Spin-torque ac impedance in magnetic tunnel junctions

Subjecting a magnetic tunnel junction (MTJ) to a spin current and/or electric voltage induces magnetic precession, which can reciprocally pump current through the circuit. This results in an ac impedance, which is sensitive to the magnetic field applied to the MTJ. Measuring this impedance can be used to characterize the coupling between the magnetic free layer and the electric current as well as a read-out of the magnetic configuration of the MTJ.Comment: 4 pages, 3 figure

SPICE based compact model for electrical switching of antiferromagnet

A simulation framework that can model the behavior of antiferromagnets (AFMs) is essential to building novel high-speed devices. The electrical switching of AFMs allows for high performance memory applications. With new phenomena in spintronics being discovered, there is a need for flexible and expandable models. With that in mind, we developed a model for AFMs which can be used to simulate AFM switching behavior in SPICE. This approach can be modified for adding modules, keeping pace with new developments. The proposed AFM switching model is based on the Landau-Lifshitz-Gilbert equation (LLG). LLG along with an exchange coupling module is implemented with conventional electrical circuit elements like voltage-dependent current sources and capacitors. This proposed simulation can be performed for different user defines magnet parameters and initial magnet configurations. The model is carefully benchmarked with experiments. It can be used to study different AFM structures and corresponding switching capabilities. This provides the simulations required with good accuracy for high performance memory applications of AFM in high speed devices

Subnanosecond Fluctuations in Low-Barrier Nanomagnets

Fast magnetic fluctuations due to thermal torques have useful technological functionality ranging from cryptography to probabilistic computing. The characteristic time of fluctuations in typical uniaxial anisotropy magnets studied so far is bounded from below by the well-known energy relaxation mechanism. This time scales as $\alpha^{-1}$, where $\alpha$ parameterizes the strength of dissipative processes. Here, we theoretically analyze the fluctuating dynamics in easy-plane and antiferromagnetically coupled nanomagnets. We find in such magnets, the dynamics are strongly influenced by fluctuating intrinsic fields, which give rise to an additional dephasing-type mechanism for washing out correlations. In particular, we establish two time scales for characterizing fluctuations (i) the average time for a nanomagnet to reverse|which for the experimentally relevant regime of low damping is governed primarily by dephasing and becomes independent of $\alpha$, (ii) the time scale for memory loss of a single nanomagnet|which scales as $\alpha^{-1/3}$ and is governed by a combination of energy dissipation and dephasing mechanism. For typical experimentally accessible values of intrinsic fields, the resultant thermal-fluctuation rate is increased by multiple orders of magnitude when compared with the bound set solely by the energy relaxation mechanism in uniaxial magnets. This could lead to higher operating speeds of emerging devices exploiting magnetic fluctuations