Machine learning aided design and optimization of MEMS optical phased array with silicon micro mirrors for nanofabrication

The integration of microelectromechanical systems (MEMS) with optical phased arrays (OPAs) has emerged as a promising approach for advanced optical beam steering applications. This paper presents a comprehensive study on the design and optimization of a MEMS optical phased array utilizing silicon micromirrors for precise beam manipulation. Leveraging machine learning techniques, we propose a novel methodology for the efficient exploration of the vast design space, enabling rapid identification of optimal geometrical parameters. The MEMS OPA design is coupled with nanofabrication constraints, ensuring practical feasibility. Through rigorous simulations and iterative refinement, our approach achieves significant improvements in beam steering accuracy, speed, and efficiency. The resulting MEMS OPA demonstrates exceptional performance characteristics, showcasing its potential in next-generation photonics systems. This work highlights the synergy between MEMS, optics, and machine learning, paving the way for enhanced nanofabrication techniques and advanced optical devices.