Generalized optical design and optimization of multipass cells with independent circle patterns based on the Monte Carlo and Nelder-Mead simplex algorithms.

Abstract

In this paper, we propose an automatic approach to optimize the multipass cell (MPC) design with independent circle patterns. First, the Monte Carlo algorithm is performed to globally search for the characteristic values of the distance between two mirrors. Second, the Nelder-Mead simplex (NM) algorithm is applied to locally optimize the re-entry condition. In addition, we utilize the clustering method to select the independent circle patterns automatically. Three optimal MPCs with five, seven and nine independent circles are built and tested experimentally. We analyze the stability of the final point for the MPCs and optimize the quality of the output beam based on multi-ray tracing. This type of MPC shows the superior characteristics of compactness, high detection sensitivity, and affordability, has various applications, and can promote the development of portable gas sensors. The proposed approach is effective and efficient for automatically optimizing MPC design and can be further extended to versatile optical designs.