The field of nanomagnetism has recently attracted tremendous attention as it can potentially deliver low-power, high-speed and dense non-volatile memories. It is now possible to engineer the size, shape, spacing, orientation and composition of sub-100 nm magnetic structures. This has spurred the exploration of nanomagnets for unconventional computing paradigms. Here, we harness the energy-minimization nature of nanomagnetic systems to solve the quadratic optimization problems that arise in computer vision applications, which are computationally expensive. By exploiting the magnetization states of nanomagnetic disks as state representations of a vortex and single domain, we develop a magnetic Hamiltonian and implement it in a magnetic system that can identify the salient features of a given image with more than 85% true positive rate. These results show the potential of this alternative computing method to develop a magnetic coprocessor that might solve complex problems in fewer clock cycles than traditional processors.
Nano-magnetic logic (NML) has been a promising technology for logic computation. Contribution of this paper is twofold. First, we have fabricated and captured MFM images of a NML architecture that has computed the majority of seven variables. This logic block can potentially implement eight different logic functions that could be configured in real-time. Next, we have performed a set of experiments with a multilayer stack of Co t ¼ 0.4 nm /Cu t ¼ 4 nm /Ni 20 Fe 80t ¼ 5 nm with a perpendicular magnetic anisotropy bottom layer to realize neighbor interaction between adjacent free layers of devices. Based on the MFM images, we conclude that dipolar coupling between the free layers of the neighboring spin-valve based NML (SVBN) devices can be exploited to construct local elements such as majority gates, inverters and interconnects. Since magnetic multilayer stacks have already been implemented in memory devices to read/write data, SVBN devices would not only solve the input/output problems in NML but also would have potential in logic-in-memory applications. V
The present study investigated the dipole–dipole interaction for finite 2D arrays of ferromagnetic circular nanomagnets. Starting with two basic arrangements of coupled nanomagnets namely, longitudinal and transverse, different diameters, and thicknesses are studied. The phase plot results exhibit for longitudinal arrangements that the single domain state is pervasive over a large range of thickness values as compared to the transverse arrangement or isolated nanomagnet cases. The study is further extended to finite arrays (3 × 3 and 5 × 5) of circular nanomagnets. The magnetic force microscopy results show that arrays of nanomagnets favors antiferromagnetic ordering at remanence. We have correlated our experimental results with micromagnetic simulations. Based on our study, we can conclude that nanomagnets with 100 nm in diameter, 15 nm in thickness, and 20 nm in spacing have single domain states in an array configuration with one-step switching, which results in fast operation, a property ideal for computing.
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