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We present a procedure to study the switching and the stability of an array of magnetic nanoparticles in the dynamical regime. The procedure leads to the criterion of multi-switching stability to be satisfied in order to have stable…

Materials Science · Physics 2009-11-13 F. Porrati , M. Huth

$^{11}B$ NMR and nuclear spin-lattice relaxation rate (NSLR) are reported at 7.2 Tesla and 1.4 Tesla in powder samples of the intermetallic compound $MgB_2$ with superconducting transition temperature in zero field $T_c$ = 39.2 K. From the…

Superconductivity · Physics 2009-11-07 J. K. Jung , Seung Ho Baek , F. Borsa , S. L. Bud'ko , G. Lapertot , P. C. Canfield

We theoretically investigate the possibility of generating pulses in an excitable (asymmetric) semiconductor ring laser (SRL) using optical trigger pulses. We show that the phase difference between the injected field and the electric field…

Neurons in the brain behave as non-linear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behavior to realize high density, low power neuromorphic computing will require huge…

We theoretically investigate influences of electronic circuit delay, noise and temperature on write-error-rate (WER) in voltage-controlled magnetization switching operation of a magnetic-topological-insulator-based (MTI) device by means of…

Mesoscale and Nanoscale Physics · Physics 2023-09-07 Takashi Komine , Takahiro Chiba

The efficiency of dipole-dipole coupling driven coherence transfer experiments in solid-state NMR spectroscopy of powder samples is limited by dispersion of the orientation of the internuclear vectors relative to the external magnetic…

Quantum Physics · Physics 2009-11-13 N. Khaneja , C. Kehlet , S. J. Glaser , N. C. Nielsen

We present a study of the pulsed current switching characteristics of spin-valve nanopillars with in-plane magnetized dilute permalloy and undiluted permalloy free layers in the ballistic regime at low temperature. The dilute permalloy free…

Designing two-dimensional (2D) materials with magnetic and topological properties has continuously attracted intense interest in fundamental science and potential applications. Here, on the basis of first-principles calculations, we predict…

Materials Science · Physics 2020-09-08 Chang Liu , Botao Fu , Huabing Yin , Guangbiao Zhang , Chao Dong

We investigate the stochastic dynamics of nanoscale perpendicular magnetic tunnel junctions (pMTJs) and the correlations that arise when they are electrically coupled. Individual junctions exhibit thermally activated spin-transfer torque…

Mesoscale and Nanoscale Physics · Physics 2026-02-04 Dairong Chen , Ahmed Sidi El Valli , Jonathan Z. Sun , Flaviano Morone , Dries Sels , Andrew D. Kent

Numerical integration of the Landau-Lifshitz-Gilbert equation with thermal fluctuations is used to study the dynamic response of single-domain nanomagnets to rapid changes in the applied magnetic field. The simulation can resolve…

Materials Science · Physics 2007-05-23 G. Brown , M. A. Novotny , P. A. Rikvold

Energy-efficient switching of magnetization is a central problem in nonvolatile magnetic storage and magnetic neuromorphic computing. In the past two decades, several efficient methods of magnetic switching were demonstrated including spin…

On chip exciting electric modes in individual plasmonic nanostructures are realized widely; nevertheless, the excitation of their magnetic counterparts is seldom reported. Here, we propose a highly efficient on chip excitation approach of…

Optics · Physics 2021-12-15 Yingke Ji , Binbin Wang , Liang Fang , Qiang Zhao , Fajun Xiao , Xuetao Gan

In this paper we first show that dynamic switching schemes can be used to reduce energy dissipation below the thermodynamic minimum of NkTlnr (N= number of state variables, 1/r=error probability), but only at the expense of the error…

Mesoscale and Nanoscale Physics · Physics 2015-06-25 Sayeef Salahuddin , Supriyo Datta

We discuss multipulse magnetometry that exploits all three magnetic sublevels of the S=1 nitrogen-vacancy center in diamond to achieve enhanced magnetic field sensitivity. Based on dual frequency microwave pulsing, the scheme works in…

Mesoscale and Nanoscale Physics · Physics 2015-07-20 H. J. Mamin , M. H. Sherwood , M. Kim , C. T. Rettner , K. Ohno , D. D. Awschalom , D. Rugar

Over the past decade Spiking Neural Networks (SNN) have emerged as one of the popular architectures to emulate the brain. In SNN, information is temporally encoded and communication between neurons is accomplished by means of spikes. In…

Emerging Technologies · Computer Science 2016-12-14 Abhronil Sengupta , Aparajita Banerjee , Kaushik Roy

Binary stochastic neurons (BSNs) are excellent hardware accelerators for machine learning. A popular platform for implementing them are low- or zero-energy barrier nanomagnets possessing in-plane magnetic anisotropy (e.g. circular disks or…

Mesoscale and Nanoscale Physics · Physics 2022-11-16 Rahnuma Rahman , Supriyo Bandyopadhyay

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-effcient cognitive intelligence. The computational model attempt to exploit the intrinsic device…

Emerging Technologies · Computer Science 2018-01-29 Chamika M. Liyanagedera , Abhronil Sengupta , Akhilesh Jaiswal , Kaushik Roy

We put forward a method for achieving fast and robust for magnetization reversal in a nanomagnet, by combining the inverse engineering and composite pulses. The magnetic fields, generated by microwave with time-dependent frequency, are…

Quantum Physics · Physics 2017-03-13 Ze-Guo Song , Han Wu , Si Wang , Yue Ban , Xi Chen

Heat waste is a bottleneck in the development of green information technologies and much effort has been devoted to suppress the heating effect in both electronic and spintronic devices. Here we take an alternative approach and show that…

Mesoscale and Nanoscale Physics · Physics 2026-05-22 H. Y. Yuan , Yizheng Wu , Olena Gomonay

Neural networks span a wide range of applications of industrial and commercial significance. Binary neural networks (BNN) are particularly effective in trading accuracy for performance, energy efficiency or hardware/software complexity.…

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