Quantum chemistry, the study of chemical properties and processes at the quantum scale, has opened many paths to research and discovery in modern chemistry. Without ever handling a beaker or a test tube, chemists can make predictions about the properties of a given atom or molecule and how it will undergo chemical reactions by studying its electronic structure—how its electrons are arranged in orbitals—and how those electrons interact with those of other compounds or atoms. While quantum chemistry consumes a large fraction of computation power on the world's supercomputers, a new tool, OrbNet, uses machine learning to empower quantum-chemistry calculations to be performed 1,000 times faster than previously possible, allowing accurate quantum chemistry research to be performed faster than ever before. OrbNet innovates the way in which atoms and molecules are represented based around the Schrödinger equation, a piece of mathematics central to quantum mechanics. Leveraging this knowledge, OrbNet can accurately perform quantum chemistry calculations on molecules as much as 10 times larger than the molecules present in training data.

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"Machine Learning Speeds Up Quantum Chemistry Calculations"