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Towards mitigation of apparent tension between nuclear physics and astrophysical observations by improved modeling of neutron star matter
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abstract
Observations of neutron stars (NSs) by the LIGO-Virgo and NICER collaborations have provided reasonably precise measurements of their various macroscopic properties. In this paper, we employ a Bayesian framework to combine them and place improved joint constraints on the properties of NS equation of state (EoS). We use a hybrid EoS formulation that employs a parabolic expansion-based nuclear empirical parameterization around the nuclear saturation density augmented by a generic 3-segment piecewise polytrope model at higher densities. Within the $90 \%$ credible level this parameterization predicts $R_{1.4} = 12.57_{-0.92}^{+0.73}$ km and $\Lambda_{1.4} = 550_{-225}^{+223}$ for the radius and dimensionless tidal deformability, respectively, of a $1.4 M_{\odot}$ NS. Finally, we show how the construction of the full NS EoS based solely on the nuclear empirical parameters at saturation density leads to certain tension with the astrophysical data, and how the hybrid approach provides a resolution to it.
Forward citations
Cited by 2 Pith papers
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Systematics from NICER Pulse Profiles Drive Uncertainty in Multi-Messenger Inference of the Neutron Star Equation of State
A joint Bayesian analysis of NICER, gravitational wave, radio, and nuclear data shows that NICER pulse profile modeling choices dominate equation of state uncertainties and prefer the ST+PDT model over the PDT-U model...
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PSR J0952-0607: Probing the Stiffest Equations of State and r-Mode Suppression Mechanisms
Using the 709.2 Hz spin of PSR J0952-0607 in Bayesian equation-of-state inference shifts its inferred non-rotating mass to 2.10+0.25-0.24 Msun and makes r-mode stability depend on crust rigidity.
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