scholarly journals The equation of state of dense matter and the effect of Λ hyperons to neutron star structure

2019 ◽  
Author(s):  
Stefano Gandolfi ◽  
Diego Lonardoni
Keyword(s):  
Neutron Star ◽  
Equation Of State ◽  
Dense Matter ◽  
Star Structure

scholarly journals Bounds on the speed of sound in dense matter, and neutron star structure

2017 ◽  
Vol 95 (4) ◽  
Author(s):  
Ch. C. Moustakidis ◽  
T. Gaitanos ◽  
Ch. Margaritis ◽  
G. A. Lalazissis
Keyword(s):  
Neutron Star ◽  
Speed Of Sound ◽  
Dense Matter ◽  
Star Structure

scholarly journals COMPUTATION OF NEUTRON STAR STRUCTURE USING MODERN EQUATION OF STATE

2006 ◽  
Vol 21 (07) ◽  
pp. 1555-1565 ◽  
Author(s):  
G. H. BORDBAR ◽  
M. HAYATI
Keyword(s):  
Neutron Star ◽  
Equation Of State ◽  
Equations Of State ◽  
Maximum Mass ◽  
Neutron Star Matter ◽  
Radio Pulsars ◽  
Good Consistency ◽  
The Given ◽  
Neutron Star Radius ◽  
Star Structure

Using the modern equations of state derived from microscopic calculations, we have calculated the neutron star structure. For the neutron star, we have obtained a minimum mass about 0.1 M⊙ which is nearly independent of the equation of state, and a maximum mass between 1.47 M⊙ and 1.98 M⊙ which is strongly dependent on the equation of state. It is shown that among the equations of state of neutron star matter which we have used, the stiffest one leads to higher maximum mass and radius and lower central density. It is seen that the given maximum mass for the Reid-93 equation of state shows a good consistency with the accurate observations of radio pulsars. We have indicated that the thickness of neutron star crust is very small compared to the predicted neutron star radius.

scholarly journals The equation of state of neutron matter, symmetry energy and neutron star structure

2014 ◽  
Vol 50 (2) ◽  
Author(s):  
S. Gandolfi ◽  
J. Carlson ◽  
S. Reddy ◽  
A. W. Steiner ◽  
R. B. Wiringa
Keyword(s):  
Neutron Star ◽  
Equation Of State ◽  
Symmetry Energy ◽  
Neutron Matter ◽  
Star Structure

scholarly journals Thermal properties of hot and dense matter: Influence of rapid rotation on protoneutron stars, hot neutron stars, and neutron star merger remnants

2021 ◽  
Vol 252 ◽  
pp. 05004
Author(s):  
Polychronis Koliogiannis ◽  
Charalampos Moustakidis
Keyword(s):  
Neutron Star ◽  
Equation Of State ◽  
Neutron Stars ◽  
Nuclear Matter ◽  
Equations Of State ◽  
Interaction Model ◽  
Dense Matter ◽  
Baryon Density ◽  
Dense Nuclear Matter ◽  
Protoneutron Stars

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.

scholarly journals Neural network reconstruction of the dense matter equation of state derived from the parameters of neutron stars

2020 ◽  
Vol 642 ◽  
pp. A78 ◽  
Author(s):  
F. Morawski ◽  
M. Bejger
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Neural Networks ◽  
Neutron Star ◽  
Equation Of State ◽  
Neutron Stars ◽  
Equations Of State ◽  
Dense Matter ◽  
Data Set ◽  
Global Parameters

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.

scholarly journals Hyperons in hot dense matter: what do the constraints tell us for equation of state?

2018 ◽  
Vol 35 ◽  
Author(s):  
M. Fortin ◽  
M. Oertel ◽  
C. Providência
Keyword(s):  
Neutron Star ◽  
Equation Of State ◽  
Symmetry Energy ◽  
Nuclear Physics ◽  
Equations Of State ◽  
Dense Matter ◽  
Baryon Octet ◽  
Thermodynamic Quantities ◽  
Binary Neutron Star ◽  
Hot Matter

AbstractFor core-collapse and neutron star merger simulations, it is important to have adequate equations of state which describe dense and hot matter as realistically as possible. We present two newly constructed equations of state including the entire baryon octet, compatible with the main constraints coming from nuclear physics, both experimental and theoretical. One of the equations of state describes cold β-equilibrated neutron stars with a maximum mass of 2 Msun. Results obtained with the new equations of state are compared with the ones of DD2Y, the only existing equation of state containing the baryon octet and satisfying the above constraints. The main difference between our new equations of state and DD2Y is the harder symmetry energy of the latter. We show that the density dependence of the symmetry energy has a direct influence on the amount of strangeness inside hot and dense matter and, consequently, on thermodynamic quantities. We expect that these differences affect the evolution of a proto-neutron star or binary neutron star mergers. We propose also several parameterisations based on the DD2 and SFHo models calibrated to Lambda hypernuclei that satisfy the different constraints.

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