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Machine learning-assisted high-accuracy and large dynamic range thermometer in high-Q microbubble resonators.

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    Multimode sensing using whispering gallery mode (WGM) resonators extracts more information than single-mode tracking. This advanced approach enhances measurement accuracy for applications like temperature detection.

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    Area of Science:

    • Optics and Photonics
    • Sensing Technologies
    • Machine Learning Applications

    Background:

    • Whispering gallery mode (WGM) resonators offer high sensitivity and fast response for precise measurements.
    • Traditional WGM sensing methods often ignore valuable data from multiple resonances, limiting performance.
    • Developing novel sensing strategies is crucial to fully leverage WGM resonator capabilities.

    Purpose of the Study:

    • To demonstrate that multimode sensing in WGM resonators contains more Fisher information than single-mode tracking.
    • To investigate the potential of multimode sensing for achieving superior measurement performance.
    • To develop an intelligent optical sensing system based on WGM resonators.

    Main Methods:

    • Utilizing a microbubble resonator as the sensing platform.
    • Implementing an automated experimental setup to collect multimode spectral signals.
    • Employing a generalized regression neural network (GRNN) machine learning algorithm for data analysis and temperature prediction.

    Main Results:

    • The multimode sensing method achieved an average temperature error of 3.8 × 10⁻³ °C within the 25.00°C to 40.00°C range.
    • Demonstrated that multimode sensing contains more Fisher information compared to single-mode tracking.
    • Analyzed the impact of data resources, including training data volume and temperature range variations, on prediction accuracy.

    Conclusions:

    • Multimode sensing significantly enhances the performance of WGM resonator-based sensors.
    • The developed GRNN-based temperature detection system exhibits high accuracy and a large dynamic range.
    • This work establishes a foundation for intelligent optical sensing utilizing WGM resonators.