Optimization of Structural Parameters of PCF Polarization Filter by a Genetic Algorithm

Abstract

The material and geometry of photonic crystal fiber (PCF) are significant adjustable characteristics, and affect its optical properties. Finding the global optimal fiber is formulated as an optimization problem, and intelligent algorithms are used for the complex objective optimization. This paper presents the optimal structure of PCF for polarization filter determined by the Genetic Algorithm (GA) method, and the fitness function of GA is defined relatedly to the polarization filter optical index crosstalk (CT) and bandwidth. The designed PCF polarization filter has the following characteristics: the CT reaches 1845.3113 dB at 1.55 μm. When the fiber length is limited to 1000 nm, the bandwidth value exceeds 800 nm. Numerical results demonstrate that the performance of the designed PCF filter is better than that of the original and also have proved the GA method is beneficial to the design and fabrication of optical fibers.