Inferring phase transitions and critical exponents from limited observations with thermodynamic maps.

ABSTRACT: Phase transitions are ubiquitous across life, yet hard to quantify and describe accurately. In this work, we develop an approach for characterizing generic attributes of phase transitions from very limited observations made deep within different phases' domains of stability. Our approach is called thermodynamic maps (TM), which combines statistical mechanics and molecular simulations with score-based generative models. TM enable learning the temperature dependence of arbitrary thermodynamic observables across a wide range of temperatures. We show its usefulness by calculating phase transition attributes such as melting temperature, temperature-dependent heat capacities, and critical exponents. For instance, we demonstrate the ability of TM to infer the ferromagnetic phase transition of the

SUBMITTER: Herron L 

PROVIDER: S-EPMC11670242 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature