<i>AutoRefl</i>: active learning in neutron reflectometry for fast data acquisition.

ABSTRACT: Neutron reflectometry (NR) is a powerful technique for interrogating the structure of thin films at interfaces. Because NR measurements are slow and instrument availability is limited, measurement efficiency is paramount. One approach to improving measurement efficiency is active learning (AL), in which the next measurement configurations are selected on the basis of information gained from the partial data collected so far. AutoRefl, a model-based AL algorithm for neutron reflectometry measurements, is presented in this manuscript. AutoRefl uses the existing measurements of a function to choose both the position and the duration of the next measurement. AutoRefl maximizes the information acquisition rate in specific model parameters of interest and uses the well defin

SUBMITTER: Hoogerheide DP 

PROVIDER: S-EPMC11771133 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature