Affiliation:
1. Korea Advanced Institute of Science and Technology
Abstract
The whispering gallery mode (WGM) optical microresonator sensors are emerging as a promising platform for precise temperature measurements, driven by their excellent sensitivity, resolution and integration. Nevertheless, challenges endure regarding stability, single resonant mode tracking, and real-time monitoring. Here, we demonstrate a temperature measurement approach based on convolutional neural network (CNN), leveraging the recognition of multimode barcode images acquired from a WGM microbottle resonator (MBR) sensor with robust packaged microresonator-taper coupling structure (packaged-MTCS). Our work ensures not only a high sensitivity of −14.28 pm/℃ and remarkable resolution of 3.5 × 10−4 ℃ across a broad dynamic range of 96 ℃ but also fulfills the demands for real-time temperature measurement with an average detection accuracy of 96.85% and a speed of 0.68s per image. These results highlight the potential of high-performance WGM MBR sensors in various fields and lay the groundwork for stable soliton microcomb excitation through thermal tuning.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Young Elite Scientists Sponsorship Program by CAST
Subject
Atomic and Molecular Physics, and Optics