Paper detail

Bayesian Characterization of Main Sequence Binaries in the Old Open Cluster NGC 188

The binary fractions of open and globular clusters yield powerful constraints on their dynamical state and evolutionary history. We apply publicly available Bayesian analysis code to a $UBVRIJHK_{S}$ photometric catalog of the old open cluster NGC 188 to detect and characterize photometric binaries along the cluster main sequence. This technique has the advantage that it self-consistently handles photometric errors, missing data in various bandpasses, and star-by-star prior constraints on cluster membership. Simulations are used to verify uncertainties and quantify selection biases in our analysis, illustrating that among binaries with mass ratios >0.5, we recover the binary fraction to better than 7% in the mean, with no significant dependence on binary fraction and a mild dependence on assumed mass ratio distribution. Using our photometric catalog, we recover the majority (65%$\pm$11%) of spectroscopically identified main sequence binaries, including 8 of the 9 with spectroscopically measured mass ratios. Accounting for incompleteness and systematics, we derive a mass ratio distribution that rises toward lower mass ratios (within our $q >$0.5 analysis domain). We observe a raw binary fraction for solar-type main sequence stars with mass ratios $q >$0.5 of 42%$\pm$4%, independent of the assumed mass ratio distribution to within its uncertainties, consistent with literature values for old open clusters but significantly higher than the field solar-type binary fraction. We confirm that the binaries identified by our method are more concentrated than single stars, in agreement with previous studies, and we demonstrate that the binary nature of those candidates which remain unidentified spectroscopically is strongly supported by photometry from Gaia DR2.

preprint2019arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.