Analytical expression and neural network study of the symmetry energy

Motivated by classical molecular dynamics simulations of infinite nuclear systems with varying density, temperature and isospin content, an analytical expression that approximates the symmetry energy at subcritical densities is obtained. Similarly a neural network is used to evaluate E Sym in the same temperature-density regime. The resulting expression and neural network can both be used to calculate the symmetry energy at a given density and temperature or, conversely, to extract the temperature of experimental data.