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Novel multiplexing triple-axis neutron scattering spectrometers yield significant improvements of the common triple-axis instruments. While the planar scattering geometry keeps ensuring compatibility with complex sample environments, a simultaneous detection of scattered neutrons at various angles and energies leads to tremendous improvements in the data acquisition rate. Here we report on the software package MJOLNIR that we have developed to handle the resulting enhancement in data complexity. Using data from the new CAMEA spectrometer of the Swiss Spallation Neutron Source at the Paul Scherrer Institut, we show how the software reduces, visualises and treats observables measured on multiplexing spectrometers. The software package has been generalised to a uniformed framework, allowing for collaborations across multiplexing instruments at different facilities, further facilitating new developments in data treatment, such as fitting routines and modelling of multi-dimensional data.
A reliable and user-friendly characterisation of nano-objects in a target material is presented here in the form of a software data analysis package for interpreting small-angle X-ray scattering (SAXS) patterns. When provided with data on absolute sc
Neutron direct-geometry time-of-flight chopper spectroscopy is instrumental in studying fundamental excitations of vibrational and/or magnetic origin. We report here that techniques in super-resolution optical imagery (which is in real-space) can be
Autonomous experiments are excellent tools to increase the efficiency of material discovery. Indeed, AI and ML methods can help optimizing valuable experimental resources as, for example, beam time in neutron scattering experiments, in addition to sc
The Mantid framework is a software solution developed for the analysis and visualization of neutron scattering and muon spin measurements. The framework is jointly developed by software engineers and scientists at the ISIS Neutron and Muon Facility a
PyUnfold is a Python package for incorporating imperfections of the measurement process into a data analysis pipeline. In an ideal world, we would have access to the perfect detector: an apparatus that makes no error in measuring a desired quantity.