UWM Researchers Develop a Machine-Learning Algorithm for Resolving Time Sequences in High-Speed Data Collection
Two University of Wisconsin – Milwaukee (UWM) Physics department researchers, working with an international team of scientists, have developed and tested a machine-learning algorithm for reducing timing uncertainties during fast changing events. The efforts of UWM Distinguished Professor Abbas Ourmazd and Senior Scientist Russell Fung, working with data from a project tracking the movement of molecules, led to the creation of the computer algorithm. The project utilized an X-ray free electron laser (XFEL), the world’s brightest X-ray laser located at the SLAC National Accelerator Laboratory, to track the movements of molecules as the bonds holding their atoms together were torn apart. The sequence of events in this high-speed process are somewhat scrambled and the algorithm helps to reconstruct a clear vision of how the molecules are affected by exposure to the intense electron laser beam. The research team sees further applications for the algorithm in other sciences where dynamical histories are imprecisely known. More information can be found at UWM researchers create a better way to find out ‘when’.