Magnetic skyrmions are topologically protected spin textures that have nanoscale dimensions and can be manipulated by an electric current. These properties make the structures potential information carriers in data storage, processing and transmission devices. However, the development of functional all-electrical electronic devices based on skyrmions remains challenging. Here we show that the current-induced creation, motion, detection and deletion of skyrmions at room temperature can be used to mimic the potentiation and depression behaviours of biological synapses. In particular, the accumulation and dissipation of magnetic skyrmions in ferrimagnetic multilayers can be controlled with electrical pulses to represent the variations in the synaptic weights. Using chip-level simulations, we demonstrate that such artificial synapses based on magnetic skyrmions could be used for neuromorphic computing tasks such as pattern recognition. For a handwritten pattern dataset, our system achieves a recognition accuracy of ~89%, which is comparable to the accuracy achieved with software-based ideal training (~93%).

磁天文离子是具有拓扑结构的自旋纹理，具有纳米尺度的尺寸，可以通过电流进行控制。这些特性使这些结构成为数据存储，处理和传输设备中潜在的信息载体。然而，基于天窗离子的功能全电电子设备的开发仍然具有挑战性。在这里，我们表明电流诱导的创建，运动，检测和删除在室温下的skyrmion可以用来模仿生物突触的增强和抑制行为。特别地，可以用电脉冲控制亚铁磁性多层中的磁性天体离子的积累和耗散，以表示突触权重的变化。使用芯片级仿真，我们证明了这种基于磁天窗的人工突触可用于神经形态计算任务，例如模式识别。对于手写模式数据集，我们的系统可实现约89％的识别精度，这与基于软件的理想训练所获得的精度（约93％）相当。