Integrated $3 \times 3 \beta-\text{Ga}_{2} \mathrm{O}_{3}$ Optoelectronic Synaptic Array for Efficient Edge Detection in Neuromorphic Computing

Neuromorphic visual sensors, inspired by retinal neuron synapses, have garnered significant attention in the field of novel optoelectronic imaging and sensing. In this work, we fabricated a novel$3 \times 3 \beta-\text{Ga}_{2} \mathrm{O}_{3}$optoelectronic synaptic array by introducing additional oxygen vacancies to achieve persistent photoconductivity. This enables the device to emulate critical biological synaptic characteristics, such as short-term plasticity and learning-forgetting-relearning cycles, which are essential for dynamic data processing. We demonstrated the potential of a$\beta - \text{Ga}_{2} \mathrm{O}_{3}$optoelectronic synaptic array in convolutional image processing, where it successfully extracted various features using multiple convolutional kernels. Our work provides a promising hardware platform for efficient and scalable$\beta-\text{Ga}_{2} \mathrm{O}_{3}$-based neuromorphic computing.