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The impact of superconductivity and the Hall effect in models of magnetised neutron stars

Published online by Cambridge University Press:  06 September 2021

Ankan Sur*
Affiliation:
Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Bartycka 18, 00-716 Warsaw, Poland
Brynmor Haskell
Affiliation:
Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Bartycka 18, 00-716 Warsaw, Poland
*
*Author for correspondence: Ankan Sur, E-mail: ankansur@camk.edu.pl
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Abstract

Equilibrium configurations of the internal magnetic field of a pulsar play a key role in modelling astrophysical phenomena from glitches to gravitational wave emission. In this paper, we present a numerical scheme for solving the Grad–Shafranov equation and calculating equilibrium configurations of pulsars, accounting for superconductivity in the core of the neutron star, and for the Hall effect in the crust of the star. Our numerical code uses a finite difference method in which the source term appearing in the Grad–Shafranov equation, which is used to model the magnetic equilibrium is non-linear. We obtain solutions by linearising the source and applying an under-relaxation scheme at each step of computation to improve the solver’s convergence. We have developed our code in both C++ and Python, and our numerical algorithm can further be adapted to solve any non-linear PDEs appearing in other areas of computational astrophysics. We produce mixed toroidal–poloidal field configurations, and extend the portion of parameter space that can be investigated with respect to previous studies. We find that in even in the more extreme cases, the magnetic energy in the toroidal component does not exceed approximately 5% of the total. We also find that if the core of the star is superconducting, the toroidal component is entirely confined to the crust of the star, which has important implications for pulsar glitch models which rely on the presence of a strong toroidal field region in the core of the star, where superfluid vortices pin to superconducting fluxtubes.

Information

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Astronomical Society of Australia
Figure 0

Figure 1. Flowchart of our numerical algorithm.

Figure 1

Figure 2. Variation of $\alpha$ (contours of which give the poloidal field lines) at the equator across the radial direction for the constant electron density profile. The black solid line shows the analytical solution.

Figure 2

Figure 3. Variation of $\alpha$ (whose contours give the poloidal field lines) at the equator across the radial direction for eight values of the parameter s shown for three different density profiles in (a),(c), and (e). Variation of the maximum value of $\alpha$ across the angular direction with s. The density profiles are given as text in each figure.

Figure 3

Figure 4. Contours of poloidal field for different values of s (given in the text box in each figure) using the constant electron density profile $n_1=1$. The colourbar shows the strength of $\beta$. The black dotted line represents the location of stellar radius. We have shown contours of $\alpha$ having values $(0.1 \alpha_s,0.2\alpha_s,0.3\alpha_s,0.4\alpha_s,0.5\alpha_s,0.6\alpha_s,0.7\alpha_s,0.8\alpha_s,0.9\alpha_s,1\alpha_s)$.

Figure 4

Figure 5. Contours of poloidal field lines (with similar strengths as above), for the electron density profile $n_2=(1-r^2)$. The colourbar, again, shows the strength of $\beta$ and the red dotted line represent $r=R$.

Figure 5

Figure 6. Contours of poloidal field lines with different s values for the $n=1$ polytropic density profile $\rho=\rho_c\frac{sin(\pi r/R)}{\pi r/R}$. The colourbar, again, shows the strength of $\beta$ and the red dotted line represent $r=R$.

Figure 6

Table 1. The percentage of $\mathcal{E}_{tor}/\mathcal{E}_{mag}$ for different parameter values of s for $n_2(r)=(1-r^2).$ A comparison is also shown with Armaza et al. (2015) and Gourgouliatos et al. (2013).

Figure 7

Figure 7. Percentage fraction of the toroidal magnetic energy ($\mathcal{E}_{tor}$) to the total magnetic energy $\mathcal{E}_{mag}$) for two different density profiles given in figure labels for the setup given in Subsection 4.1.

Figure 8

Figure 8. Magnetic field lines and the strength of $\beta$ for the Hall equilibrium in the crust and MHD equilibrium in core.

Figure 9

Figure 9. Percentage fraction of the toroidal magnetic energy ($\mathcal{E}_{tor}$) to the total magnetic energy $\mathcal{E}_{mag}$) for the pure Hall (setup in 4.1) and mixed Hall+MHD (setup in 4.2) with varying s.

Figure 10

Figure 10. Contours of poloidal field lines for two different values of s in the superconducting core Hall equilibrium crust. The location of the crust–core interface is represented by the solid grey line at $r=0.9R$, while the red dotted line shows the stellar surface. The colourscale represents the strength of the toroidal field $\beta$.

Figure 11

Figure 11. (a) Number of iterations as a function of accuracy for three different grid sizes for the two versions of our code. (b) The number of iterations taken by our solvers to reach a certain accuracy when generating different field geometries, purely poloidal ($s=0$) and the mixed poloidal–toroidal($s=5$).