AI estimation of partition functions with the PULSE method for the thermodynamic properties of disordered compounds
The PULSE method uses an unsupervised machine learning approach to estimate partition functions for chemically disordered materials. It was tested on the 2D Ising model, showing it can accurately predict thermodynamic properties with very few samples, significantly reducing computational cost compared to traditional Monte Carlo methods.