Neutron Star Equation Of State Research Articles

Bayesian Survey of the Dense Matter Equation of State Built upon Skyrme Effective Interactions

The nonrelativistic model of nuclear matter (NM) with zero-range Skyrme interactions is employed within a Bayesian approach in order to study the behavior of the neutron star (NS) equation of state (EOS). A minimal number of constraints from nuclear physics and ab initio calculations of pure neutron matter (PNM) are imposed together with causality and a lower limit on the maximum mass of an NS to all our models. Our key result is that accounting for correlations among the values that the energy per neutron in PNM takes at various densities and that are typically disregarded efficiently constrains the behavior of the EOS at high densities. A series of global NS properties, e.g., maximum mass, central density of the maximum mass configuration, minimum NS mass that allows for direct URCA, and radii of intermediate and massive NSs, appear to be correlated with the value of effective neutron mass in PNM at 0.16 fm−3. Together with similar studies in the literature our work contributes to a better understanding of the NS EOS as well as its link with the properties of dense NM.

Inference of neutron-star properties with unified crust-core equations of state for parameter estimation

Relating different global neutron-star (NS) properties, such as tidal deformability and radius, or mass and radius, requires an equation of state (EoS). Determining the NS EoS is therefore not only the science goal of a variety of observational projects, but it also enters in the analysis process; for example, to predict a NS radius from a measured tidal deformability via gravitational waves (GW) during the inspiral of a binary NS merger. To this aim, it is important to estimate the theoretical uncertainties on the EoS, one of which is the possible bias coming from an inconsistent treatment of the low-density region; that is, the use of a so called non-unified NS crust. We propose a numerical tool allowing the user to consistently match a nuclear-physics informed crust to an arbitrary high-density EoS describing the core of the star. We introduce an inversion procedure of the EoS close to saturation density that allows users to extract nuclear-matter parameters and extend the EoS to lower densities in a consistent way. For the treatment of inhomogeneous matter in the crust, a standard approach based on the compressible liquid-drop (CLD) model approach was used in our work. A Bayesian analysis using a parametric agnostic EoS representation in the high-density region is also presented in order to quantify the uncertainties induced by an inconsistent treatment of the crust. We show that the use of a fixed, realistic-but-inconsistent model for the crust causes small but avoidable errors in the estimation of global NS properties and leads to an underestimation of the uncertainties in the inference of NS properties. Our results highlight the importance of employing a consistent EoS in inference schemes. The numerical tool that we developed to reconstruct such a thermodynamically consistent EoS, CUTER, has been tested and validated for use by the astrophysical community.

Insights into Neutron Star Equation of State by Machine Learning

Due to its powerful capability and high efficiency in big data analysis, machine learning has been applied in various fields. We construct a neural network platform to constrain the behaviors of the equation of state of nuclear matter with respect to the properties of nuclear matter at saturation density and the properties of neutron stars. It is found that the neural network is able to give reasonable predictions of parameter space and provide new hints into the constraints of hadron interactions. As a specific example, we take the relativistic mean field approximation in a widely accepted Walecka-type model to illustrate the feasibility and efficiency of the platform. The results show that the neural network can indeed estimate the parameters of the model at a certain precision such that both the properties of nuclear matter around saturation density and global properties of neutron stars can be saturated. The optimization of the present modularly designed neural network and extension to other effective models is straightforward.

Bayesian investigation of the neutron star equation of state vs gravity degeneracy

Bayesian investigation of the neutron star equation of state vs gravity degeneracy

Deducing neutron star equation of state from telescope spectra with machine-learning-derived likelihoods

The interiors of neutron stars reach densities and temperatures beyond the limits of terrestrial experiments, providing vital laboratories for probing nuclear physics. While the star's interior is not directly observable, its pressure and density determine the star's macroscopic structure which affects the spectra observed in telescopes. The relationship between the observations and the internal state is complex and partially intractable, presenting difficulties for inference. Previous work has focused on the regression from stellar spectra of parameters describing the internal state. We demonstrate a calculation of the full likelihood of the internal state parameters given observations, accomplished by replacing intractable elements with machine learning models trained on samples of simulated stars. Our machine-learning-derived likelihood allows us to perform maximum a posteriori estimation of the parameters of interest, as well as full scans. We demonstrate the technique by inferring stellar mass and radius from an individual stellar spectrum, as well as equation of state parameters from a set of spectra. Our results are more precise than pure regression models, reducing the width of the parameter residuals by 11.8% in the most realistic scenario. The neural networks will be released as a tool for fast simulation of neutron star properties and observed spectra.

