The Blue Stragglers of the Old Open Cluster NGC 188

  • Robert D. Mathieu
  • Aaron M. Geller
Part of the Astrophysics and Space Science Library book series (ASSL, volume 413)


The old (7 Gyr) open cluster NGC 188 has yielded a wealth of astrophysical insight into its rich blue straggler population. Specifically, the NGC 188 blue stragglers are characterised by:
  • A binary frequency of 80 % for orbital periods less than 104 days;

  • Typical orbital periods around 1,000 days;

  • Typical secondary star masses of 0.5 M;

  • At least some white dwarf companion stars;

  • Modestly rapid rotation;

  • A bimodal radial spatial distribution;

  • Dynamical masses greater than standard stellar evolution masses (based on short-period binaries);

  • Underluminosity for dynamical masses (short-period binaries).

Extensive N-body modeling of NGC 188 with empirical initial conditions reproduces the properties of the cluster, and in particular the main-sequence solar-type binary population. The current models also reproduce well the binary orbital properties of the blue stragglers, but fall well short of producing the observed number of blue stragglers. This deficit could be resolved by reducing the frequency of common-envelope evolution during Roche lobe overflow. Both the observations and the N-body models strongly indicate that the long-period blue-straggler binaries—which dominate the NGC 188 blue-straggler population—are formed by asymptotic-giant (primarily) and red-giant mass transfer onto main-sequence stars. The models suggest that the few non-velocity-variable blue stragglers formed from mergers or collisions. Several remarkable short-period double-lined binaries point to the importance of subsequent dynamical exchange encounters, and provide at least one example of a likely collisional origin for a blue straggler.


Orbital Period White Dwarf Open Cluster Binary Frequency Binary Property 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of AstronomyUniversity of Wisconsin-MadisonMadisonUSA

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