A Machine Learning Approach for Understanding Chiral Materials

Machine learning has proven to be a very useful tool for analysis of materials science. In the search for qubits, we aim to use machine learning to find skyrmions and categorize quantum spin liquids by developing a machine learning model to predict a material's exchange parameters. Knowing the exchange parameters of a material J1,J2,J3 will allow us insight into the properties of different materials and accelerate further research into applications of skyrmions and quantum spin liquids.