Constraining Nuclear Parameters Using Gravitational Waves from f-mode Oscillations in Neutron Stars

Gravitational waves (GWs) emanating from unstable quasi-normal modes in neutron stars (NSs) could be accessible with the improved sensitivity of the current GW detectors or with the next-generation GW detectors and, therefore, can be employed to study the NS interior. Assuming f-mode excitation in isolated pulsars with typical energy of pulsar glitches and considering potential f-mode GW candidates for A+ (upgraded LIGO detectors operating at fifth observing run design sensitivity) and Einstein Telescope (ET), we demonstrate the inverse problem of NS asteroseismology within a Bayesian formalism to constrain the nuclear parameters and NS equation of state (EOS). We describe the NS interior within relativistic mean-field formalism. Taking the example of glitching pulsars, we find that for a single event in A+ and ET, among the nuclear parameters, the nucleon effective mass (m*) within 90% credible interval can be restricted within 10% and 5%, respectively. At the same time, the incompressibility (K) and the slope of the symmetry energy (L) are only loosely constrained. Considering multiple (10) events in A+ and ET, all the nuclear parameters are well constrained, especially m*, which can be constrained to 3% and 2% in A+ and ET, respectively. Uncertainty in the observables of a 1.4 M ⊙ NS such as radius (), f-mode frequency (), damping time (), and a few EOS properties including squared speed of sound (c s 2) are also estimated.

Phase transition phenomenology with nonparametric representations of the neutron star equation of state

Phase transition phenomenology with nonparametric representations of the neutron star equation of state

Tidal deformability doppelgänger: Implications of a low-density phase transition in the neutron star equation of state

Tidal deformability doppelgänger: Implications of a low-density phase transition in the neutron star equation of state

A Quantum-mechanical Treatment of Electron Broadening in Strong Magnetic Fields

Spectral line-shape fitting is an extremely useful tool in determining the gravity of white dwarf stars. This method is so far limited to nonmagnetic white dwarfs largely because the theory of line broadening in high magnetic fields is not as complete as in the nonmagnetic case. Current Stark+Zeeman models treat plasma particles classically and ignore the motion of the nucleus. We develop the formalism for a quantum-mechanical treatment of the perturbing electrons and include the nuclear motion as part of the broadening and explore their relative importance. The conditions we explore are those found in white dwarf and neutron star atmospheres. We find that, contrary to previous studies, the quantized perturbing electrons create more broadening than perturbers on a straight-path trajectory. Additionally, the quantization of the plasma electrons gives rise to resonances away from the line center. The nuclear motion creates an additional electric field, which also leads to an increase in line broadening; however, this effect in neutron star atmospheres is not as large as previously estimated. This suggests that neutron star spectral lines are sensitive to density and that their mass and radius can be obtained from spectral line fitting, which would help constrain the neutron star equation of state.

I-Love-Q relations for a generic family of neutron star equations of state

ABSTRACT Neutron stars (and quark stars) have recently been found to follow certain universality, the I-Love-Q relations. These relations can provide a greater understanding of the structural and macro properties of compact astrophysical objects with knowledge of any one of the observable. The reason behind this is the lack of sensitivity to the relations with the equation of state (EoS) of matter. In this work, we have investigated the consistency of universal relations for a generic family of equations of state. These equations of state are consistent with the prescribed limits of nuclear theory (low densities) and perturbative QCD (asymptotically high densities) and respecting recent astronomical observations. At intermediate densities, the equations of states are parametrized by the adiabatic speed of sound. Although the spread in the EoS is significant, the universal nature of the I-Love-Q trio holds relatively well up to a specific tolerance limit of 5 per cent fractional percentage error. We have compared the result first with a similar set, but not respecting the recent astrophysical constraints. A deviation from universality is seen and the tolerance exceeds the 5 per cent limit. Next, we have compared our result with a family of EoS having monotonic sound speed inside a neutron star. A slight deviation from universality is seen for this case; however, the tolerance remains within the 5 per cent limit. This shows the existence of a correlation between universal relations and observational constraints.

