Synthetic Dataset for Analyzing Geometry-Dependent Optical Properties of All-Pass Micro-Ring Resonators

This study focuses on the analysis of the spectral response of all-pass micro-ring resonators (MRRs), which are essential in photonic device applications such as telecommunications, sensing, and optical frequency comb generation. The aim of this work is to generate a synthetic dataset that explores the spectral characteristics of the expected transmission spectra of MRRs by varying their structural parameters. Using numerical simulations, the dataset will allow the optimization of MRR performance metrics such as free spectral range (FSR), full width at half maximum (FWHM), and quality factor (Q-factor). The results confirm that variations in geometric configurations can significantly affect MRR performance, and the dataset provides valuable insights into the optimization process. Furthermore, machine learning techniques can be applied to the dataset to automate and improve the design process, reducing simulation times and increasing accuracy. This work contributes to the development of photonic devices by providing a broad dataset for further analysis and optimization.