Quasi-Monte Carlo Technique With the Halton Sequence Applied To Mushroomwaveguide Photodetectors (WGPDs)

Monte Carlo (MC) simulation is a widely adopted computational method that relies on random sampling, but it is susceptible to exhibiting patterns and biases due to the use of pseudo-random numbers. In contrast, Quasi-Monte Carlo (QMC) techniques employ low discrepancy sequences, resulting in more evenly distributed random numbers and the potential for more accurate and reliable simulation outcomes. Mushroom-Waveguide Photodetectors (WGPDs) are integrated to a wide range of applications, and their performance is critically dependent on precise dimensional parameters. In this research, we investigate the utilization of QMC simulations to enhance the accuracy of the bandwidth calculations of Mushroom-WGPDs. In the presented study, we have employed QMC simulations in combination with a drift diffusion model to comprehensively analyze the influence of dimensional tolerances on the mean and the standard deviations of the bandwidth of Mushroom-WGPDs for various biasing. The model used in our work encompasses a thorough consideration of material properties, photodetector dimensions, structural characteristics, biasing configurations, and parasitic effects, offering a holistic approach to Mushroom-WGPD analysis. This study also includes a comparative analysis, which sets the results of stochastic analysis using QMC against the traditional MC technique. This comparison demonstrates the superior efficiency and accuracy of the Quasi-Monte Carlo approach for photodetector analysis.