Field-Free Spin-Splitting-Torque Driven Stochastic Neuron Mimicking the Neuromorphic Imagination for High-Performance Recognition.

The human brain can construct coherent spatial imagery in the absence of sensory input-an "imagination" capability that complementary metal-oxide-semiconductor transistor (CMOS)-based artificial neural networks (ANNs) struggle to replicate with comparable energy efficiency and architectural compactness. Realizing this function in hardware requires a single spintronic device that simultaneously provides field-free switching and intrinsic, Gaussian-distributed stochasticity; yet such devices have not been reported to date. Here, we report field-free spintronic neuromorphic devices that exploit the spin-splitting effect of altermagnetic RuO2. The resulting stochastic neuron exhibits Gaussian-distributed outputs, which reduces the number of devices required by about 87%. Benefiting from the high thermal conductivity and micrometer footprint of RuO2, transient Joule heating drives stochastic, field-free magnetization reversal in the adjacent Co/Pt multilayer. Leveraging these devices, we implement an all-spin ANN to restore CIFAR-10 images with 50% occlusion. The reconstructed images achieve a high Fréchet Inception Distance score of 1.98 and a classification accuracy of ∼90%, and a 3.75-fold improvement in recognition performance. Our work establishes an energy-efficient, hardware-level pathway toward brain-inspired imagination systems, advancing the functional emulation of cortical associative processes.