Simulating neutron stars with a flexible enthalpy-based equation of state parametrization in spectre

Numerical simulations of neutron star mergers represent an essential step toward interpreting the full complexity of multimessenger observations and constraining the properties of supranuclear matter. Currently, simulations are limited by an array of factors, including computational performance and input physics uncertainties, such as the neutron star equation of state. In this work, we expand the range of nuclear phenomenology efficiently available to simulations by introducing a new analytic parametrization of cold, beta-equilibrated matter that is based on the relativistic enthalpy. We show that the new enthalpy parametrization can capture a range of nuclear behavior, including strong phase transitions. We implement the enthalpy parametrization in the spectre code, simulate isolated neutron stars, and compare performance to the commonly used spectral and polytropic parametrizations. We find comparable computational performance for nuclear models that are well represented by either parametrization, such as simple hadronic equations of state. We show that the enthalpy parametrization further allows us to simulate more complicated hadronic models or models with phase transitions that are inaccessible to current parametrizations.

General-relativistic neutrino-radiation magnetohydrodynamics simulation of seconds-long black hole-neutron star mergers: Dependence on the initial magnetic field strength, configuration, and neutron-star equation of state

As a follow-up study of our previous work [Phys. Rev. D 106, 023008 (2022)], numerical-relativity simulations for seconds-long black hole-neutron star mergers are performed for a variety of setups. Irrespective of the initial and symmetry conditions, we find qualitatively universal evolution processes: The dynamical mass ejection takes place together with a massive accretion disk formation after the neutron star is tidally disrupted; subsequently, the magnetic field in the accretion disk is amplified by the magnetic winding, Kelvin-Helmholtz instability, and magnetorotational instability, which establish a turbulent state inducing the dynamo and angular momentum transport; the postmerger mass ejection by the effective viscous processes stemming from the magnetohydrodynamics turbulence sets in at $\ensuremath{\sim}300--500\text{ }\text{ }\mathrm{ms}$ after the merger and continues for several hundred ms; a magnetosphere near the black-hole spin axis is developed and the collimated strong Poynting flux is generated with its lifetime of $\ensuremath{\sim}0.5--2\text{ }\text{ }\mathrm{s}$. We have newly found that the model of no equatorial-plane symmetry shows the reverse of the magnetic-field polarity in the magnetosphere, which is caused by the dynamo associated with the magnetorotational instability in the accretion disk. The model with initially toroidal fields shows the tilt of the disk and magnetosphere in the late postmerger stage because of the anisotropic postmerger mass ejection. These effects could terminate the strong Poynting-luminosity stage within the timescale of $\ensuremath{\sim}0.5--2\text{ }\text{ }\mathrm{s}$.

Perturbative QCD and the neutron star equation of state

Perturbative QCD and the neutron star equation of state

Degeneracy in the Inference of Phase Transitions in the Neutron Star Equation of State from Gravitational Wave Data.

Gravitational wave (GW) detections of binary neutron star inspirals will be crucial for constraining the dense matter equation of state (EOS). We demonstrate a new degeneracy in the mapping from tidal deformability data to the EOS, which occurs for models with strong phase transitions. We find that there exists a new family of EOS with phase transitions that set in at different densities and that predict neutron star radii that differ by up to ∼500 m but that produce nearly identical tidal deformabilities for all neutron star masses. Next-generation GW detectors and advances in nuclear theory may be needed to resolve this degeneracy.

