Whispering gallery mode (WGM) microresonators emerged as a promising platform for highly sensitive sensing applications due to their high-quality factors and small mode volumes. They offer the advantages of the ultrahigh sensitivity and compact size, rendering them suitable across multiple fields. A stable encapsulation process is essential for practical applications to establish a reliable coupling system between the microcavity and its waveguide coupler, especially for the microtoroidal resonator and tapered fiber coupler. However, adjusting the coupling coefficient after the packaging process poses challenges, thereby compromising coupling accuracy and limiting its range of applications. It is imperative to provide a platform of tunable coupling for packaged WGM resonators. Here, we provide an approach for leveraging the magnetostrictive effect to dynamically regulate the fiber-cavity coupling, enabling the measurement of the magnetic field as an example. Moreover, we show the fine-tuning of coupling within the packaged WGM microresonator, allowing the precision control of the optomechanical effect. Through this method, a tunable coupling platform in a packaged system is realized, opening up new dimensions of research in various fields.

Convolutional Neural Network（CNN）has shown a wide range of applications in the fields of face recognition, image classification, machine vision, medical imaging, and aerospace due to its excellent feature extraction capabilities. However, traditional electrical intelligent processing chips are restricted by Moore’s law, and is difficult to meet the continuous growth of CNN computing power demand. With its characteristics of ultra-large broadband and ultra-low loss, light wave is a disruptive technology that supports the high computing power demand of the next generation of artificial intelligence. With optical or electrical high-dimensional control structure as the basic unit, it can realize computing through controlled propagation of light. In this paper, the research progress and technological breakthroughs of optical convolutional neural networks are reviewed. The overall trend of their development and the technical problems that need to be solved in the future are summarized. The prospects of optical convolutional neural networks for application are also discussed.