Full Automation for Rapid Modulator Characterization and Accurate Analysis Using SciPy

TL;DR

This paper presents an automated approach using SciPy to streamline silicon modulator testing, including bias setting and data analysis, addressing complexities like hardware connections and optical distortions.

Contribution

It introduces a novel automation method leveraging SciPy for modulator characterization, simplifying complex testing procedures and improving measurement accuracy.

Findings

Automated bias setting reduces testing time.

Enhanced data analysis accuracy with SciPy tools.

Simplified testing process for silicon modulators.

Abstract

Modulator testing involved complex biasing conditions, hardware connections and data analysis. Also, any optical signal distortion due to the grating coupler effect could potentially induce additional difficulty in setting the correct bias condition for an accurate measurement of the modulator performance. In this paper, we proposed to use SciPy, an open-source scientific computing library, for automation in the silicon modulator test with bias setting and data analysis.