Artist’s impression of two black holes colliding.

Formation of merging double compact objects

Current ground based gravitational wave observatories such as LIGO, Virgo, and KAGRA and future space-based detectors like LISA can detect gravitational waves emitted by merging double compact objects. Interacting binaries are arguably the most important astrophysical laboratories available for studying compact objects. While a plethora of scenarios has been proposed in the literature for the formation of coalescing binary compact objects, the evolution of isolated binary stellar systems remains the dominant one.

It is now established that most massive stars are members of binary or higher-order stellar systems. More often than not, these stars will interact during their evolution which eventually leads to the formation of merging compact objects, such as black holes, neutron stars, and white dwarfs. Over hundreds of millions of years, these systems slowly spiral inward towards each other, eventually colliding. During the last seconds of their life, these compact objects orbit each other at an ever-increasing rate emitting extreme amounts of energy in gravitational waves.

While some aspects of the astrophysics of these binaries can be obtained from observations and modelling of present-day properties of individual, well-studied systems, more comprehensive insight requires understanding their astrophysical origin, population properties, evolutionary links to other stellar systems, and interplay with their environments. Binary population synthesis is a modelling technique that allows scientists to rapidly evolve millions of binary systems and hence obtain statistical properties of compact object astrophysical observables. At GWSC, we have developed a next-generation binary population synthesis code – POSYDON – incorporating full stellar structure and binary evolution modelling.  These modelling advancements are crucial because, e.g., black-hole spins depend on the stellar and binary evolution interaction history and are currently poorly predicted in standard rapid population synthesis models.


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