Driving skyrmions in flow regime in synthetic ferrimagnets.

The last decade has seen significant improvements in our understanding of skyrmions current induced dynamics, along with their room temperature stabilization, however, the impact of local material inhomogeneities still remains an issue that impedes reaching the regime of steady state motion of these spin textures. Here, we study the spin-torque driven motion of skyrmions in synthetic ferrimagnetic multilayers with the aim of achieving high mobility and reduced skyrmion Hall effect. We consider Pt|Co|Tb multilayers of various thicknesses with antiferromagnetic coupling between the Co and Tb magnetization. The increase of Tb thickness in the multilayers reduces the total magnetic moment and increases the spin-orbit torques allowing to reach velocities up to 400 ms-1 for skyrmions with diameters of about 160 nm. We demonstrate that due to reduced skyrmion Hall effect combined with the edge repulsion of the magnetic track, the skyrmions move along the track without any transverse deflection. Further, by comparing the field-induced domain wall motion and current-induced skyrmion motion, we demonstrate that the skyrmions at the largest current densities present all the characteristics of a dynamical flow regime.

Gesture recognition with Brownian reservoir computing using geometrically confined skyrmion dynamics.

Physical reservoir computing leverages the dynamical properties of complex physical systems to process information efficiently, significantly reducing training efforts and energy consumption. Magnetic skyrmions, topological spin textures, are promising candidates for reservoir computing systems due to their enhanced stability, non-linear interactions and low-power manipulation. Traditional spin-based reservoir computing has been limited to quasi-static detection or real-world data must be rescaled to the intrinsic timescale of the reservoir. We address this challenge by time-multiplexed skyrmion reservoir computing, that allows for aligning the reservoir's intrinsic timescales to real-world temporal patterns. Using millisecond-scale hand gestures recorded with Range-Doppler radar, we feed voltage excitations directly into our device and detect the skyrmion trajectory evolution. This method scales down to the nanometer level and demonstrates competitive or superior performance compared to energy-intensive software-based neural networks. Our hardware approach's key advantage is its ability to integrate sensor data in real-time without temporal rescaling, enabling numerous applications.

Large Interfacial Rashba Interaction Generating Strong Spin-Orbit Torques in Atomically Thin Metallic Heterostructures.

The hallmark of spintronics has been the ability of spin-orbit interactions to convert a charge current into a spin current and vice versa, mainly in the bulk of heavy metal thin films. Here, we demonstrate how a light metal interface profoundly affects both the nature of spin-orbit torques and its efficiency in terms of damping-like (HDL) and field-like (HFL) effective fields in ultrathin Co films. We measure unexpectedly HFL/HDL ratios much larger than 1 by inserting a nanometer-thin Al metallic layer in Pt|Co|Al|Pt as compared to a similar stacking, including Cu as a reference. From our modeling, these results evidence the existence of large Rashba interaction at the Co|Al interface generating a giant HFL, which is not expected from a metallic interface. The occurrence of such enhanced torques from an interfacial origin is further validated by demonstrating current-induced magnetization reversal showing a significant decrease of the critical current for switching.