Quantum Complexity Tamed by Machine Learning

Recent work done by Marivi Fernández-Serra and former student Sebastian Dick was highlighted in Quanta Magazine.

“ "These machine learning methods,” said Marivi Fernández-Serra, a condensed matter physicist at Stony Brook University, “they got to where the field was in a couple of years and have already surpassed it." ”

" The development of new functionals like those of Fernández-Serra and DeepMind suggests that machine learning can be a powerful tool for exploring new regions of the universal density functional, particularly those corresponding to molecules and chemistry. "

The highlighted work, published in Physical Review B, can be found here.