collaborators

5 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…

physics.app-ph2025

Spintronic Neuron Using a Magnetic Tunnel Junction for Low-Power Neuromorphic Computing

Steven Louis, Hannah Bradley, Cody Trevillian +2

This paper proposes a novel spiking artificial neuron design based on a combined spin valve/magnetic tunnel junction (SV/MTJ). Traditional hardware used in artificial intelligence…

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…

cond-mat.mes-hall2025

Equivalent Electric Model of a Macrospin

Steven Louis, Hannah Bradley, Vasyl Tyberkevych

Dynamics of a ferromagnetic macrospin (e.g., a free layer of a magnetic tunnel junction (MTJ)) can be described in terms of equivalent capacitor charge and inductor flux ,…