Issue |
A&A
Volume 594, October 2016
|
|
---|---|---|
Article Number | A63 | |
Number of page(s) | 14 | |
Section | Planets and planetary systems | |
DOI | https://doi.org/10.1051/0004-6361/201527828 | |
Published online | 13 October 2016 |
The International Deep Planet Survey
II. The frequency of directly imaged giant exoplanets with stellar mass⋆
1 LESIA, Observatoire de Paris, CNRS,
Université Paris Diderot, Université Pierre et Marie Curie,
5 place Jules Janssen,
92190
Meudon,
France
e-mail: raphael.galicher@obspm.fr
2 Groupement d’Intérêt Scientifique
PHASE (Partenariat Haute résolution Angulaire Sol Espace) between ONERA, Observatoire
de Paris, CNRS and Université Paris Diderot, 75000
Paris,
France
3 National Research Council Canada,
5071 West Saanich Road, Victoria, BC,
V9E 2E7,
Canada
4 Lawrence Livermore National
Laboratory, 7000 East
Ave., Livermore,
CA
94550,
USA
5 Kavli Institute for Particle
Astrophysics and Cosmology, Stanford University, CA
94305,
USA
6 Department of Physics and Astronomy,
University of California, Los
Angeles, CA
90095,
USA
7 Lunar and Planetary Laboratory,
University of Arizona, Tucson
AZ
85721,
USA
8 CASS, University of California San
Diego, La Jolla,
CA
92093-0424,
USA
9 Department of Physics and Astronomy,
University of Georgia, Athens, GA
30602-2451,
USA
10 Arizona State
University, Tempe,
AZ
85281,
USA
11 Département de Physique, Université
de Montréal, C.P.
6128
Succ. Centre-Ville, Montréal,
QC
H3C 3J7,
Canada
12 SETI Institute,
Carl Sagan Center, 189 Bernardo
Avenue, Mountain
View, CA
94043,
USA
Received:
25
November
2016
Accepted:
17
July
2016
Context. Radial velocity and transit methods are effective for the study of short orbital period exoplanets but they hardly probe objects at large separations for which direct imaging can be used.
Aims. We carried out the international deep planet survey of 292 young nearby stars to search for giant exoplanets and determine their frequency.
Methods. We developed a pipeline for a uniform processing of all the data that we have recorded with NIRC2/Keck II, NIRI/Gemini North, NICI/Gemini South, and NACO/VLT for 14 yr. The pipeline first applies cosmetic corrections and then reduces the speckle intensity to enhance the contrast in the images.
Results. The main result of the international deep planet survey is the
discovery of the HR 8799 exoplanets. We also detected 59 visual multiple systems including
16 new binary stars and 2 new triple stellar systems, as well as 2279 point-like sources. We used Monte Carlo
simulations and the Bayesian theorem to determine that of stars harbor at least one giant planet between
0.5 and 14 MJ and between
20 and 300 AU. This result is obtained assuming
uniform distributions of planet masses and semi-major axes. If we consider power law
distributions as measured for close-in planets instead, the derived frequency is
, recalling the strong impact of assumptions on Monte
Carlo output distributions. We also find no evidence that the derived frequency depends on
the mass of the hosting star, whereas it does for close-in planets.
Conclusions. The international deep planet survey provides a database of confirmed background sources that may be useful for other exoplanet direct imaging surveys. It also puts new constraints on the number of stars with at least one giant planet reducing by a factor of two the frequencies derived by almost all previous works.
Key words: planets and satellites: gaseous planets / planets and satellites: fundamental parameters / methods: observational / methods: data analysis / methods: statistical / instrumentation: high angular resolution
Tables 11−15 are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/594/A63
© ESO, 2016
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.