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

Abstract

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.

16 pages, 11 figures, accepted for publication in Astronomy and Astrophysics

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• The Science of the Einstein Telescope
• Bayesian Inference of Fine-Features of Nuclear Equation of State from Future Neutron Star Radius Measurements to 0.1km Accuracy
• Constraining the equation of state in neutron-star cores via the long-ringdown signal
• Frozen and $\beta$-equilibrated $f$ and $p$ modes of cold neutron stars: nuclear metamodel predictions
• Decoding Long-duration Gravitational Waves from Binary Neutron Stars with Machine Learning: Parameter Estimation and Equations of State
• Crust (Unified) Tool for Equation-of-state Reconstruction (CUTER) v2
• Bayesian inference of neutron star crust properties using an ab initio-benchmarked meta-model
• New Skyrme parametrizations to describe finite nuclei and neutron star matter with realistic effective masses
• Investigating the role of nuclear parameters in Neutron Star oscillations: a model comparison
• Bayesian Inference of Hybrid Star Properties from Future High-Precision Measurements of Their Radii
• Strongly interacting matter in extreme magnetic fields
• Imprints of high-density nuclear symmetry energy on the crustal fraction of neutron star moment of inertia
• New solution to the hyperon puzzle of neutron stars: Quantum many-body effects
• Limitations in constraining neutron star radii and nuclear properties from inspiral gravitational wave detections
• Tracing the Trace Anomaly of Dense Matter inside Neutron Stars