scholarly journals Equation of state of dense matter and the minimum mass of cold neutron stars

2002 ◽  
Vol 385 (1) ◽  
pp. 301-307 ◽  
Author(s):  
P. Haensel ◽  
J. L. Zdunik ◽  
F. Douchin
2016 ◽  
Vol 591 ◽  
pp. A25 ◽  
Author(s):  
J. Nättilä ◽  
A. W. Steiner ◽  
J. J. E. Kajava ◽  
V. F. Suleimanov ◽  
J. Poutanen

2021 ◽  
Vol 252 ◽  
pp. 05004
Author(s):  
Polychronis Koliogiannis ◽  
Charalampos Moustakidis

The knowledge of the equation of state is a key ingredient for many dynamical phenomena that depend sensitively on the hot and dense nuclear matter, such as the formation of protoneutron stars and hot neutron stars. In order to accurately describe them, we construct equations of state at FInite temperature and entropy per baryon for matter with varying proton fractions. This procedure is based on the momentum dependent interaction model and state-of-the-art microscopic data. In addition, we investigate the role of thermal and rotation effects on microscopic and macroscopic properties of neutron stars, including the mass and radius, the frequency, the Kerr parameter, the central baryon density, etc. The latter is also connected to the hot and rapidly rotating remnant after neutron star merger. The interplay between these quantities and data from late observations of neutron stars, both isolated and in matter of merging, could provide useful insight and robust constraints on the equation of state of nuclear matter.


2020 ◽  
Author(s):  
◽  
Germán Malfatti

This thesis work focuses on studying the possible existence of phase transitions in the immediate compact remnants of core collapse supernova, neutron stars, and the theoretical models that describe the interior of dense matter. Specifically, we are interested in analyzing the feasibility of a transition from hadronic matter to quark matter in the cores of these objects. The density of matter inside neutron stars is several times that of atomic nuclei, and the equation of state that describes such matter in such a regime is still unknown. In this context, it is known that the interaction between the constituents of nucleons, the quarks, weakens with increasing density due to the intrinsic property of the QCD known as it asymptotic freedom. Therefore, matter should either dissolve into a quark-free state at high densities, or else form a superconduct- ing state of color. This superconducting phase of color would be energetically favorable, if it were present in a cold neutron star, since a system of fermions that interact weakly at low temperature is unstable with respect to the formation of Cooper pairs. Although it is impossible to know both theoretically and experimentally whether these phases exist in neutron stars, the interpolation of the resolvable part of QCD at high densities, together with the hadronic equations of state at low densities, suggest that they could appear in the interior of compact objects. For the phase transition we will use two different formalisms: the Maxwell formalism, in which an abrupt phase transition between hadronic and quark matter without mixed phase formation is assumed, and the Gibbs formalism, in which a mixed phase in which hadrons and quarks coexist. For the description of hadronic matter, we will use different parametrizations of the relativistic mean field model with density-dependent coupling constants. For the description of quark matter we will use an effective nonlocal Nambu Jona-Lasinio model of three flavors with vector interactions, in which we will include the possibility of formation of diquarks to model a superconducting phase of color in SU (3), which we will call 2SC + s. Phase diagrams and equations of state of quark matter at finite temperature are presented, and the influence of that kind of matter on observables associated with neutron stars is investigated. Likewise, using hybrid equations of state, the simplified thermal evolution of compact stars during their formation is studied, from their state of proto-neutron stars to that of cold neutron stars, and the results obtained are compared with recent astrophysical observations. The pa- rameterizations used in this work are adjusted to the most recent measurements of masses and coupling constants of the QCD, which imposes strong restrictions on the existence of quark matter in proto-stars, unlike what happens with less realistic models or with more free parameters. However, the results obtained indicate that even considering these restrictions, the occurrence of quark matter in the nuclei of these stars remains a promis- ing possibility. The remaining free parameters of the models were adjusted taking into account the observational restrictions, coming from precise determinations of the pulsars masses of ∼ 2 M⊙, and the event corresponding to the fusion of two neutron stars, known as GW170817. The fact that the use of more realistic models for the description of the dense matter in these objects indicates the presence of quark matter inside neutron stars, could be an answer to the question of the behavior of that kind of matter and the determination of its corresponding equation of state.


Author(s):  
SLAVOMÍR ČERNÝ ◽  
JIŘINA ŘÍKOVSKÁ STONE ◽  
ZDENĚK STUCHLÍK ◽  
STANISLAV HLEDÍK

2020 ◽  
Vol 642 ◽  
pp. A78 ◽  
Author(s):  
F. Morawski ◽  
M. Bejger

Context. Neutron stars are currently studied with an rising number of electromagnetic and gravitational-wave observations, which will ultimately allow us to constrain the dense matter equation of state and understand the physical processes at work within these compact objects. Neutron star global parameters, such as the mass and radius, can be used to obtain the equation of state by directly inverting the Tolman-Oppenheimer-Volkoff equations. Here, we investigate an alternative approach to this procedure. 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 precisely reconstructing 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 only the gravitational-wave observations of tidal deformability, that is, using quantities that are not related in any straightforward way. Methods. The application of an artificial neural network in the equation-of-state reconstruction exploits the non-linear potential of this machine learning model. Since each neuron in the network is basically a non-linear function, it is possible to create a complex mapping between the input sets of observations and the output equation-of-state table. Within the supervised training paradigm, we construct a few hidden-layer deep neural networks on a generated data set, consisting of a realistic equation of state for the neutron star crust connected with a piecewise relativistic polytropes dense core, with its parameters representative of state-of-the art realistic equations of state. Results. We demonstrate the performance of our machine-learning implementation with respect to the simulated cases with a varying number of observations and measurement uncertainties. Furthermore, we study the impact of the neutron star mass distributions on the results. Finally, we test the reconstruction of the equation of state trained on parametric polytropic training set using the simulated mass–radius and mass–tidal-deformability sequences based on realistic equations of state. Neural networks trained with a limited data set are capable of generalising the mapping between global parameters and equation-of-state input tables for realistic models.


Sign in / Sign up

Export Citation Format

Share Document