Related papers: XDWM: A 2D Domain Wall Memory
Convolutional neural networks have become the main tools for processing two-dimensional data. They work well for images, yet convolutions have a limited receptive field that prevents its applications to more complex 2D tasks. We propose a…
Conductive ferroelectric domain walls--ultra-narrow and configurable conduction paths, have been considered as essential building blocks for future programmable domain wall electronics. For applications in high density devices, it is…
Magnetic domain-walls (DWs) with a preferred chirality exhibit very efficient current-driven motion. Since structural inversion asymmetry (SIA) is required for their stability, the observation of chiral domain walls in highly symmetric…
Sliding Window Sum algorithms have been successfully used for training and inference of Deep Neural Networks. We have shown before how both pooling and convolution 1-D primitives could be expressed as sliding sums and evaluated by the…
The domain wall motion in a magnetic nanowire is examined theoretically in the regime where the domain wall driving force is weak and its competition against disorders is assisted by thermal agitations. Two types of driving forces are…
Coupled quasi-one-dimensional (quasi-1D) electron systems host rich emergent physics that cannot be accounted for by understanding isolated 1D electron systems alone. Open questions remain about how transport in these arrays can be…
Machine learning implements backpropagation via abundant training samples. We demonstrate a multi-stage learning system realized by a promising non-volatile memory device, the domain-wall magnetic tunnel junction (DW-MTJ). The system…
Research on current-induced domain wall (DW) motion in heavy metal/ferromagnet structures is crucial for advancing memory, logic, and computing devices. Here, we demonstrate that adjusting the angle between the DW conduit and the current…
We present a new Clash-of-Symmetries mechanism in the context of an intersecting domain-wall brane model in 5+1-dimensional Minkowskian spacetime recently proposed by the authors. This new application of the Dvali-Shifman idea is designed…
We revisit the cosmological evolution of domain wall networks, taking advantage of recent improvements in computing power. We carry out high-resolution field theory simulations in two, three and four spatial dimensions to study the effects…
The current mobile applications have rapidly growing memory footprints, posing a great challenge for memory system design. Insufficient DRAM main memory will incur frequent data swaps between memory and storage, a process that hurts…
As the High Performance Computing world moves towards the Exa-Scale era, huge amounts of data should be analyzed, manipulated and stored. In the traditional storage/memory hierarchy, each compute node retains its data objects in its local…
Cellular-level neuron stimulation has attracted much attention in the areas of prevention, diagnosis and treatment of neurological disorders. Herein, we propose a spintronic neurostimulator based on the domain wall movement inside…
Mining informative negative instances are of central importance to deep metric learning (DML), however this task is intrinsically limited by mini-batch training, where only a mini-batch of instances is accessible at each iteration. In this…
We show that in a magnetic nanowire with double magnetic domain walls, quantum interference results in spin-split quasistationary states localized mainly between the domain walls. Spin-flip-assisted transmission through the domain structure…
Nanoscale magnetic junction provides a useful approach to act as the building block for magnetoresistive random access memories (MRAM), where one of the key issues is to control the magnetic domain configuration. Here, we study the domain…
A study of transverse tail-to-tail magnetic domain walls (DW) in novel current perpendicular to the plane (CPP) spin valves (SV) of various dimensions is presented. For films with dimensions larger than the DW width, we find that DW motion…
We study finite-horizon optimal switching with discrete intervention dates on a general filtration, allowing continuous-time observations between decision dates, and develop a deep-learning-based dual framework with computable upper bounds.…
Ferroelectric domain walls represent multifunctional 2D-elements with great potential for novel device paradigms at the nanoscale. Improper ferroelectrics display particularly promising types of domain walls, which, due to their unique…
Chiral domain walls of Neel type emerge in heterostructures that include heavy metal (HM) and ferromagnetic metal (FM) layers owing to the Dzyaloshinskii-Moriya (DM) interaction at the HM/FM interface. In developing storage class memories…