Reconstructing the neutron star equation of state from observational data via automatic differentiation

Neutron star observables like masses, radii, and tidal deformability are direct probes to the dense matter equation of state (EoS). A novel deep learning method that optimizes an EoS in the automatic differentiation framework of solving inverse problems is presented. The trained neural network EoS yields narrow bands for the relationship between the pressure and speed of sound as a function of the mass density. The results are consistent with those obtained from conventional approaches and the observational bound on the tidal deformability inferred from the gravitational wave event, GW170817.

The luminosity functions of kilonovae from binary neutron star mergers under different equation of states

ABSTRACTKilonovae produced by mergers of binary neutron stars (BNSs) are important transient events to be detected by time domain surveys with the alerts from the ground-based gravitational wave detectors. The observational properties of these kilonovae depend on the physical processes involved in the merging processes and the equation of state (EOS) of neutron stars (NSs). In this paper, we investigate the dependence of kilonova luminosities on the parameters of BNS mergers, and estimate the distribution functions of kilonova peak luminosities (KLFs) at the u, g, r, i, y, and z bands as well as its dependence on the NS EOS, by adopting a comprehensive semi-analytical model for kilonovae (calibrated by the observations of GW170817), a population synthesis model for the cosmic BNSs, and the ejecta properties of BNS mergers predicted by numerical simulations. We find that the kilonova light curves depend on both the BNS properties and the NS EOS, and the KLFs at the considered bands are bimodal with the bright components mostly contributed by BNS mergers with total mass $\lesssim 3.2\, \mathrm{M}_\odot$/$2.8\, \mathrm{M}_\odot$ and fainter components mostly contributed by BNS mergers with total mass $\gtrsim 3.2\, \mathrm{M}_\odot$/$2.8\, \mathrm{M}_\odot$ by assuming a stiff/soft (DD2/SLy) EOS. The emission of the kilonovae in the KLF bright components is mostly due to the radiation from the wind ejecta by the remnant discs of BNS mergers, while the emission of the kilonovae in the KLF faint components is mostly due to the radiation from the dynamical ejecta by the BNS mergers.

Constraining free parameters of a color superconducting nonlocal Nambu–Jona-Lasinio model using Bayesian analysis of neutron stars mass and radius measurements

We provide a systematic study of hybrid neutron star equations of state (EOS) consisting of a relativistic density functional for the hadronic phase and a covariant nonlocal Nambu--Jona-Lasinio (nlNJL) model to describe the color superconducting quark matter phase. Changing the values of the two free parameters, the dimensionless vector and diquark coupling strengths ${\ensuremath{\eta}}_{V}$ and ${\ensuremath{\eta}}_{D}$ results in a set of EOS with varying stiffness and deconfinement onset. The favorable parameters are obtained from a systematic Bayesian analysis for which the multimessenger constraint on the neutron star radius at $14{M}_{\ensuremath{\bigodot}}$ and the combined mass-radius constraint for PSR $\mathrm{J}0740+6620$ from NICER experiment are used as the constraints. Additionally, the transition from hadronic matter to deconfined quark matter is constrained to occur above nuclear saturation density. Hybrid stars modeled with these favorable parameters are compatible with the NICER results for the radius of the highest known mass neutron star, PSR $\mathrm{J}0740+6620$. Three new observations interesting for neutron star phenomenology are reported: (i) we show that the constant sound speed (CSS) EOS provides an excellent fit to that of the nlNJL model which implies the squared speed of sound at high densities to be about 0.5 for the optimized parameters; (ii) we give a simple functional form for the mapping between the parameter spaces of these two models valid for the whole range of relevant chemical potentials and (iii) we observe that the special point property of hybrid EOS based on CSS quark matter generalizes to a set of lines consisting of special points when two EOS parameters are varied instead of one. A lower limit for the maximum mass of hybrid stars as a function of the vector coupling strength is obtained.

