Photonic Encoding-Driven Neuromorphic and Cryptographic System Based on Oxide Semiconductor Device

Next-generation neuromorphic hardware must concurrently address computation, learning, and security demands. Here, a photonic-driven neuromorphic cryptographic platform based on an ITO/IGZO/TaN memristive device is reported. Under dual-wavelength optical stimuli (405 and 532 nm), the device emulates various synaptic plasticity behaviors, including spike-amplitude-dependent plasticity (SADP), spike-number-dependent plasticity (SNDP), and spike-rate-dependent plasticity (SRDP), enabling high-accuracy reservoir computing (88.39%) on Fashion Modified National Institute of Standards and Technology Database (FMNIST). Light-driven probabilistic learning using a Restricted Boltzmann Machine (RBM) achieved 95.06% image reconstruction accuracy via experimentally extracted sigmoid activation. Moreover, the device enables optical logic operations and generates robust physical unclonable functions by leveraging intrinsic material randomness and optical conductance modulation. This multifunctional platform offers a promising path toward secure, energy-efficient, and reconfigurable neuromorphic systems integrating memory, computation, and hardware-level encryption within a single device architecture.