Abstract

An approach based on the Fisher information (FI) is developed to quantify the maximum information gain and optimal experimental design in neutron reflectometry experiments. In these experiments, the FI can be calculated analytically and used to provide sub-second predictions of parameter uncertainties. This approach can be used to influence real-time decisions about measurement angle, measurement time, contrast choice and other experimental conditions based on parameters of interest. The FI provides a lower bound on parameter estimation uncertainties, and these are shown to decrease with the square root of the measurement time, providing useful information for the planning and scheduling of experimental work. As the FI is computationally inexpensive to calculate, it can be computed repeatedly during the course of an experiment, saving costly beam time by signalling that sufficient data have been obtained or saving experimental data sets by signalling that an experiment needs to continue. The approach's predictions are validated through the introduction of an experiment simulation framework that incorporates instrument-specific incident flux profiles, and through the investigation of measuring the structural properties of a phospholipid bilayer.

Highlights

  • The Fisher information (FI) (Fisher, 1925) has been applied across many fields, from information theory and communications (Wang & Yin, 2010; Barnes et al, 2019) to quantum mechanics (Barndorff-Nielsen & Gill, 2000; Petz, 2002), quantitative finance (Taylor, 2019) and volcanology (Telesca et al, 2009)

  • We compare the results with established sampling methods and demonstrate the FI’s use for experimental design, and for potentially enabling early stopping of experiments based on counting statistics

  • We have presented a framework for determining the maximum information gain and experimental design optimization of neutron reflectometry experiments using the Fisher information

Read more

Summary

Introduction

The Fisher information (FI) (Fisher, 1925) has been applied across many fields, from information theory and communications (Wang & Yin, 2010; Barnes et al, 2019) to quantum mechanics (Barndorff-Nielsen & Gill, 2000; Petz, 2002), quantitative finance (Taylor, 2019) and volcanology (Telesca et al, 2009). Neutron reflectometry allows one to model a measured reflectivity curve in order to determine the properties of the thin-film layer structure that produced the curve. Most reflectometry analyses use sampling methods to extract parameter uncertainties, though this is expensive and cannot be performed in real time with current software (Nelson & Prescott, 2019; Kienzle et al, 2017; Hughes, 2017). We describe an application of the FI to neutron reflectometry in enabling real-time estimation of parameter uncertainties, as well as a projection of these with time. We compare the results with established sampling methods and demonstrate the FI’s use for experimental design, and for potentially enabling early stopping of experiments based on counting statistics

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call