| The Advanced Photon Source (APS) at Argonne organizes an ongoing seminar series, the APS Scientific Computation Seminar Series, focused on various aspects of computation for synchrotron science; talks are related to data analysis, reconstruction, theory, simulation, optimization, machine learning, automation, and visualization. The seminar provides an opportunity to present and learn about state-of-the-art software and the application of computational, AI/ML and mathematical techniques to synchrotron science. |
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| Title: | Accelerating Diffraction Analysis Using the MAUD Interface Language Kit (MILK) | | Presenter(s): | Dan Savage
Staff Scientist, Materials Science and Technology Division
Los Alamos National Laboratory (LANL) | | Date: | March 11, 2024 | | Time: | 1:00 PM (Central Daylight Savings Time) | | Location (hybrid): | Join ZoomGov Meeting
https://argonne.zoomgov.com/j/1601444470?pwd=N1phbHZVdCtmcVR5cGh0c1Zhc0…
Meeting ID: 160 144 4470
Passcode: 937918
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Meeting ID: 160 144 4470
Find your local number: https://argonne.zoomgov.com/u/af2crdvQy | | Abstract: | Diffraction experiments often result in tens to thousands of patterns from which information can be extracted ranging from microstructure to equation of state. The extraction happens by fitting models of the diffraction process which describe the instrument (e.g. sample-to-detector distances and angles), the sample’s crystal structure (e.g., crystallographic space group and lattice parameters), and the microstructure (e.g. phase fractions and texture).
Finding the set of parameters that best describes a measurement is hard to do in a robust way without expert intervention and in a way that leverages parallel resources (critical for real-time analysis). Benchmark examples of the open-source Python scripting framework for MAUD Rietveld software (MILK) will be presented with the Python Rietveld optimization and uncertainty quantification package (Spotlight) which together enable the scalable Rietveld optimization strategy for large datasets and advanced analysis workflows (e.g. sampling uncertainty in key parameters). |
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