Adiabatic Control of Spin-Wave Propagation using Magnetisation Gradients

Spin waves are of large interest as data carriers for future logic devices. However, due to the strong anisotropic dispersion relation of dipolar spin-waves in in-plane magnetised films the realisation of two-dimensional information transport remains a challenge. Bending of the energy flow is prohibited since energy and momentum of spin waves cannot be conserved while changing the direction of wave propagation. Thus, non-linear or non-stationary mechanisms are usually employed. Here, we propose to use reconfigurable laser-induced magnetisation gradients to break the system's translational symmetry. The resulting changes in the magnetisation shift the dispersion relations locally and allow for operating with different spin-wave modes at the same frequency. Spin-wave momentum is first transformed via refraction at the edge of the magnetisation gradient region and then adiabatically modified inside it. Along these lines the spin-wave propagation direction can be controlled in a broad frequency range with high efficiency

Perspective on Nanoscaled Magnonic Networks

With the rapid development of artificial intelligence in recent years, mankind is facing an unprecedented demand for data processing. Today, almost all data processing is performed using electrons in conventional complementary metal-oxide-semiconductor (CMOS) circuits. Over the past few decades, scientists have been searching for faster and more efficient ways to process data. Now, magnons, the quanta of spin waves, show the potential for higher efficiency and lower energy consumption in solving some specific problems. While magnonics remains predominantly in the realm of academia, significant efforts are being made to explore the scientific and technological challenges of the field. Numerous proof-of-concept prototypes have already been successfully developed and tested in laboratories. In this article, we review the developed magnonic devices and discuss the current challenges in realizing magnonic circuits based on these building blocks. We look at the application of spin waves in neuromorphic networks, stochastic and reservoir computing and discuss the advantages over conventional electronics in these areas. We then introduce a new powerful tool, inverse design magnonics, which has the potential to revolutionize the field by enabling the precise design and optimization of magnonic devices in a short time. Finally, we provide a theoretical prediction of energy consumption and propose benchmarks for universal magnonic circuits.Comment: 9 pages, 1 figur