Anomalous Bias Dependence of Spin Torque in Magnetic Tunnel Junctions

We predict an anomalous bias dependence of the spin transfer torque parallel to interface, $T_{||}$, in magnetic tunnel junctions (MTJ), which can be selectively tuned by the exchange splitting. It may exhibit a sign reversal {\it without} a corresponding sign reversal of the bias or even a quadratic bias dependence. We demonstrate that the underlying mechanism is the interplay of spin currents for the ferromagnetic (antiferromagnetic) configurations, which vary linearly (quadratically) with bias, respectively, due to the symmetric (asymmetric) nature of the barrier. The spin transfer torque perpendicular to interface exhibits a quadratic bias dependence.Comment: 4 pages, 5 figure

Voltage Dependence of Spin Transfer Torque in Magnetic Tunnel Junctions

Theoretical investigations of spin transfer torque in magnetic tunnel junctions using the tight-binding model in the framework of non-equilibrium Green functions formalism are presented. We show that the behavior of the spin transfer torque as a function of applied voltage can vary over a wide range depending on the band parameters of the ferromagnetic electrodes and the insulator that comprise the magnetic tunnel junction. The behavior of both the parallel and perpendicular components of the spin torque is addressed. This behavior is explained in terms of the spin and charge current dependence and on the interplay between evanescent states in the insulator and the Fermi surfaces of ferromagnetic electrodes comprising the junction. The origin of the perpendicular (field-like) component of spin transfer torque at zero bias, i.e. exchange coupling through the barrier between ferromagnetic electrodes is discussed.Comment: 5 pages,4 figure

Financial Fraud Detection using Quantum Graph Neural Networks

Financial fraud detection is essential for preventing significant financial losses and maintaining the reputation of financial institutions. However, conventional methods of detecting financial fraud have limited effectiveness, necessitating the need for new approaches to improve detection rates. In this paper, we propose a novel approach for detecting financial fraud using Quantum Graph Neural Networks (QGNNs). QGNNs are a type of neural network that can process graph-structured data and leverage the power of Quantum Computing (QC) to perform computations more efficiently than classical neural networks. Our approach uses Variational Quantum Circuits (VQC) to enhance the performance of the QGNN. In order to evaluate the efficiency of our proposed method, we compared the performance of QGNNs to Classical Graph Neural Networks using a real-world financial fraud detection dataset. The results of our experiments showed that QGNNs achieved an AUC of $0.85$, which outperformed classical GNNs. Our research highlights the potential of QGNNs and suggests that QGNNs are a promising new approach for improving financial fraud detection.Comment: 15 pages, 18 figures, 4 table

Vertical current induced domain wall motion in MgO-based magnetic tunnel junction with low current densities

Shifting electrically a magnetic domain wall (DW) by the spin transfer mechanism is one of the future ways foreseen for the switching of spintronic memories or registers. The classical geometries where the current is injected in the plane of the magnetic layers suffer from a poor efficiency of the intrinsic torques acting on the DWs. A way to circumvent this problem is to use vertical current injection. In that case, theoretical calculations attribute the microscopic origin of DW displacements to the out-of-plane (field-like) spin transfer torque. Here we report experiments in which we controllably displace a DW in the planar electrode of a magnetic tunnel junction by vertical current injection. Our measurements confirm the major role of the out-of-plane spin torque for DW motion, and allow to quantify this term precisely. The involved current densities are about 100 times smaller than the one commonly observed with in-plane currents. Step by step resistance switching of the magnetic tunnel junction opens a new way for the realization of spintronic memristive devices

Effect of resistance feedback on spin torque-induced switching of nanomagnets

In large magnetoresistance devices spin torque-induced changes in resistance can produce GHz current and voltage oscillations which can affect magnetization reversal. In addition, capacitive shunting in large resistance devices can further reduce the current, adversely affecting spin torque switching. Here, we simultaneously solve the Landau-Lifshitz-Gilbert equation with spin torque and the transmission line telegrapher's equations to study the effects of resistance feedback and capacitance on magnetization reversal of both spin valves and magnetic tunnel junctions. While for spin valves parallel (P) to anti-parallel (AP) switching is adversely affected by the resistance feedback due to saturation of the spin torque, in low resistance magnetic tunnel junctions P-AP switching is enhanced. We study the effect of resistance feedback on the switching time of MTJ's, and show that magnetization switching is only affected by capacitive shunting in the pF range.Comment: 8 page

Magnetoresistance and spin-transfer torque in magnetic tunnel junctions

We comment on both recent progress and lingering puzzles related to research on magnetic tunnel junctions (MTJs). MTJs are already being used in applications such as magnetic-field sensors in the read heads of disk drives, and they may also be the first device geometry in which spin-torque effects are applied to manipulate magnetic dynamics, in order to make nonvolatile magnetic random access memory. However, there remain many unanswered questions about such basic properties as the magnetoresistance of MTJs, how their properties change as a function of tunnel-barrier thickness and applied bias, and what are the magnitude and direction of the spin-transfer-torque vector induced by a tunnel current.Comment: 37 pages, 2 figures. Contribution to a collection of "Current Perspectives" articles on spin transfer torque now available in the Journal of Magnetism and Magnetic Material

Spin Transfer Torque and Tunneling Magnetoresistance Dependences on the Finite Bias Voltages and Insulator Barrier Energy

We investigate the dependence of perpendicular and parallel spin transfer torque (STT) and tunneling magnetoresistance (TMR) on the insulator barrier energy in the magnetic tunnel junction (MTJ). We employed single orbit tight binding model combined with the Keldysh non-equilibrium Green's function method in order to calculate the perpendicular and parallel STT, and TMR in MTJ with the finite bias voltages. The dependences of STT and TMR on the insulator barrier energy are calculated for the semi-infinite half metallic ferromagnetic electrodes. We find that perfect linear relation between the parallel STT and the tunneling current for the wide range of the insulator barrier energy. Furthermore, the TMR also depends on the insulator barrier energy, which contradicts to the Julliere's simple model

Magnetic domain wall motion by spin transfer

The discovery that a spin polarized current can exert a large torque on a ferromagnet through a transfusion of spin angular momentum, offers a new way to control a magnetization by simple current injection, without the help of an applied external field. Spin transfer can be used to induce magnetization reversals and oscillations, or to control the position of a magnetic domain wall. In this review, we focus on this last mechanism, which is today the subject of an extensive research, both because the microscopic details for its origin are still debated, but also because promising applications are at stake for non-volatile magnetic memories

Time-resolved detection of spin-transfer-driven ferromagnetic resonance and spin torque measurement in magnetic tunnel junctions

Several experimental techniques have been introduced in recent years in attempts to measure spin transfer torque in magnetic tunnel junctions (MTJs). The dependence of spin torque on bias is important for understanding fundamental spin physics in magnetic devices and for applications. However, previous techniques have provided only indirect measures of the torque and their results to date for the bias dependence are qualitatively and quantitatively inconsistent. Here we demonstrate that spin torque in MTJs can be measured directly by using time-domain techniques to detect resonant magnetic precession in response to an oscillating spin torque. The technique is accurate in the high-bias regime relevant for applications, and because it detects directly small-angle linear-response magnetic dynamics caused by spin torque it is relatively immune to artifacts affecting competing techniques. At high bias we find that the spin torque vector differs markedly from the simple lowest-order Taylor series approximations commonly assumed.Comment: 29 pages, 5 figures including supplementary materia