Methodology study of machine learning for the neutron star equation of state

Understand

We discuss a methodology of machine learning to deduce the neutron star equation of state from a set of mass-radius observational data.

• We propose an efficient procedure to deal with a mapping from finite data points with observational errors onto an equation of state.
• We generate training data and optimize the neural network.
• Using independent validation data (mock observational data) we confirm that the equation of state is correctly reconstructed with precision surpassing observational errors.