Topological magnetic and ferroelectric systems for reservoir computing
Topological spin textures in magnetic materials and arrangements of electric dipoles in
ferroelectrics are considered to be promising candidates for next-generation information …
ferroelectrics are considered to be promising candidates for next-generation information …
Two-Dimensional Materials for Brain-Inspired Computing Hardware
Recent breakthroughs in brain-inspired computing promise to address a wide range of
problems from security to healthcare. However, the current strategy of implementing artificial …
problems from security to healthcare. However, the current strategy of implementing artificial …
Quantum-limited stochastic optical neural networks operating at a few quanta per activation
Energy efficiency in computation is ultimately limited by noise, with quantum limits setting the
fundamental noise floor. Analog physical neural networks hold promise for improved energy …
fundamental noise floor. Analog physical neural networks hold promise for improved energy …
Nanoscale Map** of Magnetic Auto-Oscillations with a Single Spin Sensor
Spin Hall nano-oscillators convert DC to magnetic auto-oscillations in the microwave
regime. Current research on these devices is dedicated to creating next-generation energy …
regime. Current research on these devices is dedicated to creating next-generation energy …
Mutual synchronization in spin-torque and spin Hall nano-oscillators
This chapter reviews the state of the art in mutually synchronized spin-torque and spin Hall
nano-oscillator (STNO and SHNO) arrays. After briefly introducing the underlying physics …
nano-oscillator (STNO and SHNO) arrays. After briefly introducing the underlying physics …
Two-Terminal Neuromorphic Devices for Spiking Neural Networks: Neurons, Synapses, and Array Integration
The ever-increasing volume of complex data poses significant challenges to conventional
sequential global processing methods, highlighting their inherent limitations. This …
sequential global processing methods, highlighting their inherent limitations. This …
Pattern recognition using spiking antiferromagnetic neurons
Spintronic devices offer a promising avenue for the development of nanoscale, energy-
efficient artificial neurons for neuromorphic computing. It has previously been shown that …
efficient artificial neurons for neuromorphic computing. It has previously been shown that …
Wavenumber-dependent magnetic losses in YIG-GGG heterostructures at millikelvin temperatures
D Schmoll, AA Voronov, RO Serha… - arxiv preprint arxiv …, 2024 - arxiv.org
Magnons have inspired potential applications in modern quantum technologies and hybrid
quantum systems due to their intrinsic nonlinearity, nanoscale scalability, and a unique set …
quantum systems due to their intrinsic nonlinearity, nanoscale scalability, and a unique set …
Direct design of ground-state probabilistic logic using many-body interactions for probabilistic computing
In this work, an innovative design model aimed at enhancing the efficacy of ground-state
probabilistic logic with a binary energy landscape (GSPL-BEL) is presented. This model …
probabilistic logic with a binary energy landscape (GSPL-BEL) is presented. This model …
Brain-like hardware, do we need it?
The brain's ability to perform efficient and fault-tolerant data processing is strongly related to
its peculiar interconnected adaptive architecture, based on redundant neural circuits …
its peculiar interconnected adaptive architecture, based on redundant neural circuits …