Nonparametric Representation of Neutron Star Equation of State Using Variational Autoencoder

Understand

We introduce a new nonparametric representation of the neutron star (NS) equation of state (EoS) by using the variational autoencoder (VAE).

• As a deep neural network, the VAE is frequently used for dimensionality reduction since it can compress input data to a low-dimensional latent space using the encoder component and then reconstruct the data using the decoder component.
• Once a VAE is trained, one can take the decoder of the VAE as a generator.
• We employ 100,000 EoSs that are generated using the nonparametric representation method based on \citet{2021ApJ...919...11H} as the training set and try different settings of the neural network, then we get an EoS generator (trained VAE's decoder) with four parameters.