DS4MS

Motivation

‍The goal of the project is to develop a generic, automized method of fitting a signal of neutron scattering data in the presence of background noise. The first goal is to capture separately the signal and the background noise. We then aim at improving the data collection process through an intelligent decision making algorithm that will determine when a sufficient amount of neutrons has been collected in an arbitrary measurement setting.

Proposed Approach / Solution

SDSC developed ML models and optimization algorithms to tackle the fitting problem and the decision-making problem. First, we designed  a denoising algorithm that extracts the signal from the noisy observations (Fig. 2). The solution is based on the resolution of a regularized problem that leverages the rotation invariance property of the background noise. The solution was implemented in the MJOLNIR software that treats the collected data. Second, the approach identified the regions that require more measurement to get a good signal-to-noise ratio. We used a stopping criterion ensuring that enough have been collected to get a good signal-to-noise ratio.

Impact

‍The outcomes of the project will help to exploit collected data and further improve the use of the multiplexing instrument (Fig. 1) by reducing beam time and by providing more insights in the scattering data analysis. This approach could be also adapted for different application including time-of-light neutron spectroscopy.