3 papers
cs.NE2026
Biologically Realistic Dynamics for Nonlinear Classification in CMOS+X Neurons
Steven Louis, Hannah Bradley, Artem Litvinenko +3
Spiking neural networks encode information in spike timing and offer a pathway toward energy efficient artificial intelligence. However, a key challenge in spiking neural networks…
physics.app-ph2025
A CMOS+X Spiking Neuron With On-Chip Machine Learning
Steven Louis, Matthew Blake Abramson, Hannah Bradley +8
We present the design and numerical simulation of a spiking neuron in a proof-of-concept model of on-chip machine learning. Built within the CMOS+X framework, the spiking neuron co…
cond-mat.mes-hall2025
A Physics-Based Circuit Model for Magnetic Tunnel Junctions
Steven Louis, Hannah Bradley, Artem Litvinenko +1
This work presents an equivalent circuit model for Magnetic Tunnel Junctions (MTJs) that accurately captures their magnetization dynamics and electrical behavior. Implemented in LT…