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The overall design of the Integrated Spectral Analysis Workbench (ISAW), being developed at Argonne, provides for an extensible, highly interactive, collaborating set of viewers for neutron scattering data. Large arbitrary collections of spectra from multiple detectors can be viewed as an image, a scrolled list of individual graphs, or using a 3D representation of the instrument showing the detector positions. Data from an area detector can be displayed using a contour or intensity map as well as an interactive table. Selected spectra can be displayed in tables or on a conventional graph. A unique characteristic of these viewers is their interactivity and coordination. The position pointed at by the user in one viewer is sent to other viewers of the same DataSet so they can track the position and display relevant information. Specialized viewers for single crystal neutron diffractometers are being developed. A proof-of-concept viewer that directly displays the 3D reciprocal lattice from a complete series of runs on a single crystal diffractometer has been implemented.
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
A principal component analysis (PCA) of clean microcalorimeter pulse records can be a first step beyond statistically optimal linear filtering of pulses towards a fully non-linear analysis. For PCA to be practical on spectrometers with hundreds of se
China Spallation Neutron Source (CSNS) is the first high-performance pulsed neutron source in China, which will meet the increasing fundamental research and technique applications demands domestically and overseas. A new distributed data processing a
ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independe
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