Machine Learning Optimization of Surface-Normal Optical Modulators for SWIR Time-of-Flight 3-D Camera

作者：Bianconi Simone; Wheaton Skyler; Park Min Su; Nia Iman Hassani; Mohseni Hooman^*

来源：IEEE Journal of Selected Topics in Quantum Electronics, 2018, 24(6): 8201108.

DOI：10.1109/JSTQE.2018.2854566

• Electrooptic modulation
• quantum well devices
• Infrared imaging
• 3D imaging
• integrated optoelectronics

Surface-normal opticalmodulators based on multiple quantum wells are attractive for an increasing number of applications, including photonic links such as on-chip optical interconnects. The design of such structures however is still based on intuition and experience rather than on a quantitative assessment of the device and system performance, due to the extreme complexity of the device behavior and the large number of design parameters involved. We developed a method for the systematic optimization of the modulator design, using a combination of analytical modeling and supervised machine learning. The global optimization is driven by an evolutionary algorithm, and the robustness of the final results is evaluated using variance-based sensitivity analysis. The optimization algorithm was tested on the case of time-of-flight three-dimensional camera (ranging) application, yielding two novel optimized designs which allow for a considerable improvement of the depth resolution of the system. Finally, we propose a figure of merit for comparing the modulation efficiency of surface-normal modulators.

• 出版日期2018-12
• 单位西北大学