High-speed, ultra-low-power, and robust superconductive neuron with ReLU activation
Yuto Ueno, Yuki Hironaka, Nobuyuki Yoshikawa, Yuki Yamanashi · Neuromorphic Computing and Engineering · 2025
Abstract We propose a novel ultra-high-speed neuron device utilizing a superconductive single flux quantum (SFQ) circuit to realize an ideal rectified linear unit (ReLU) activation function. This circuit generates quantum-accurate voltage output through frequency conversion within the SFQ digital circuit. A significant advantage of this design is its combination of high-speed and ultra-low-power operation with inherent tolerance to device parameter variations. This crucial feature mitigates performance degradation often observed in large-scale neural networks that rely on analog neuron circuits susceptible to characteristic variation of neuron devices. We designed and implemented the proposed neuron circuit using a 10 kA cm−2 Nb four-layer 1.0 μm fabrication process. Experimental measurements at 4.2 K confirmed correct operation up to approximately 41.2 GHz input. Results from multiple chips successfully demonstrated ideal ReLU input–output characteristics, showcasing both the high-speed nature of the device and the scalability and robustness of our neuron circuits for next-generation artificial neural network hardware.