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Internal constitution of the outer crust of non-accreted neutron stars and magnetars

par Servais, Juliette ;Chamel, Nicolas
Référence Astronomy & astrophysics
Publication Publié, 2026-05-14

Article révisé par les pairs

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Résumé :

Context. Determining the internal constitution of the outer crust of magnetars is important for interpreting several of their astrophysical manifestations. In particular, the crustal composition is a key input for simulations of r-process nucleosynthesis in giant flareejecta. However, traditional methods are computationally expensive, limiting their use in large-scale studies. Although faster iterativeapproaches exist, they are restricted to unmagnetized matter and strongly quantizing magnetic fields, leaving the intermediate fieldstrengths characteristic of observed magnetars without an efficient treatment.Aims. We developed the program magcrust to extend these existing iterative approaches, enabling the rapid computation of theouter-crust composition of cold, non-accreted magnetars over the full range of the magnetic-field strengths inferred for these objects.Methods. Transitions between adjacent crustal layers are computed by solving approximate equilibrium conditions at the interface.Nuclear abundances and layer depths are estimated from approximate solutions of Einstein’s equations of general relativity.Results. The performance and accuracy of the program were assessed against detailed numerical calculations. Relative deviationsfrom exact transition properties remain within a few percent, and crustal compositions are well reproduced across 17 nuclear masstables and 1300 magnetic-field strengths from 1013 to 1016 G. Computation times are reduced by factors of 103 − 107compared totraditional approaches.Conclusions. This program provides a robust and efficient tool for determining the stratification of magnetars’ outer crust over thefull range of astrophysically relevant magnetic-field strengths. Its computational speed makes it well suited to systematic calculations,including sensitivity analyses, uncertainty quantification, and ensemble studies.