Ádám Papp

Spin-wave based realization of optical computing primitives

We use micromagnetic simulations to demonstrate that spin waves can perform optically inspired, non-Boolean computing algorithms. We propose and design coherent spin-wave sources and phase shifters, which act akin to the key components of an optical signal processing system. We show that the functionality of the proposed on-chip spin-wave based signal processing system is similar to known optical computing devices. We argue that such computing system can serve as a practical, energy efficient, and integrated component of nanoscale image processing systems.

Threshold Gate-Based Circuits From Nanomagnetic Logic

This paper demonstrates the design of nanomagnetic logic (NML) gates with multiple weighted inputs, which are magnetic equivalents of threshold logic gates (TLGs). We use micromagnetic simulations to show that NML TLGs can be constructed with minimum overhead compared to standard NML gates, and they significantly reduce device footprint and interconnection complexity of magnetic logic circuits. As an example, we design a full adder circuit using said TLGs and compare its performance to majority-gate-based NML.

Design of On-Chip Readout Circuitry for Spin-Wave Devices

We present the design of readout circuitry based on complementary metal-oxide semiconductors (CMOS) for spin-waves. The circuit provides the functionality of a high-speed oscilloscope/spectrum analyzer, and can be integrated with a spin-wave-based signal processing device. The circuit consumes sub-50 mW power and requires an area below 1 mm2. A spin-wave-based processing system, when combined with the presented electrical input/output circuitry, can perform complex microwave signal processing tasks, with speed, power consumption, and area that are not feasible in a CMOS-only system.

Spin-wave-based computing devices

We use micromagnetic simulations to demonstrate spin-wave-based, optically-inspired computing primitives in nanomagnetic devices. We demonstrate the construction of devices based on spin-wave propagation, such as spin-wave sources, lenses, and mirrors. We show that these can serve as building blocks of more complex spin-wave systems, e.g. Fourier transformation or filtering.

Nanoscale spectrum analyzer based on spin-wave interference

We present the design of a spin-wave-based microwave signal processing device. The microwave signal is first converted into spin-wave excitations, which propagate in a patterned magnetic thin-film. An interference pattern is formed in the film and its intensity distribution at appropriate read-out locations gives the spectral decomposition of the signal. We use analytic calculations and micromagnetic simulations to verify and to analyze the operation of the device. The results suggest that all performance figures of this magnetoelectric device at room temperature (speed, area, power consumption) may be significantly better than what is achievable in a purely electrical system. We envision that a new class of low-power, high-speed, special-purpose signal processors can be realized by spin-waves.

Hybrid yttrium iron garnet-ferromagnet structures for spin-wave devices

We study coupled ferromagnetic layers, which could facilitate low loss, sub 100 nm wavelength spin-wave propagation and manipulation. One of the layers is a low-loss garnet film (such as yttrium iron garnet (YIG)) that enables long-distance, coherent spin-wave propagation. The other layer is made of metal-based (Permalloy, Co, and CoFe) magnetoelectronic structures that can be used to generate, manipulate, and detect the spin waves. Using micromagnetic simulations, we analyze the interactions between the spin waves in the YIG and the metallic nanomagnet structures and demonstrate the components of a scalable spin-wave based signal processing device. We argue that such hybrid-metallic ferromagnet structures can be the basis of potentially high-performance, ultra low-power computing devices.

Non-boolean computing based on linear waves and oscillators

We investigate, how linear or weakly nonlinear oscillatory systems (coupled nanoscale oscillators and propagating spin-waves) can be used as non-Boolean computing systems. We study two model systems: nearest-neighbor connected harmonic oscillators and propagating spin-waves. We argue that these systems may realize efficient co-processors for some demanding applications (image processing, associative memories, scientific computations), where digital CMOS solutions are notably inefficient. Wave-based processing architectures may use emerging nano-scale oscillators as device components, potentially surpassing end-of-roadmap CMOS performance.

Optically-inspired computing based on spin waves

We demonstrate the use of spin-wave interference for analog signal processing. We show that wave-computing concepts of optical computing can be used for the design of novel nanoscale spin-wave devices. We present a number of designs to demonstrate, how the basic building blocks of optics can be realized for spin waves. Our designs are demonstrated by means of micromagnetic simulations.

Holographic algorithms for on-chip, non-boolean computing

It is widely believed that the established route of microelectronic scaling is approaching its end: further downscaling of semiconductor devices carries disproportionate penalties in power consumption and poses fundamental fabrication challenges. Instead of scaling of devices, Moores law is now increasingly about scaling computing systems: single-core devices toward larger, multi-core systems. While there are known programming methodologies for parallelizing program codes to a few threads, only very few, special-purpose applications lend themselves to parallelization on very large numbers of cores. This motivates our quest for studying computing paradigms and algorithms that are inherently parallel [1]. Holographic / optical computing is a perfect example of such algorithms: the results of a computation are given by an interference pattern formation of many light rays (see Fig. 1 for an illustration [1]). Optical systems are impractical to realize on-chip. For this reason, we explore routes to design holographic algorithms that can be naturally integrated with microelectronic technologies and require no optical hardware. Two approaches will be discussed in this paper.

Signal processing with optically-inspired algorithms

We introduce holographic (optically inspired) algorithms, which are suited for implementation on massively parallel, locally interconnected arrays of nanoscale devices. This computing method is inspired by optical signal processing, but it neither relies on optical wave propagation nor optical hardware. We describe implementations on digital semiconductor circuitry and on magnetoelectronic devices.