arXiv subjects

George Bourianoff

Publications and source records attributed to George Bourianoff.

5 recordsLinked to original sources

arXiv2022

Spatial Analysis of Physical Reservoir Computers

Physical reservoir computing is a computational framework that implements spatiotemporal information processing directly within physical systems. By exciting nonlinear dynamical systems and creating linear models from their state, we can create highly energy-efficient devices capable of solving machine learning tasks without building a modular system consisting of millions of neurons interconnected by synapses. To act as an effective reservoir, the chosen dynamical system must have two desirable properties: nonlinearity and memory. We present task agnostic spatial measures to locally measure both of these properties and exemplify them for a specific physical reservoir based upon magnetic skyrmion textures. In contrast to typical reservoir computing metrics, these metrics can be resolved spatially and in parallel from a single input signal, allowing for efficient parameter search to design efficient and high-performance reservoirs. Additionally, we show the natural trade-off between memory capacity and nonlinearity in our reservoir's behaviour, both locally and globally. Finally, by balancing the memory and nonlinearity in a reservoir, we can improve its performance for specific tasks.

cs.LG↗

arXiv2019

Reservoir Computing with Random Skyrmion Textures

The Reservoir Computing (RC) paradigm posits that sufficiently complex physical systems can be used to massively simplify pattern recognition tasks and nonlinear signal prediction. This work demonstrates how random topological magnetic textures present sufficiently complex resistance responses for the implementation of RC as applied to A/C current pulses. In doing so, we stress how the applicability of this paradigm hinges on very general dynamical properties which are satisfied by a large class of physical systems where complexity can be put to computational use. By harnessing the complex resistance response exhibited by random magnetic skyrmion textures and using it to demonstrate pattern recognition, we explain how spintronically accessible magnetic systems offer an advantage in the search for an ideal reservoir computer. The low-power properties of compact skyrmion fabrics, coupled with their CMOS integrability operating on similar length and timescales, open the door for their RC employment geared towards industrial application.

cond-mat.mes-hall↗

arXiv2018

Skyrmion nucleation via localized spin current injection in confined nanowire geometry in low chirality magnetic materials

Magnetic skyrmions have been the focus of intense research with promising applications in memory, logic and interconnect technology. Several schemes have been recently proposed and demonstrated to nucleate skyrmions. However, they either result in an uncontrolled skyrmion bubble production or are mostly targeted towards integration with racetrack memory device. In this work, we propose a novel scheme for a controlled single skyrmion nucleation in a confined nanowire geometry with sub-100 nm width using a generalized approach of "localized spin current injection" technique in material systems exhibiting low Dzyaloshinskii-Moriya interaction (DMI). Our proposed nucleation mechanism follows a pathway involving the creation of a reversed magnetic domain containing one or more pairs of vertical Bloch lines (VBLs) that form an edge-to-edge domain wall as the VBLs get annihilated at the edge of the nanowire. However, pinning of the edge domain walls within a narrow gap using notches or anti-notches results in the creation of a magnetic bubble with defect-free domain wall that eventually relaxes into a circular skyrmion structure. Our simulations predict that the proposed mechanism allows skyrmion nucleation on sub-nanosecond timescale, shows robustness to variations like local pinning sites and is applicable for any skyrmion-based logic, memory and interconnect application.

cond-mat.mes-hall↗

arXiv2017

Potential implementation of Reservoir Computing models based on magnetic skyrmions

Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir Computing paradigm does not require any knowledge of the reservoir topology or node weights for training purposes and can therefore utilize naturally existing networks formed by a wide variety of physical processes. Most efforts prior to this have focused on utilizing memristor techniques to implement recursive neural networks. This paper examines the potential of skyrmion fabrics formed in magnets with broken inversion symmetry that may provide an attractive physical instantiation for Reservoir Computing.

cond-mat.mes-hall↗

arXiv2017

A magnetic skyrmion as a non-linear resistive element - a potential building block for reservoir computing

Inspired by the human brain, there is a strong effort to find alternative models of information processing capable of imitating the high energy efficiency of neuromorphic information processing. One possible realization of cognitive computing are reservoir computing networks. These networks are built out of non-linear resistive elements which are recursively connected. We propose that a skyrmion network embedded in frustrated magnetic films may provide a suitable physical implementation for reservoir computing applications. The significant key ingredient of such a network is a two-terminal device with non-linear voltage characteristics originating from single-layer magnetoresistive effects, like the anisotropic magnetoresistance or the recently discovered non-collinear magnetoresistance. The most basic element for a reservoir computing network built from "skyrmion fabrics" is a single skyrmion embedded in a ferromagnetic ribbon. In order to pave the way towards reservoir computing systems based on skyrmion fabrics, here we simulate and analyze i) the current flow through a single magnetic skyrmion due to the anisotropic magneto-resistive effect and ii) the combined physics of local pinning and the anisotropic magneto-resistive effect.

cond-mat.dis-nn↗