Magnetic Cellular Nonlinear Network with Spin Wave Bus for Image Processing

We describe and analyze a cellular nonlinear network based on magnetic nanostructures for image processing. The network consists of magneto-electric cells integrated onto a common ferromagnetic film - spin wave bus. The magneto-electric cell is an artificial two-phase multiferroic structure comprising piezoelectric and ferromagnetic materials. A bit of information is assigned to the cell's magnetic polarization, which can be controlled by the applied voltage. The information exchange among the cells is via the spin waves propagating in the spin wave bus. Each cell changes its state as a combined effect of two: the magneto-electric coupling and the interaction with the spin waves. The distinct feature of the network with spin wave bus is the ability to control the inter-cell communication by an external global parameter - magnetic field. The latter makes possible to realize different image processing functions on the same template without rewiring or reconfiguration. We present the results of numerical simulations illustrating image filtering, erosion, dilation, horizontal and vertical line detection, inversion and edge detection accomplished on one template by the proper choice of the strength and direction of the external magnetic field. We also present numerical assets on the major network parameters such as cell density, power dissipation and functional throughput, and compare them with the parameters projected for other nano-architectures such as CMOL-CrossNet, Quantum Dot Cellular Automata, and Quantum Dot Image Processor. Potentially, the utilization of spin waves phenomena at the nanometer scale may provide a route to low-power consuming and functional logic circuits for special task data processing

Spin Wave Magnetic NanoFabric: A New Approach to Spin-based Logic Circuitry

We propose and describe a magnetic NanoFabric which provides a route to building reconfigurable spin-based logic circuits compatible with conventional electron-based devices. A distinctive feature of the proposed NanoFabric is that a bit of information is encoded into the phase of the spin wave signal. It makes possible to transmit information without the use of electric current and utilize wave interference for useful logic functionality. The basic elements include voltage-to-spin wave and wave-to-voltage converters, spin waveguides, a modulator, and a magnetoelectric cell. As an example of a magnetoelectric cell, we consider a two-phase piezoelectric-piezomagnetic system, where the spin wave signal modulation is due to the stress-induced anisotropy caused by the applied electric field. The performance of the basic elements is illustrated by experimental data and results of numerical modeling. The combination of the basic elements let us construct magnetic circuits for NOT and Majority logic gates. Logic gates AND, OR, NAND and NOR are shown to be constructed as the combination of NOT and a reconfigurable Majority gates. The examples of computational architectures such as Cellular Automata, Cellular Nonlinear Network and Field Programmable Gate Array are described. The main advantage of the proposed NanoFabric is in the ability to realize logic gates with less number of devices than it required for CMOS-based circuits. Potentially, the area of the elementary reconfigurable Majority gate can be scaled down to 0.1um2. The disadvantages and limitations of the proposed NanoFabric are discussed

Massively parallel computing on an organic molecular layer

Current computers operate at enormous speeds of ~10^13 bits/s, but their principle of sequential logic operation has remained unchanged since the 1950s. Though our brain is much slower on a per-neuron base (~10^3 firings/s), it is capable of remarkable decision-making based on the collective operations of millions of neurons at a time in ever-evolving neural circuitry. Here we use molecular switches to build an assembly where each molecule communicates-like neurons-with many neighbors simultaneously. The assembly's ability to reconfigure itself spontaneously for a new problem allows us to realize conventional computing constructs like logic gates and Voronoi decompositions, as well as to reproduce two natural phenomena: heat diffusion and the mutation of normal cells to cancer cells. This is a shift from the current static computing paradigm of serial bit-processing to a regime in which a large number of bits are processed in parallel in dynamically changing hardware.Comment: 25 pages, 6 figure

Nanomagnetic Boolean Logic -- The Tempered (and Realistic) Vision

The idea of nanomagnetic Boolean logic was advanced more than two decades ago. It envisaged the use of nanomagnets with two stable magnetization orientations as the primitive binary switch for implementing logic gates and ultimately combinational/sequential circuits. Enthusiastic proclamations of how nanomagnetic logic will eclipse traditional (transistor-based) logic circuits proliferated the applied physics literature. Two decades later there is not a single viable nanomagnetic logic chip in sight, let alone one that is a commercial success. In this perspective article, I offer my reasons on why this has come to pass. I present a realistic and tempered vision of nanomagnetic logic, pointing out many misconceptions about this paradigm, flaws in some proposals that appeared in the literature, shortcomings, and likely pitfalls that might stymie progress in this field.Comment: Accepted in IEEE Acces