23–26 Sept 2025
Yerevan, Armenia
Etc/GMT+4 timezone

Inferring the Equation of State from Neutron Star Observables via Machine Learning

Not scheduled
20m
Yerevan, Armenia

Yerevan, Armenia

Department of Physics, Alex Manukyan str. 1, Yerevan, Armenia

Speaker

NARESH KUMAR PATRA (The Chinese University of Hong Kong, Shenzhen, China)

Description

We have conducted an extensive study using a diverse set of equations of state (EoSs) to uncover strong relationships between neutron star (NS) observables and the underlying EoS parameters using symbolic regression method. These EoS models, derived from a mix of agnostic and physics-based approaches, considered neutron stars composed of nucleons, hyperons, and other exotic degrees of freedom in beta equilibrium. The maximum mass of a NS is found to be strongly correlated with the pressure and baryon density at an energy density of approximately 800 MeV.fm$^{-3}$. We have also demonstrated that the EoS can be expressed as a function of radius and tidal deformability within the NS mass range 1-2$M_\odot$. These insights offer a promising and efficient framework to decode the dense matter EoS directly from the accurate knowledge of NS observables.

Author

NARESH KUMAR PATRA (The Chinese University of Hong Kong, Shenzhen, China)

Co-authors

Bijay Agrawal Constança Providência Helena Pais (University of Coimbra) Prof. Kai Zhou (Chinese University of Hong Kong - Shenzhen (CUHK-Shenzhen)) TUHIN MALIK

Presentation materials

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