Statistical study for binary star evolution in dense embedded clusters
Wenjie Wu, Pavel Kroupa, Vikrant V. Jadhav

TL;DR
This study uses N-body simulations to analyze how primordial binaries evolve in dense embedded star clusters, revealing key parameters that influence binary survival and providing a new dynamical operator model.
Contribution
We develop an empirical dynamical operator framework for binary evolution in embedded clusters, improving previous models by including wide binaries and cluster gas effects.
Findings
Hard binaries heat the cluster and suppress wide binary formation.
Soft binaries tend to survive or be disrupted based on their energy.
Mass-ratio distribution is influenced more by stellar physics than dynamics.
Abstract
Context: The dynamical evolution of binary populations in embedded star clusters shapes the statistical properties of binaries observed in the Galactic field. Accurately modelling this process requires resolving both early cluster dynamics and binary interactions. Aims: We aim to characterize the early dynamical evolution of primordial binaries in embedded clusters and identify the key parameters that govern binary survival and disruption. Methods: We perform a set of direct -body simulations starting from 100\% primordial binaries in a time-varying gas potential of a gas-embedded cluster. To describe the evolution of binary orbital properties, we define empirical dynamical operators for period, binding energy, and mass ratio, and calibrate them across the simulated ensemble. Results:The binding energy and orbital period evolve in a consistent, sigmoidal fashion. Their…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Astrophysics and Star Formation Studies
