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Triage of the Gaia DR3 astrometric orbits – I. A sample of binaries with probable compact companions

Shahaf, S. and Bashi, D. and Mazeh, T. and Faigler, S. and Arenou, F. and El-Badry, K. and Rix, H. W. (2023) Triage of the Gaia DR3 astrometric orbits – I. A sample of binaries with probable compact companions. Monthly Notices of the Royal Astronomical Society, 518 (2). pp. 2991-3003. ISSN 0035-8711. doi:10.1093/mnras/stac3290. https://resolver.caltech.edu/CaltechAUTHORS:20230105-896230000.64

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Abstract

In preparation for the release of the astrometric orbits of Gaia, Shahaf et al. (2019) proposed a triage technique to identify astrometric binaries with compact companions based on their astrometric semimajor axis, parallax, and primary mass. The technique requires the knowledge of the appropriate mass–luminosity relation to rule out single or close-binary main-sequence companions. The recent publication of the Gaia DR3 astrometric orbits used a schematic version of this approach, identifying 735 astrometric binaries that might have compact companions. In this communication, we return to the triage of the DR3 astrometric binaries with more careful analysis, estimating the probability for its astrometric secondary to be a compact object or a main-sequence close binary. We compile a sample of 177 systems with highly probable non-luminous massive companions, which is smaller but cleaner than the sample reported in Gaia DR3. The new sample includes eight candidates to be black-hole systems with compact-object masses larger than 2.4 M_⊙. The orbital–eccentricity–secondary–mass diagram of the other 169 systems suggests a tentative separation between the white-dwarf and the neutron-star binaries. Most white-dwarf binaries are characterized by small eccentricities of about 0.1 and masses of 0.6 M⊙, while the neutron star binaries display typical eccentricities of 0.4 and masses of 1.3 M_⊙.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/mnras/stac3290DOIArticle
ORCID:
AuthorORCID
Shahaf, S.0000-0001-9298-8068
Bashi, D.0000-0002-9035-2645
Mazeh, T.0000-0002-3569-3391
Faigler, S.0000-0002-8368-5724
Arenou, F.0000-0003-2837-3899
El-Badry, K.0000-0002-6871-1752
Rix, H. W.0000-0003-4996-9069
Additional Information:© 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). We thank the referee, Zephyr Penoyre, for the thoughtful comments and suggestions that helped us improved the original manuscript. We thank Na’ama Hallakoun, Shany Danieli, Boaz Katz, and Soetkin Janssens for their insightful suggestions and valuable comments. The research of SS is supported by a Benoziyo prize postdoctoral fellowship. This research was supported by grant no. 2016069 of the United States-Israel Binational Science Foundation (BSF) and by grant no. I-1498-303.7/2019 of the German-Israeli Foundation for Scientific Research and Development (GIF) to TM and HWR. This work has made use of data from the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://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 work made use of ArtPop, a python package for synthesizing stellar populations and simulating realistic images of stellar systems (Greco & Danieli 2021); the MIST isochrone grids (Paxton et al. 2011, 2013, 2015; Choi et al. 2016; Dotter 2016); The WD models package for WD photometry to physical parameters; catsHTM, a tool for fast accessing and cross-matching large astronomical catalogues (Soumagnac & Ofek 2018); astropy, a community-developed core python package for Astronomy (Astropy Collaboration et al. 2013, 2018); matplotlib (Hunter 2007); numpy (Oliphant 2006; van der Walt, Colbert & Varoquaux 2011); scipy (Virtanen et al. 2020); and scikit-learn (Pedregosa et al. 2011). DATA AVAILABILITY. All data underlying this research are publicly available.
Funders:
Funding AgencyGrant Number
Weizmann Institute of ScienceUNSPECIFIED
Binational Science Foundation (USA-Israel)2016069
German-Israeli Foundation for Research and DevelopmentI-1498-303.7/2019
Gaia Multilateral AgreementUNSPECIFIED
Issue or Number:2
DOI:10.1093/mnras/stac3290
Record Number:CaltechAUTHORS:20230105-896230000.64
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20230105-896230000.64
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:118737
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:06 Jan 2023 00:07
Last Modified:06 Jan 2023 00:07

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