Demonstrates improved image recognition in neuromorphic systems, indicating efficiency and compactness benefits.
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 RuO 2 . 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 RuO 2 , 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.
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Zeng et al. (2026) studied this question.
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