Abstract
Silicon photonic spatial heterodyne Fourier transform spectrometers (SH-FTSs) are attractive with chip-scale monolithic arrays of imbalanced Mach–Zehnder interferometers; however, there exist optical path difference (OPD) errors from the inevitable fabrication imperfection, which will severely distort the retrieved spectra. In this Letter, we propose that a predictive model can be created for rapid and accurate spectral recovery based on the conditional generative adversarial network (cGAN) featuring strong input-on-output supervision, instead of both complicated physical OPD modification and time-consuming iterative spectral calculation. As a demonstration, cGAN spectral prediction was performed for our previously presented dual-polarized SH-FTS with large OPD errors [Opt. Lett. 44, 2923 (2019) [CrossRef] ]. Due to the strong noise-resistant capability, the cGAN-predicted spectra can stay reliable, even though the signal-to-noise ratio of acquired interferograms dramatically drops from 1000 to 100, implying a lower limit of detection.
© 2021 Optical Society of America
Full Article | PDF ArticleMore Like This
Huijie Wang, Zhongjin Lin, Qifeng Li, and Wei Shi
Opt. Lett. 44(11) 2923-2926 (2019)
Huijie Wang, Qifeng Li, and Wei Shi
Opt. Lett. 45(6) 1479-1482 (2020)
Junjie Du, Hongyi Zhang, Xinyi Wang, Weihan Xu, Liangjun Lu, Jianping Chen, and Linjie Zhou
Opt. Lett. 47(2) 218-221 (2022)