Spanning the full range of neutron star properties within a microscopic description

Abstract

The high-density behavior of nuclear matter is analyzed within a relativistic mean-field description with non-linear meson interactions. To assess the model parameters and their output, a Bayesian inference technique is used. The Bayesian setup is limited only by a few nuclear saturation properties, the neutron star maximum mass larger than 2 M${}_{\odot }$, and the low-density pure neutron matter equation of state (EOS) produced by an accurate N${}^3$LO calculation in chiral effective field theory. Depending on the strength of the non-linear scalar vector field contribution, we have found three distinct classes of EOSs, each one correlated to different star properties distributions. If the non-linear vector field contribution is absent, the gravitational maximum mass and the sound velocity at high densities are the greatest. However, it also gives the smallest speed of sound at densities below three times saturation density. On the other hand, models with the strongest non-linear vector field contribution predict the largest radii and tidal deformabilities for 1.4 M${}_{\odot }$ stars, together with the smallest mass for the onset of the nucleonic direct Urca processes and the smallest central baryonic densities for the maximum mass configuration. These models have the largest speed of sound below three times saturation density, but the smallest at high densities, in particular, above four times saturation density the speed of sound decreases approaching approximately $\sqrt{0.4}c$ at the center of the maximum mass star. On the contrary, a weak non-linear vector contribution gives a monotonically increasing speed of sound. A 2.75 M${}_{\odot }$ NS maximum mass was obtained in the tail of the posterior with a weak non-linear vector field interaction. We found that pQCD favors models with a large non-linear vector field contribution or hyperons.

There are 17 pages, 16 figures (The typographical error in the supplemental update)

References in corpus (31)

• Multi-messenger Observations of a Binary Neutron Star Merger
• Gravitational Waves and Gamma-rays from a Binary Neutron Star Merger: GW170817 and GRB 170817A
• GW190814: Gravitational Waves from the Coalescence of a 23 M${}_{\odot }$ Black Hole with a 2.6 M${}_{\odot }$ Compact Object
• PSR J0030+0451 Mass and Radius from NICER Data and Implications for the Properties of Neutron Star Matter
• A NICER View of PSR J0030+0451: Millisecond Pulsar Parameter Estimation
• A NICER View of the Massive Pulsar PSR J0740+6620 Informed by Radio Timing and XMM-Newton Spectroscopy
• Refined Mass and Geometric Measurements of the High-Mass PSR J0740+6620
• Neutron-Rich Nuclei in Heaven and Earth
• Cold Quark Matter
• Relativistic Mean-Field Hadronic Models under Nuclear Matter Constraints
• Hyperon Puzzle: Hints from Quantum Monte Carlo Calculations
• Building relativistic mean field models for finite nuclei and neutron stars
• Neutron Stars and the Nuclear Equation of State
• On the Sound Speed in Neutron Stars
• Density dependence of the nuclear symmetry energy: a microscopic perspective
• GW190814: Impact of a 2.6 solar mass neutron star on nucleonic equations of state
• How perturbative QCD constrains the Equation of State at Neutron-Star densities
• Multimessenger constraints for ultra-dense matter
• Non-rotating and rotating neutron stars in the extended field theoretical model
• The Equation of State for the Nucleonic and Hyperonic Core of Neutron Stars
• Asymmetric nuclear matter and neutron-skin in extended relativistic mean field model
• A Detailed Examination of Astrophysical Constraints on the Symmetry Energy and the Neutron Skin of ${}^{208}$Pb with Minimal Modeling Assumptions
• The Vlasov formalism for extended relativistic mean field models: the crust-core transition and the stellar matter equation of state
• Relativistic description of dense matter equation of state and compatibility with neutron star observables: a Bayesian approach
• Relativistic hypernuclear compact stars with calibrated equations of state
• Role of vector self-interaction in Neutron Star properties
• Bayesian inference of signatures of hyperons inside neutron stars
• Bayesian reconstruction of nuclear matter parameters from the equation of state of neutron star matter
• The Radius of PSR J0740+6620 from NICER and XMM-Newton Data
• Nearly model-independent constraints on dense matter equation of state in a Bayesian approach
• Inferring the nuclear symmetry energy at supra saturation density from neutrino cooling

Cited by in corpus (29)

• Strongly interacting matter exhibits deconfined behavior in massive neutron stars
• The Science of the Einstein Telescope
• Dense Matter in Neutron Stars with eXTP
• Constraining a relativistic mean field model using neutron star mass-radius measurements II: Hyperonic models
• Implications of comprehensive nuclear and astrophysics data on the equations of state of neutron star matter
• Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks
• Astrophysics and Nuclear Physics Informed Interactions in Dense Matter: Inclusion of PSR J0437-4715
• Unified neutron star equations of state calibrated to nuclear properties
• Non-strange quark stars within resummed QCD
• Towards Uncovering Dark Matter Effects on Neutron Star Properties: A Machine Learning Approach
• Feasibility of dark matter admixed neutron star based on recent observational constraints
• Bayesian inference of the dense matter equation of state built upon extended Skyrme interactions
• New covariant density functionals of nuclear matter for compact star simulations
• A Bayesian study of quark models in view of recent astrophysical constraints
• From NS observations to nuclear matter properties: a machine learning approach
• Bayesian constraints on covariant density functional equations of state of compact stars with new NICER mass-radius measurements
• Nambu-Jona-Lasinio description of hadronic matter from a Bayesian approach
• Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state
• Bayesian inferences on covariant density functionals from multimessenger astrophysical data: Nucleonic models
• Testing the Paradigm of Nuclear Many-Body Theory
• Inferring the Equation of State from Neutron Star Observables via Machine Learning
• Detecting Hyperons in neutron stars -- a machine learning approach
• Conditional variational autoencoder inference of neutron star equation of state from astrophysical observations
• Comparing strange and non-strange quark stars within resummed QCD at NLO
• Effect of Dark matter and $\sigma$-cut potential on radial and non-radial oscillation modes in neutron stars
• Unveiling a universal relationship between the f(R) parameter and neutron star properties
• Detecting the third family of compact stars with normalizing flows
• Bayesian inferences on covariant density functionals from multimessenger astrophysical data: Influences of parametrizations of density dependent couplings
• Learning about neutron star composition from the slope of the mass-radius diagram