Constraining properties of high-density matter in neutron stars with magneto-elastic oscillations

Abstract We discuss torsional oscillations of highly magnetized neutron stars (magnetars) using two-dimensional, magneto-elastic-hydrodynamical simulations. Our model is able to explain both the low- and high-frequency quasi-periodic oscillations (QPOs) observed in magnetars. The analysis of these o...

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Veröffentlicht in:Monthly notices of the Royal Astronomical Society 2018-05, Vol.476 (3), p.4199-4212
Hauptverfasser: Gabler, Michael, Cerdá-Durán, Pablo, Stergioulas, Nikolaos, Font, José A, Müller, Ewald
Format: Artikel
Sprache:eng
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Zusammenfassung:Abstract We discuss torsional oscillations of highly magnetized neutron stars (magnetars) using two-dimensional, magneto-elastic-hydrodynamical simulations. Our model is able to explain both the low- and high-frequency quasi-periodic oscillations (QPOs) observed in magnetars. The analysis of these oscillations provides constraints on the breakout magnetic-field strength, on the fundamental QPO frequency, and on the frequency of a particularly excited overtone. By performing a new set of simulations, we are able to derive for the first time empirical relations for a self consistent model including a superfluid core which describe these constraints quantitatively. We use these relations to generically constrain properties of high-density matter in neutron stars, employing Bayesian analysis. In spite of current uncertainties and computational approximations, our model-dependent Bayesian posterior estimates for SGR 1806-20 yield a magnetic-field strength $\bar{B}\sim 2.1^{+1.3}_{-1.0}\times 10^{15}\,$G and a crust thickness of $\Delta r = 1.6^{+0.7}_{-0.6}$ km, which are both in remarkable agreement with observational and theoretical expectations, respectively (1σ error bars are indicated). Our posteriors also favour the presence of a superfluid phase in the core, a relatively low stellar compactness, M/R  1.4 × 108 cm s−1. Although the procedure laid out here still has large uncertainties, these constraints could become tighter when additional observations become available.
ISSN:0035-8711
1365-2966
DOI:10.1093/mnras/sty445