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A survey of the parameter space of the compressible liquid drop model as applied to the neutron star inner crust

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arxiv 1110.4043 v2 pith:KPTTV6C2 submitted 2011-10-18 astro-ph.SR nucl-exnucl-th

A survey of the parameter space of the compressible liquid drop model as applied to the neutron star inner crust

classification astro-ph.SR nucl-exnucl-th
keywords crustenergybaselinedensitiesdensitymodelneutronnuclear
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present a systematic survey the range of predictions of the neutron star inner crust composition, crust-core transition densities and pressures, and density range of the nuclear `pasta' phases at the bottom of the crust provided by the compressible liquid drop model in the light of current experimental and theoretical constraints on model parameters. Using a Skyrme-like model for nuclear matter, we construct baseline sequences of crust models by consistently varying the density dependence of the bulk symmetry energy at nuclear saturation density, $L$, under two conditions: (i) that the magnitude of the symmetry energy at saturation density $J$ is held constant, and (ii) $J$ correlates with $L$ under the constraint that the pure neutron matter (PNM) EoS satisfies the results of ab-initio calculations at low densities. Such baseline crust models facilitate consistent exploration of the $L$ dependence of crustal properties. The remaining surface energy and symmetric nuclear matter parameters are systematically varied around the baseline, and different functional forms of the PNM EoS at sub-saturation densities implemented, to estimate theoretical `error bars' for the baseline predictions. Inner crust composition and transition densities are shown to be most sensitive to the surface energy at very low proton fractions and to the behavior of the sub-saturation PNM EoS. Recent calculations of the energies of neutron drops suggest that the low-proton-fraction surface energy might be higher than predicted in Skyrme-like models, which our study suggests may result in a greatly reduced volume of pasta in the crust than conventionally predicted.

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    Bayesian modeling with informed priors reduces uncertainties in neutron-star crust shear properties, predicting torsional mode frequencies of 20-50 Hz compatible with observations.