Bayesian inference for precise and uncertainty-quantified single-shot widefield interferometric geometrical nanometrology

TL;DR

This paper introduces a Bayesian inference framework using Dynamic Nested Sampling for precise, uncertainty-quantified measurement of semiconductor optical waveguides from single-shot interferograms, eliminating the need for near-field microscopy.

Contribution

It presents a novel Bayesian-based analysis method for widefield interferometry that improves accuracy, quantifies uncertainty, and enhances robustness in nanometrology of semiconductor waveguides.

Findings

Achieves measurement accuracy down to 8 nm for waveguide dimensions

Provides uncertainty quantification alongside parameter estimates

Demonstrates robustness to noise through numerical and experimental validation

Abstract

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.