Neural networks reconstruction of the dense-matter equation of state from neutron-star parameters

Understand

Aims: The aim of this work is to study the application of the artificial neural networks guided by the autoencoder architecture as a method for precise reconstruction of the neutron star equation of state, using their observable parameters: masses, radii and tidal deformabilities.

• In addition we study how well the neutron star radius can be reconstructed using the gravitational-wave only observations of tidal deformability, i.e.
• quantities which are not related in a straightforward way.
• Methods: Application of artificial neural network in the equation of state reconstruction exploits the non-linear potential of this machine learning model.