Unlocking a New Phase of Solid Hydrogen with Machine Learning Simulations

A machine-learning model can predict the new phase of solid hydrogen

Hydrogen is the most abundant element of the universe. It can be found in many places, from dust that fills most of outer space, to the cores and surfaces of stars, to substances on Earth. Hydrogen is the most abundant element in the universe. It can be found everywhere, from outer space dust to the cores of stars and many substances on Earth. David Ceperley is a professor of Physics at the University of Illinois Urbana-Champaign. He believes that hydrogen is the perfect starting point to formulate and test theories of matter.

Ceperley is also a member at the Illinois Quantum Information Science and Technology Center. He uses computer simulations in order to study how hydrogen molecules interact and combine into different phases of matter, such as solids, liquids and gases. Quantum mechanics is required to fully understand these phenomena, but quantum mechanical simulations can be expensive. Ceperley, along with his collaborators, developed a machine-learning technique to simplify the task. This allows for quantum mechanical simulations that can be run on an unprecedented number atoms. In Physical Review Letters, they reported that their method discovered a new type of high-pressure liquid hydrogen that previous theory and experiments had missed.

Ceperley stated that \”machine learning taught us a lot.\” We had seen signs of new behaviors in our previous simulations but didn’t believe them because they could only accommodate a small number of atoms. Our machine learning model allowed us to take advantage of the most accurate methods, and we could see what was really happening.


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