Binary Star Evolution Modules in REBOUNDx

TL;DR

This paper introduces a comprehensive, high-accuracy N-body simulation extension called REBOUNDx that models complex close-binary evolution processes including mass transfer, winds, magnetic braking, and relativistic effects.

Contribution

It provides an interoperable, modular framework integrating multiple binary evolution effects within N-body dynamics, with conservation and stability features.

Findings

Conservation of linear momentum during mass transfer processes.

Implementation of a variety of stellar wind and magnetic braking models.

The code is publicly available at https://github.com/malidib/ReboundS.

Abstract

Close-binary evolution couples Roche-lobe overflow (RLOF), common-envelope (CE) drag, stellar winds, magnetic braking, and gravitational-wave losses, exchanging mass and angular momentum while reshaping orbits and spins. We present interoperable effects in the REBOUNDx extension to REBOUND that embed these processes within high-accuracy N-body dynamics. The suite includes: a momentum-conserving RLOF operator with conservative and systemic channels and configurable specific-j loss; a CE drag model based on Mach-dependent dynamical friction with kick limiting; isotropic Reimers winds, Parker-type thermal winds, and Eddington-limited outflows powered by a parametric stellar-evolution module supplying mass-dependent R and L; magnetic braking via the Verbunt-Zwaan/Kawaler torque with a saturation-aware closed-form spin update; and post-Newtonian corrections 2PN point-mass and spin-spin; 2.5PN radiation reaction. Linear momentum is conserved for conservative transfer, a minimal corrective torque enforces angular-momentum consistency, and adaptive sub-stepping stabilizes evolution near contact. Inter-module flags coordinate wind/RLOF/CE activity. The unit-agnostic framework enables self-consistent, time-resolved studies of close binaries in isolated or dynamically rich settings. Multiple examples and comparisons against other codes are provided in the Appendix. The code is available at https://github.com/malidib/ReboundS .