Integrating magnetic skyrmions into neuromorphic computing could help improve hardware efficiency and computational power. However, developing a scalable implementation of the weighted sum of neuron signals—a core operation in neural networks—has remained a challenge. Here we show that weighted sum operations can be performed in a compact, biologically inspired manner by using the non-volatile and particle-like characteristics of magnetic skyrmions that make them easily countable and summable. The skyrmions are electrically generated in numbers proportional to an input with an efficiency given by a non-volatile weight. The chiral particles are then directed using localized current injections to a location in which their presence is quantified through non-perturbative electrical measurements. Our experimental demonstration, which currently has two inputs, can be scaled to accommodate multiple inputs and outputs using a crossbar-array design, potentially nearing the energy efficiency observed in biological systems.

将磁性斯格明子集成到神经形态计算中有助于提高硬件效率和计算能力。然而，开发神经元信号加权和的可扩展实现（神经网络中的核心操作）仍然是一个挑战。在这里，我们展示了通过使用磁斯格明子的非挥发性和粒子状特性，可以以紧凑的、受生物学启发的方式执行加权和运算，这使得它们易于计数和求和。斯格明子以与输入成比例的数量产生，其效率由非易失性重量给出。然后，使用局部电流注入将手性粒子引导至某个位置，通过非扰动电学测量来量化其存在。我们的实验演示目前有两个输入，可以使用交叉开关阵列设计进行扩展以适应多个输入和输出，可能接近在生物系统中观察到的能源效率。