Advanced geometrical nanometrology is critical for process control in semiconductor manufacturing, supporting applications in, e.g., photonic integrated circuits, nanoelectronics, and emerging quantum and optoelectronic technologies. Widefield interferometric approach provide a cost-effective, non-destructive solution for characterizing semiconductor optical waveguides, which are fundamental to nanophotonic devices. This work presents a Bayesian inference framework, implemented using Dynamic Nested Sampling, for estimating geometric parameters - such as width and height - of a semiconductor optical waveguide from a single widefield interferogram. The proposed framework reduces the need of leveraging near field scanning microscopy methods for measurements. The notable advantage is that Bayesian statistics not only provide the estimated parameter values but also quantify the uncertainty of the inference results and the fitness of the used model. The proposed full-field, single-shot interferometric approach, supported by Bayesian-based data analysis, achieves high accuracy and sensitivity - down to successful measurement of 8 nm rib waveguide - while remaining resilient to noise. Thus, the demonstrated methodology provides a cost-effective, robust, and scalable tool for semiconductor fabrication monitoring and process verification, as confirmed by both numerical simulations and experimental validation on optical waveguides. This method contributes to high-precision nanometrology by integrating advanced statistical modeling and inference techniques.

翻译：先进的几何纳米计量对于半导体制造中的工艺控制至关重要，支持光子集成电路、纳米电子学以及新兴量子与光电子技术等应用。宽场干涉方法为表征半导体光波导提供了一种成本效益高、非破坏性的解决方案，而光波导是纳米光子器件的基础。本研究提出了一个基于动态嵌套采样实现的贝叶斯推断框架，用于从单张宽场干涉图中估计半导体光波导的几何参数（如宽度和高度）。该框架减少了对近场扫描显微测量方法的依赖。其显著优势在于，贝叶斯统计不仅提供参数估计值，还能量化推断结果的不确定性及所用模型的拟合度。所提出的全场单次干涉方法，辅以基于贝叶斯的数据分析，实现了高精度与高灵敏度——可成功测量低至8纳米的脊形波导——同时保持对噪声的鲁棒性。因此，经数值模拟和光波导实验验证证实，该方法为半导体制造监控与工艺验证提供了一种成本效益高、稳健且可扩展的工具。通过整合先进的统计建模与推断技术，本方法为高精度纳米计量学做出了贡献。