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JAIST Researchers Use Deep Learning to Unlock X-ray Diffraction Secrets

JAIST Researchers Use Deep Learning to Unlock X-ray Diffraction Secrets
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New quantum approach helps solve an old problem in materials science

 E-Mail IMAGE: In this figure, the hopping amplitude and existence of possible pathways for atomic migrations [panel (a)] can be identified at the microscopic level. But it is not easy to count. view more  Credit: Ryo Maezono from JAIST Ishikawa, Japan - One of the most important classes of problems that all scientists and mathematicians aspire to solve, due to their relevance in both science and real life, are optimization problems. From esoteric computer science puzzles to the more realistic problems of vehicle routing, investment portfolio design, and digital marketing at the heart of it all lies an optimization problem that needs to be solved.

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