DeepMind open-sources DM21, an AI model for quantum chemistry

DM21 uses a neural network to approximate the energy function component of Density Functional Theory.

Researchers at DeepMind have open-sourced DM21, a neural network model for mapping electron density to chemical interaction energy, a critical component of quantum mechanical modelling. DM21 outperforms standard models on various benchmarks, and it’s accessible as a PySCF simulation framework addition.

DM21 uses a neural network to approximate the energy function component of Density Functional Theory (DFT) which describes the quantum mechanical behaviour of molecules.

“By expressing the functional as a neural network and incorporating these exact properties into the training data, we learn functionals free from important systematic errors — resulting in a better description of a broad class of chemical reactions,” said DeepMind researchers.

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The researchers used supervised learning to train an MLP neural network. The training dataset consisted of 1161 examples; the inputs contained Kohn-Sham (KS) orbital features sampled on a spatial grid, while the output values were “high-accuracy reaction energies.” 

Researchers tested DM21 on three benchmarks, including GMTKN55 and QM9, which contain data for chemical tasks “very distinct” from the training data. DM21 set new state-of-the-art performance on these benchmarks, outperforming four previous methods.

“DM21 is better than the best hybrid functional and approaches the performance of the much more expensive double-hybrid functionals,” said researchers.

DM21 was able to achieve greater accuracy in modelling the quantum mechanical behaviour of electrons.

SharathKumar Nair
Sharath is an ardent believer in the ‘Transhumanism’ movement. Anything and everything about technology excites him. At Analytics India Magazine, he writes about artificial intelligence, cybersecurity and the impact these emerging technologies have on day-to-day human lives. When not working on a story, he spends his time reading tech novels and watching sci-fi movies and series.

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