration to address
computing design. It is being pursued in many hardware technologies, both novel and …

The imitative modelling of processes in the brain of living beings is an ambitious task.
However, advances in the complexity of existing hardware brain models are limited by their …

The transmission and encoding of information in the brain has been the subject of much
research. The aim is to improve biophysical functions and to design reliable artificial …

Neuromorphic computing—which aims to mimic the collective and emergent behavior of the
brain's neurons, synapses, axons, and dendrites—offers an intriguing, potentially disruptive …

As the limits of traditional von Neumann computing come into view, the brain's ability to
communicate vast quantities of information using low-power spikes has become an …

Neuromorphic computing exploits the dynamical analogy between many physical systems
and neuron biophysics. Superconductor systems, in particular, are excellent candidates for …

In superconductors, magnetic fields are quantized into discrete fluxons (flux quanta Φ0),
made of microscopic circulating supercurrents. We introduce a multiterminal synapse …