Multi-Parameter Sensing in a Multimode Self-Interference Micro-Ring Resonator by Machine Learning

Dong Hu; Chang-Ling Zou; Hongliang Ren; Jin Lu; Zichun Le; Yali Qin; Shunqin Guo; Chunhua Dong; Weisheng Hu

doi:10.3390/s20030709

Multi-Parameter Sensing in a Multimode Self-Interference Micro-Ring Resonator by Machine Learning

Sensors (Basel). 2020 Jan 28;20(3):709. doi: 10.3390/s20030709.

Authors

Dong Hu¹, Chang-Ling Zou², Hongliang Ren¹, Jin Lu¹, Zichun Le³, Yali Qin¹, Shunqin Guo¹, Chunhua Dong², Weisheng Hu⁴

Affiliations

¹ College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
² Key Lab of Quantum Information, University of Science and Technology of China, Hefei 230026, China.
³ College of Science, Zhejiang University of Technology, Hangzhou 310023, China.
⁴ State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, Shanghai 200240, China.

Abstract

A universal multi-parameter sensing scheme based on a self-interference micro-ring resonator (SIMRR) is proposed. Benefit from the special intensity sensing mechanism, the SIMRR allows multimode sensing in a wide range of wavelengths but immune from frequency noise. To process the multiple mode spectra that are dependent on multiple parameters, we adopt the machine learning algorithm instead of massive asymptotic solutions of resonators. Employing the proposed multi-mode sensing approach, a two-parameter SIMRR sensor is designed. Assuming that two gases have different wavelength dependence of refractive indices, the feasibility and effectiveness of the two-parameter sensing strategy are verified numerically. Moreover, the dependence of parameter estimation accuracy on the laser intensity noises is also investigated. The numerical results indicate that our scheme of multi-parameter sensing in a multimode SIMRR holds great potential for practical high-sensitive sensing platforms compared with the single-mode sensing based on whispering gallery mode (WGM) resonators.

Keywords: artificial neuron network; dissipative sensing; machine learning; multimode sensing; multiparameter sensing; self-interference micro-ring resonator (SIMRR).