Note: This is simply an explanation of the paper titled “Insights into Neutron Star matter: EoS Models and Observation” by Zuhua ji, Jiarui chen, Gaijian Wu.
This is NOT real paper but only an simple explanation of what it covers.
Please read the original paper for better understanding.
Credit of content goes to the paper and author, however is summarised and explained by IBSAglobal’s contributor.
(STILL NOT COMPLETED, IS BEING UPDATED CONSTANTLY)
This paper covers classification of EoS models into Hadronic matter, hybrid, and quark matter models, and analyzes their assumptions, predictions and constraints.
This review gives a comprehensive understanding of implications of EoS, their method of construction and future direction.
Studying neutron stars provides insights into the behaviour of matter under extreme conditions that can’t be replicated on earth.
EoS models of neutron star id crucial steps to understand many properties like mass-radius relation, maximum mass, and tidal deformality.
Ever since the Tolman-Oppenheimer-Volkoff (TOV) equations by Oppenheimer and Volkoff in 1939, first relativistic EoS based on a free neutron fermi gas, there has been continuous work and growth in modeling dense matter. Then
1. In 1998, Akmal et al. Developed APR model which remains a benchmark for nucleonic EoSs.
2. Followed by this in 2009, Read JS et al. Constructed ALF1-ALF4 hybrid model by combining APR nuclear matter with color flavour locked quark matter, offering structure EoS for Bayesian interference.
3. In 2014, Gandolfi applied auxiliary field diffusion Monte Carlo (AFDMC) methods that provides higher accuracy and emphasizes significance of three body forces and symmetry energy.
4. In 2017, Kalternborn et al. Introducef DD2F-SF family, a first order hadron quark phase transition via the string flip model.
5. In 2020, Ecker et al. Proposed hybrid EoS, based on V-QCD framework.
6. Again in 2020, otto et al. Adopted a functional renormalization group (FRG) approach within quark-meson models.
7. In 2022, kojo et al. Presented QHC21 EoS.
8. In 203, Pang et al. Developed the NMMA framework.
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