Design Optimization of Ultra-High-Speed Photonic Devices based on InP Technology using Genetic Algorithms

Abstract

The exponential growth in global data traffic necessitates the development of next-generation optical communication systems capable of operating at symbol rates exceeding 100 Gbaud. Indium Phosphide (InP) technology stands at the forefront of this evolution due to its superior electron mobility and direct bandgap properties, which are critical for the realization of active high-speed photonic components. However, the design of such ultra-high-speed devices, particularly modulators and detectors, involves a complex interplay of optical and radio-frequency (RF) electrical constraints that renders traditional analytical design methodologies insufficient. This paper presents a comprehensive study on the application of Genetic Algorithms (GA) for the global optimization of InP-based photonic devices. We propose a robust optimization framework that couples evolutionary computation with full-wave electromagnetic solvers to navigate the multi-dimensional parameter space of photonic integrated circuits. By optimizing the geometric parameters of a Mach-Zehnder Modulator (MZM), we demonstrate a significant enhancement in electro-optic bandwidth and a reduction in insertion loss compared to standard designs. The results indicate that stochastic optimization methods can effectively overcome the limitations of manual tuning, paving the way for Terabit-scale optical interconnects.