On the formation history of Galactic double neutron stars (1805.07974v2)

Abstract: Double neutron stars (DNSs) have been observed as Galactic radio pulsars, and the recent discovery of gravitational waves from the DNS merger GW170817 adds to the known DNS population. We perform rapid population synthesis of massive binary stars and discuss model predictions, including formation rates, mass distributions, and delay time distributions. We vary assumptions and parameters of physical processes such as mass transfer stability criteria, supernova kick distributions, remnant mass distributions and common-envelope energetics. We compute the likelihood of observing the orbital period-eccentricity distribution of the Galactic DNS population under each of our population synthesis models, allowing us to quantitatively compare the models. We find that mass transfer from a stripped post-helium-burning secondary (case BB) onto a neutron star is most likely dynamically stable. We also find that a natal kick distribution composed of both low (Maxwellian $\sigma=30\rm~km~s^{-1}$) and high ($\sigma=265\rm~km~s^{-1}$) components is preferred over a single high-kick component. We find that the observed DNS mass distribution can place strong constraints on model assumptions.

Formation History of Galactic Double Neutron Stars

The academic paper titled "On the formation history of Galactic double neutron stars" explores the intricate dynamics governing the formation and evolution of Galactic double neutron star (DNS) systems. The authors employ rapid population synthesis, utilizing the Compact Object Mergers: Population Astrophysics and Statistics (COMPAS) suite, to simulate massive binary evolutions culminating in DNS systems.

Overview

DNS systems, observable as Galactic radio pulsars, have recently gained significant interest due to gravitational wave detections such as GW170817, which was a DNS merger. By conducting rapid population synthesis, the authors aim to predict DNS formation rates, mass distributions, and delay-time distributions. The synthesis process models the evolutionary trajectory from zero age main sequence (ZAMS) stars to DNSs. Various parameters are scrutinized, including mass transfer stability, supernova natal kicks, remnant mass prescriptions, and common-envelope energetics. This methodological diversity enables the authors to compute the probability of observing DNS orbital period–eccentricity distributions across different models for comparison.

Findings

Their simulations reveal that mass transfer from a stripped, post-helium-burning secondary onto a neutron star typically remains dynamically stable. This interaction contributes significantly to the mass and eccentricity characteristics observed in Galactic DNSs. Moreover, their findings suggest a preference for a natal kick distribution encompassing both low (Maxwellian $\sigma=30\rm~km~s^{-1}$) and high ($\sigma=265\rm~km~s^{-1}$) components, as opposed to a distribution dominated by high-kick components alone. DNS mass distribution thus provides critical constraints on theoretical models, supporting nuanced understandings of binary stellar evolution.

Implications and Speculations

Practically, this research aids in interpreting observational data of DNSs and predicting new DNS mergers observable via gravitational waves. Theoretically, it advances the understanding of stellar evolution, particularly in binary systems with massive constituents. The nuanced supernovae explosion mechanics and natal kick distributions explored offer deeper insights into DNS formation channels. The paper aptly positions itself for future exploration into metallicity effects and more detailed hydrodynamic models of mass transfer processes.

Conclusion

The authors effectively establish constraints on DNS population synthesis through empirical and computational methodology, offering valuable insights into the Galactic DNS phenomena. Their research provides a robust foundation for further explorations into the dynamics shaping DNS systems, with significant implications for astrophysical observations and theoretical models.