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New binaries from the SHINE survey
- Publication Year :
- 2022
-
Abstract
- We present the multiple stellar systems observed within the SpHere INfrared survey for Exoplanet (SHINE). SHINE searched for sub-stellar companions to young stars using high contrast imaging. Although stars with known stellar companions within the SPHERE field of view (< 5.5 arcsec) were removed from the original target list, we detected additional stellar companions to 78 of the 463 SHINE targets observed so far. Twenty-seven per cent of the systems have three or more components. Given the heterogeneity of the sample in terms of observing conditions and strategy, tailored routines were used for data reduction and analysis, some of which were specifically designed for these datasets. We then combined SPHERE data with literature and archival data, TESS light curves, and Gaia parallaxes and proper motions for an accurate characterisation of the systems. Combining all data, we were able to constrain the orbits of 25 systems. We carefully assessed the completeness of our sample for separations between 50–500 mas (corresponding to periods of a few years to a few decades), taking into account the initial selection biases and recovering part of the systems excluded from the original list due to their multiplicity. This allowed us to compare the binary frequency for our sample with previous studies and highlight interesting trends in the mass ratio and period distribution. We also found that, when such an estimate was possible, the values of the masses derived from dynamical arguments were in good agreement with the model predictions. Stellar and orbital spins appear fairly well aligned for the 12 stars that have enough data, which favours a disk fragmentation origin. Our results highlight the importance of combining different techniques when tackling complex problems such as the formation of binaries and show how large samples can be useful for more than one purpose.
Details
- Database :
- OAIster
- Notes :
- English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1356421141
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.1051.0004-6361.202140510