CUDA-based optical parametric oscillator simulator

Abstract

The coupled-wave equations (CWEs) in nonlinear optics are the fundamental starting point in the study, analysis, and understanding of various frequency conversion processes in dielectric media subjected to intense laser radiation. In this work, a useful package for the modeling of optical parametric oscillators (OPOs) based on the Split-Step Fourier Method algorithm is presented. The algorithm is scripted in the CUDA programming language in order to speed up the calculations and obtain results in a relatively short time frame by using a graphics processing unit (GPU). Our results show a speedup higher than 50X for vector size of 214 in comparison with the analogous code scripted for running only in CPU. The package implements the CWEs to model the propagation of light in second-order nonlinear crystals widely used in optical frequency conversion experiments. In addition, the code allows the user to adapt the cavity configuration by selecting the resonant electric fields and/or incorporating intracavity elements. The package is useful for modeling OPOs or other mathematically similar problems. Program summaryProgram Title:cuOPOCPC Library link to program files:https://doi.org/10.17632/5djxwg4fbp.1Developer's repository link:https://github.com/alfredos84/cuOPOLicensing provisions: MITProgramming language: CUDANature of problem: The problem that is solved in this work is that of two or three coupled differential equations that describe the propagation of light in a second order nonlinear medium, allowing the three-wave mixing process. By placing the medium in an optical cavity, an optical parametric oscillator is formed. The optical cavity is modeled by including the appropriate boundary conditions for the differential equations. As a result we obtain the electric fields of the interacting waves in the time and frequency domains.Solution method: The coupled differential equations are solved using the well-known fixed-step Split-Step Fourier method. Due to the eventual computational demand that some problems may have, we chose to implement the coupled equations in the CUDA programming language. This allows us to significantly speed up simulations, thanks to the computing power provided by a graphics processing unit (GPU) card. The output files obtained are the interacting electric fields, which have to be analyzed during post-processing.