884 citations · 1.3k across the 18 of their papers we have counts for
18 papers
Reservoir Computing with Heterogeneous Magnetic Metamaterials
R. Yagan, C. Swindells, I. T. Vidamour +5
Physical reservoir computing utilizes the intrinsic nonlinear and history-dependent dynamics of physical systems to perform machine-learning tasks with minimal training overhead. H…
Reproducible Reservoir Computing with Thermally Driven Superparamagnets: Controlling Temperature Sensitivity
Zhengfei Chen, Alex Welbourne, Matthew O. A. Ellis +3
Unconventional computing systems must demonstrate robust performance under real-world environmental conditions to enable practical deployments. We have recently proposed superparam…
Noise-Aware Training of Neuromorphic Dynamic Device Networks
Luca Manneschi, Ian T. Vidamour, Kilian D. Stenning +13
Physical computing has the potential to enable widespread embodied intelligence by leveraging the intrinsic dynamics of complex systems for efficient sensing, processing, and inter…
Machine learning using magnetic stochastic synapses
Matthew O. A. Ellis, Alex Welbourne, Stephan J. Kyle +4
The impressive performance of artificial neural networks has come at the cost of high energy usage and CO emissions. Unconventional computing architectures, with magnetic syste…
A perspective on physical reservoir computing with nanomagnetic devices
Dan A Allwood, Matthew O A Ellis, David Griffin +11
Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this succ…
A route to minimally dissipative switching in magnets via THz phonon pumping
Mara Strungaru, Matthew O A Ellis, Sergiu Ruta +3
Advanced magnetic recording paradigms typically use large temperature changes to drive switching which is detrimental to device longevity, hence finding non-thermal routes is cruci…
Quantifying the Computational Capability of a Nanomagnetic Reservoir Computing Platform with Emergent Magnetization Dynamics
Ian T Vidamour, Matthew O A Ellis, David Griffin +12
Devices based on arrays of interconnected magnetic nano-rings with emergent magnetization dynamics have recently been proposed for use in reservoir computing applications, but for…
Exploiting Multiple Timescales in Hierarchical Echo State Networks
Luca Manneschi, Matthew O. A. Ellis, Guido Gigante +3
Echo state networks (ESNs) are a powerful form of reservoir computing that only require training of linear output weights whilst the internal reservoir is formed of fixed randomly…
Modeling coupled spin and lattice dynamics
Mara Strungaru, Matthew O A Ellis, Sergiu Ruta +3
A unified model of molecular and atomistic spin dynamics is presented enabling simulations both in microcanonical and canonical ensembles without the necessity of additional phenom…
Role of longitudinal fluctuations in L FePt
Matthew O. A. Ellis, Mario Galante, Stefano Sanvito
L FePt is a technologically important material for a range of novel data storage applications. In the ordered FePt structure the normally non-magnetic Pt ion acquires a magnet…
Non-trivial spatial dependence of the spin torques in L1 FePt-based tunnelling junctions
Mario Galante, Matthew O. A. Ellis, Stefano Sanvito
We present an {\it ab-initio} study of the spin-transfer torque in a Fe/MgO/FePt/Fe magnetic tunnel junctions. We consider a FePt film with a thickness up to six unit cells, either…
Multi-scale modelling of current-induced switching in magnetic tunnel junctions using ab initio spin transfer torques
Matthew O. A. Ellis, Maria Stamenova, Stefano Sanvito
There exists a significant challenge in developing efficient magnetic tunnel junctions with low write currents for non-volatile memory devices. With the aim of analysing potential…
Manifestation of higher-order inter-granular exchange in magnetic recording media
Matthew O. A. Ellis, Razvan. -V. Ababei, Roger Wood +2
Exchange coupling between magnetic grains is essential for maintaining the stability of stored information in magnetic recording media. Using an atomistic spin model, we have inves…
All-optical switching in granular ferromagnets caused by magnetic circular dichroism
Matthew O. A. Ellis, Eric E. Fullerton, Roy W. Chantrell
Magnetic recording using circularly polarized femto-second laser pulses is an emerging technology that would allow write speeds much faster than existing field driven methods. Howe…
The Landau-Lifshitz equation in atomistic models
M. O. A. Ellis, R. F. L. Evans, T. A. Ostler +4
The Landau-Lifshitz (LL) equation, originally proposed at the macrospin level, is increasingly used in Atomistic Spin Dynamic (ASD) models. The models are based on a spin Hamiltoni…
Switching times of nanoscale FePt: finite size effects on linear reversal mechanism
M. O. A. Ellis, R. W. Chantrell
The linear reversal mechanism in FePt grains ranging from 2.316 nm to 5.404 nm has been simulated using atomistic spin dynamics, parametrized from ab-initio calculations. The Curie…
Temperature Dependent Ferromagnetic Resonance via the Landau-Lifshitz-Bloch Equation: Application to FePt
Thomas A. Ostler, Matthew O. A. Ellis, Denise Hinzke +1
Using the Landau-Lifshitz-Bloch (LLB) equation for ferromagnetic materials, we derive analytic expressions for temperature dependent absorption spectra as probed by ferromagnetic r…
Atomistic spin model simulations of magnetic nanomaterials
Richard F. L. Evans, Weijia J. Fan, Phanwadee Chureemart +3
Atomistic modelling of magnetic materials provides unprecedented detail about the underlying physical processes that govern their macroscopic properties, and allows the simulation…