Related papers: Improved Magnetic Information Storage using Return…

We develop a stochastic-dynamic framework to infer latent grain size distribution from magnetic hysteresis data in M-type hexaferrite materials, offering an alternative to imaging-based characterization. A stochastic nucleation-growth…

There is an urgent need to enhance the storage density of memory devices to accommodate the exponentially increasing amount of data generated by humankind. In this work, we describe Magnonic Combinatorial Memory (MCM), where the bits of…

A scheme for backward retrieval in optical quantum memories in which information is stored in collective states of an extended resonant atomic ensemble is developed such that phase conjugation can be implemented by application of an…

We propose theoretically a generalized memristive system based on controlled spin polarizations in the giant magnetoresistive material using a feedback loop with the classical Hall Effect. The dynamics can exhibit a memristive pinched…

We investigate hysteresis loops and return point memory for artificial square and kagome spin ice systems by cycling an applied bias force and comparing microscopic effective spin configurations throughout the hysteresis cycle. Return point…

We study the return point as well as the complementary point memory effects numerically with paradigmatic models for random magnets and show that already simple systems with Ising spin symmetry can reproduce the experimental results of…

We calculate energy spectra of a two-dimensional electron system in a perpendicular magnetic field and periodic potentials of short periods. The Coulomb interaction is included within a screened Hartree-Fock approximation. The electrostatic…

In recent years, commercial HTS superconductors have gained an increasing interest for their use in applications involving large-scale superconductor systems. These systems are typically made from hundreds to thousands of turns of…

We suggest a novel methodology to obtain a digital representation of analog signals and to perform its back-conversion using memristive devices. In the proposed converters, the same memristive systems are used for two purposes: as elements…

Storage systems often rely on multiple copies of the same compressed data, enabling recovery in case of binary data errors, of course, at the expense of a higher storage cost. In this paper we show that a wiser method of duplication entails…

Single-molecule magnets (SMMs) exhibiting open hysteresis loops may potentially apply to molecule-based information processing and storage. However, the capacity to retain magnetic memory is always limited by zero-field quantum tunneling of…

The phenomenon of storage and parametrically-stimulated recovery of a microwave signal in a ferrite film has been studied both experimentally and theoretically. The microwave signal is stored in the form of standing spin-wave modes existing…

We have proposed a quantum model for the magnetic multi-valued recording in this paper. The hysteresis loops of the two-dimensional systems with randomly distributed magnetic atoms have been studied by the quantum theory developed…

We show that both the energy stored and dissipated by a system with hysteretic nonlinearity in an applied field varies with the relative phase of the sinusoidal components of the field, even if the magnitude of these components, and thus an…

Information processing and storing by the same physical system is emerging as a promising alternative to traditional computing platforms. In turn, this requires the realization of elementary units whose memory content can be easily tuned…

Modulo sampling is a promising technology to preserve amplitude information that exceeds the observable range of analog-to-digital converters during the digitization of analog signals. Since conventional methods typically reconstruct the…

Magnetization reversal in magnetic particles is one of the fundamental issues in magnetic data storage. Technological improvements require the understanding of dynamical magnetization reversal processes at nanosecond time scales. New…

Quasi-static hysteresis loops of spherical and spheroidal magnetite nanoparticles with semi-axes ratio a/b = 1.5 and 2.0 with different types of combined magnetic anisotropy are calculated using numerical simulation. For particles of each…

This work introduces a latent space method to calculate the demagnetization reversal process of multigrain permanent magnets. The algorithm consists of two deep learning models based on neural networks. The embedded Stoner-Wohlfarth method…

We report a novel singularity in the hysteresis of spin glasses, the reversal-field memory effect, which creates a non-analyticity in the magnetization curves at a particular point related to the history of the sample. The origin of the…