Rapid hierarchical inference of neutron star equation of state from multiple gravitational wave observations of binary neutron star coalescences

Bayesian hierarchical inference of phenomenological parametrized neutron star equations of state (EoS) from multiple gravitational wave observations of binary neutron star mergers is of fundamental importance in improving our understanding of neutron star structure, the general properties of matter at supra nuclear densities, and the strong nuclear force. However, such an analysis is computationally costly, as it is unable to reuse single-event EoS agnostic parameter estimation runs that are carried out regardless for generating gravitational wave transient catalogs. With the number of events expected to be observable during the fourth observing run (O4) of LIGO/Virgo/KAGRA, this problem can only be expected to worsen. We develop a novel and robust algorithm for rapid and computationally cheap hierarchical inference of parametrized EoS from gravitational wave data which reuses single-event EoS agnostic parameter estimation samples to significantly reduce computational cost. We efficiently include a priori knowledge of neutron star physics as Bayesian priors on the EoS parameters. The high speed and low computational cost of our method allow for efficient recomputation of EoS inference every time a new binary neutron star event is discovered or whenever new observations and theoretical discoveries change the prior on EoS parameters. We test our method on both real and simulated gravitational wave data to demonstrate its accuracy. We show that our computationally cheap method produces EoS constraints that are completely consistent with existing analysis for real data, the chosen fiducial EoS for simulated data. Armed with our fast analysis scheme, we also study the variability of EoS constraints with binary neutron star properties for sets of simulated events drawn in different signal-to-noise ratio and mass ranges.

Hierarchical Bayesian method for constraining the neutron star equation of state with an ensemble of binary neutron star postmerger remnants

Binary neutron star (BNS) post-merger gravitational-wave emission can occur in the aftermath of a BNS merger -- provided the system avoids prompt collapse to a black hole -- as a quasistable hypermassive remnant experiences quadrupolar oscillations and non-axisymmetric deformations. The post-merger gravitational-wave spectrum possesses a characteristic peak frequency that has been shown to be dependent on the binary chirp mass and the neutron star equation of state (EoS), rendering post-merger gravitational waves a powerful tool for constraining neutron star composition. Unfortunately, the BNS post-merger signal is emitted at high ($\gtrsim 1.5$ kHz) frequencies, where ground-based gravitational wave detectors suffer from reduced sensitivity. It is therefore unlikely that post-merger signals will be detected with sufficient signal-to-noise ratio (SNR) until the advent of next-generation detectors. However, by employing empirical relations derived from numerical relativity simulations, we can combine information across an ensemble of BNS mergers, allowing us to obtain EoS constraints with many low-SNR signals. We present a hierarchical Bayesian method for deriving constraints on $R_{1.6}$, the radius of a 1.6$\mathrm{M_{\odot}}$ neutron star, through an ensemble analysis of binary neutron star mergers. We apply this method to simulations of the next two LIGO-Virgo-KAGRA observing runs, O4 and O5, as well as an extended 4-year run at A+ sensitivity, demonstrating the potential of our approach to yield EoS information from the post-merger signal with current-generation detectors. The A+ 4-year scenario is predicted to improve the constraint on $R_{1.6}$ from the currently available multimessenger-based 95\% credible interval (C.I.) uncertainty of $R_{1.6}=12.07^{+0.98}_{-0.77}$ km to $R_{1.6}=11.91^{+0.80}_{-0.56}$ km, a 22% reduction of the 95% C.I. width.

Impact of nuclear reactions on gravitational waves from neutron star mergers

Nuclear reactions may affect gravitational-wave signals from neutron-star mergers, but the impact is uncertain. To indicate the significance of this effect, we compare two numerical simulations representing intuitive extremes. In one case, reactions happen instantaneously. In the other case, they occur on timescales much slower than the evolutionary timescale. We show that, while the differences in the two gravitational-wave signals are small, the mismatch between them satisfies the condition for distinguishability using the Einstein Telescope noise curve, assuming that the neutron-star equation of state can be well constrained by experiments or by the postmerger signal of the event. This suggests that, to avoid systematic errors in equation of state parameters inferred from observed signals, we need to accurately implement nuclear reactions in future simulations.