Artificial intelligence can reduce a quantum physics problem with 100,000 equations to four equations
Artificial intelligence has allowed physicists to compress a quantum problem, which previously required 100,000 equations, into four simple equations. This was done without sacrificing accuracy. This work, which was published in Physical Review Letters on September 23, could revolutionize the way scientists study systems with many interacting electronic particles. If the method can be applied to other problems, it could help in the development of materials that have desirable properties, such as superconductivity, or are useful for the generation of clean energy.
\”We begin with this large object of coupled differential equations, and then use machine learning to reduce it down so small that you can count them on your fingers,\” said Domenico Di Sante. He is a visiting researcher at the Flatiron Institute’s Center for Computational Quantum Physics in New York City.
The problem is how electrons move in a grid-like lattice. Two electrons that occupy the same site on the lattice interact. The Hubbard model is a simplified version of important materials. It allows scientists to study how electron behavior leads to desired phases of matter such as superconductivity. This model is also used to test new methods, before they are applied to more complex quantum systems.