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

Salama, Maïssa and Ziegler, Carl and Baranec, Christoph and Liu, Michael C. and Law, Nicholas M. and Riddle, Reed and Henry, Todd J. and Winters, Jennifer G. and Jao, Wei-Chun and Ou, James and Hermosillo Ruiz, Arcelia (2022) An Adaptive Optics Census of Companions to Northern Stars Within 25 pc with Robo-AO. Astronomical Journal, 163 (5). Art. No. 200. ISSN 0004-6256. doi:10.3847/1538-3881/ac53fc. https://resolver.caltech.edu/CaltechAUTHORS:20220407-392556540

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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° searching for tight companions. We detected 154 companion candidates with separations ranging from ∼0.″15 to 4.″0 and magnitude differences up to Δm_(i') ≤ 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 two were ruled out as background objects. We complemented the high-resolution imaging companion search with a search for comoving 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% ± 3.0% (44%) for FGK stars and 28.2% ± 2.3% (27%) for M stars, as well as higher-order fractions of 5.5% ± 1.1% (11%) and 3.9% ± 0.9% (5%) for FGK stars and M-type stars, respectively.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3847/1538-3881/ac53fcDOIArticle
https://arxiv.org/abs/2203.11250arXivDiscussion Paper
ORCID:
AuthorORCID
Salama, Maïssa0000-0002-5082-6332
Ziegler, Carl0000-0002-0619-7639
Baranec, Christoph0000-0002-1917-9157
Liu, Michael C.0000-0003-2232-7664
Law, Nicholas M.0000-0001-9380-6457
Riddle, Reed0000-0002-0387-370X
Henry, Todd J.0000-0002-9061-2865
Winters, Jennifer G.0000-0001-6031-9513
Jao, Wei-Chun0000-0003-0193-2187
Ou, James0000-0002-8439-7767
Hermosillo Ruiz, Arcelia0000-0002-3376-7297
Additional Information:© 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2021 October 6; revised 2022 February 7; accepted 2022 February 7; published 2022 April 7. The Robo-AO system is supported by collaborating partner institutions, the California Institute of Technology and the Inter-University Centre for Astronomy and Astrophysics, and by the National Science Foundation under grant Nos. AST-0906060, AST-0960343, and AST-1207891, by the Mount Cuba Astronomical Foundation, and by a gift from Samuel Oschin. We are grateful to the Palomar Observatory staff for their ongoing support of Robo-AO on the 60 inch telescope, particularly S. Kunsman, M. Doyle, J. Henning, R. Walters, G. Van Idsinga, B. Baker, K. Dunscombe, and D. Roderick. This research was funded in part by grants to M. Liu from the Gordon and Betty Moore Foundation (Grant GBMF8550) and the National Science Foundation (AST-1518339). JGW is supported by the National Aeronautics and Space Administration under grant No. 80NSSC18K0476 issued through the XRP Program. This research has made use of the SIMBAD database, operated by Centre des Données Stellaires (Strasbourg, France), and bibliographic references from the Astrophysics Data System maintained by SAO/NASA. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC; https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This research has made use of the Washington Double Star Catalog maintained at the U.S. Naval Observatory. Facility: PO:1.5m (Robo-AO). -
Funders:
Funding AgencyGrant Number
NSFAST-0906060
NSFAST-0960343
NSFAST-1207891
Mt. Cuba Astronomical FoundationUNSPECIFIED
Samuel OschinUNSPECIFIED
Gordon and Betty Moore FoundationGBMF8550
NSFAST-1518339
NASA80NSSC18K0476
Gaia Multilateral AgreementUNSPECIFIED
Subject Keywords:Binary stars; Multiple stars; Close binary stars; High angular resolution; Direct imaging; Astronomical methods; Observational astronomy; Astronomy data analysis; Solar neighborhood
Issue or Number:5
Classification Code:Unified Astronomy Thesaurus concepts: Binary stars (154); Multiple stars (1081); Close binary stars (254); High angular resolution (2167); Direct imaging (387); Astronomical methods (1043); Observational astronomy (1145); Astronomy data analysis (1858); S
DOI:10.3847/1538-3881/ac53fc
Record Number:CaltechAUTHORS:20220407-392556540
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220407-392556540
Official Citation:Maïssa Salama et al 2022 AJ 163 200
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114189
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:07 Apr 2022 09:58
Last Modified:07 Apr 2022 20:22

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  • Salama, Maïssa and Ziegler, Carl and Baranec, Christoph and Liu, Michael C. and Law, Nicholas M. and Riddle, Reed and Henry, Todd J. and Winters, Jennifer G. and Jao, Wei-Chun and Ou, James and Hermosillo Ruiz, Arcelia An Adaptive Optics Census of Companions to Northern Stars Within 25 pc with Robo-AO. (deposited 07 Apr 2022 09:58) [Currently Displayed]

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