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Teaching Liquid State Theory to an Artificial Neural Network (ANN)

Description

Schematic of the ANN method
Credit: Tyler Martin

 

Scientific questions:

  • Can an ANN allow us to predict the structure of fluids that are impossible to predict numerically via liquid-state theory?
  • Can we learn something about liquid-state theory itself by the nature of the trained ANN?
    • What features do the hidden layers capture?
  • Can experimental scattering data be used in the training of the ANN?
    • How does the mixing of synthetic and experimental data affect predictions?
  • Can we use the trained ANN to create a new liquid-state closure?
    • Closure approximations account for the majority of error in liquid state theory.
Created March 26, 2019, Updated March 27, 2019