Boltzmann distribution Image Credit: Reprinted with permission from: F. Noé et al., Science 365, eaaw1147 (2019). aaw1147
Scientists at Freie Universität Berlin develop a deep learning method to solve a fundamental problem in statistical physics. No 255/2019 from Sep 05, 2019 A team of scientists at Freie Universität Berlin has developed an Artificial Intelligence (AI) method that provides a fundamentally new solution of the "sampling problem" in statistical physics. The sampling problem is that important properties of materials and molecules can practically not be computed by directly simulating the motion of atoms in the computer because the required computational capacities are too vast even for supercomputers. The team developed a deep learning method that speeds up these calculations massively, making them feasible for previously intractable applications. "AI is changing all areas of our life, including the way we do science," explains Dr. Frank Noé, professor at Freie Universität Berlin and main author of the study. Several years ago, so-called deep learning methods bested human experts in pattern recognition - be it the reading of handwritten texts or the recognition of cancer cells from medical images. "Since these breakthroughs, AI research has skyrocketed.
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