Bayesian Optimization for Simultaneous Noise Reduction and Property Discovery in Automated Experiments

This paper introduces a novel Bayesian Optimization (BO) workflow that integrates real-time noise optimization into automated experiments, improving data quality, and reducing resource expenditure by balancing signal-to-noise ratio and experimental duration.