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arXiv · 2203.11250

An Adaptive Optics Census of Companions to Northern Stars Within 25 pc with Robo-AO

Maissa Salama·Carl Ziegler·Christoph Baranec·Michael C. Liu·Nicholas M. Law·Reed Riddle·Todd J. Henry·Jennifer G. Winters·Wei-Chun Jao·James Ou·Arcelia Hermosillo Ruiz
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Abstract

In order to assess the multiplicity statistics of stars across spectral types and populations in a volume-limited sample, we censused nearby stars for companions with Robo-AO. We report on observations of 1157 stars of all spectral types within 25 pc with decl. $>-13^{\circ}$ searching for tight companions. We detected 154 companion candidates with separations ranging from $\sim$0.15$''$ to 4.0$''$ and magnitude differences up to $\Delta$m$_{\textit{i'}}\le$7 using the robotic adaptive optics instrument Robo-AO. We confirmed physical association from Gaia EDR3 astrometry for 53 of the companion candidates, 99 remain to be confirmed, and 2 were ruled out as background objects. We complemented the high-resolution imaging companion search with a search for co-moving objects with separations out to 10,000 AU in Gaia EDR3, which resulted in an additional 147 companions registered. Of the 301 total companions reported in this study, 49 of them are new discoveries. Out of the 191 stars with significant acceleration measurements in the Hipparcos-Gaia catalog of accelerations, we detect companions around 115 of them, with the significance of the acceleration increasing as the companion separation decreases. From this survey, we report the following multiplicity fractions (compared to literature values): 40.9%$\pm$3.0% (44%) for FGK stars and 28.2%$\pm$2.3% (27%) for M stars, as well as higher-order fractions of 5.5%$\pm$1.1% (11%) and 3.9%$\pm$0.9% (5%) for FGK stars and M type stars, respectively.

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Maissa Salama, Carl Ziegler, Christoph Baranec, Michael C. Liu, Nicholas M. Law, Reed Riddle, Todd J. Henry, Jennifer G. Winters, Wei-Chun Jao, James Ou, Arcelia Hermosillo Ruiz. 2022-03-21. An Adaptive Optics Census of Companions to Northern Stars Within 25 pc with Robo-AO. https://doi.org/10.3847/1538-3881%2Fac53fc

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