Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state

Understand

The difficulty in describing the equation of state (EoS) for nuclear matter at densities above the saturation density ($\rho_0$) has led to the emergence of a multitude of models based on different assumptions and techniques.

• These EoSs, when used to describe a neutron star (NS), lead to differing values of observables.
• An outstanding goal in astrophysics is to constrain the dense matter EoS by exploiting astrophysical and gravitational wave measurements.
• Nuclear matter parameters appear as Taylor coefficients in the expansion of the EoS around the saturation density of symmetric and asymmetric nuclear matter and provide a physically-motivated representation of the EoS.