Detection of Topological Materials with Machine Learning

Understand

Databases compiled using ab-initio and symmetry-based calculations now contain tens of thousands of topological insulators and topological semimetals.

• This makes the application of modern machine learning methods to topological materials possible.
• Using gradient boosted trees, we show how to construct a machine learning model which can predict the topology of a given existent material with an accuracy of 90%.
• Such predictions are orders of magnitude faster than actual ab-initio calculations.