Download Exomoon Detections with TESS, CHEOPS, and PLATO

Exomoon Detections with TESS, CHEOPS, and PLATO
René Heller1, Michael Hippke2, Ben Placek3, Daniel Angerhausen4,5, Eric Agol6,7
1
Max Planck Institute for Solar System Research, PLATO Data Center, Justus-von-Liebig-Weg 3, 37077 Göttingen, Germany, [email protected]
2
Luiter Straße 21b, 47506 Neukirchen-Vluyn, Germany, [email protected]
3
Center for Science and Technology, Schenectady County Community College, Schenectady, NY 12305, USA, [email protected]
4
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA, [email protected]; 5 USRA NASA Postdoctoral Program Fellow
6
Astronomy Department, U of Washington, Seattle, WA 98195, USA, [email protected]; 7 NASA Astrobiology Institute’s Virtual Planetary Laboratory
The Orbital Sampling Effect
Transit Timing Variations and Transit Duration Variations
Moons store key information about planet formation that is inaccessible by planet
observations alone [1]. Exoplanets smaller than the largest solar system moon
(Ganymede, 0.4 R⨁) have been detected with the Kepler space telescope [2], but
no exomoon has yet been found [3]. Large exomoons could be detectable with
Kepler [4,5,6,7] or with the upcoming PLATO mission [8]. Big moons can form
around super-Jovian planets [9,10], dozens of which have been found in the stellar
habitable zones around Sun-like stars. The discovery of a Mars-mass moon in the
habitable zone would make it a primary target for astrobiological studies. Here we
highlight two novel methods to search for exomoons around transiting exoplanets.
Phase-folded transit light curves of exoplanets with moons may show what we
refer to as the orbital sampling effect, which emerges after about a dozen transits.
Statistically speaking, a moon appears more often at large apparent separations
from its planet and thereby creates an extra distortion in the average transit shape.
While the orbital sampling effect is a direct photometric signature of the moon
itself, an independent verification of an exomoon is possible if the planet shows
additional transit timing variations (TTVs) and transit duration variations (TDVs)
[14]. Transits of planets with moons are not strictly periodic due to the planetary
motion around the planet-moon(s) barycenter. Sometimes the planetary transit is
late, at other times it is too early with respect to the average timing. Transit durations
vary according to the planet’s instantaneous velocity around the local barycenter.
After many transits of an exoplanet with a single moon, the TTV-TDV diagram
forms an ellipse. Multiple moons cause more complex patterns. We find that a
combination of TESS, CHEOPS, and PLATO data would offer a compelling
opportunity for an exomoon discovery around a bright star [14].
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data from exoplanets.eu
as of 30 June 2016
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transit duration variation [minutes]
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normalized stellar brightness [%]
planetary mass [Jupiter masses]
Why Exomoons Are Important
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stellar distance [AU]
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Figure 1: Extrasolar planets and brown dwarf candidates with known masses and
stellar distances. 655 objects have been detected via radial velocity or astrometry
measurements, 423 objects are transiting, and 67 objects have been directly
imaged (1145 objects in total). The blue shaded region illustrates the solar
habitable zone defined by the runaway greenhouse limit (inner edge) and the
maximum greenhouse (outer edge) [11,12]. Most objects in the habitable zone
are super-Jovian planets, which could be orbited by large exomoons.
Moons cannot be detected by stellar radial velocity measurements, and exomoon
detections via direct imaging of extrasolar planets are beyond current technological
feasibility. The transit method is the most promising means to find extrasolar
moons in the near future. At the PLATO Data Center, which is in charge of the
data calibration and processing of the upcoming PLATO mission (~2024-2030),
we also study the possibility of exomoon discoveries with PLATO.
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0
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time around planetary mid-transit [hours]
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Figure 2: Model for the orbital sampling effect due to a hypothetical extrasolar
moon [13]. The host planet is Kepler-229c, a 4.8 R⨁ planet in a 17 days orbit
around a 0.7 R⨀ star. Gray dots show the detrended and phase-folded Kepler
light curve, white dots are bins of 10 minutes, and the blue line is a transit model
for Kepler-229c with a super-Ganymede-sized moon (0.7 R⨁). The inset in the
lower left corner shows a zoom into the transit ingress with three different moon
models (see legend). The inset at the right illustrates our model of a transiting
planet (black circle) with a probability density distribution Ps(x) for the hypothetical
satellite, where x is its sky-projected distance to the planet.
Our preliminary studies suggest that the orbital sampling effect can be detectable
for moons akin to the solar system moons if the host star is a photometrically
quiet M dwarf and if more than a dozen transits are available for phase-folding
[6,7,13].
Exoplanets I Conference, 3-8 July 2016, Davos, Switzerland
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data
one-moon model
two-moon model
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transit timing variation [minutes]
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Figure 3: TTV-TDV simulations for an exoplanet with a moon [14]. We assumed an
Earth-mass planet with a Mars-mass moon (a mass ratio akin to the Pluto-Charon
system) in a 236 days orbit around a 0.55 M⨀, 0.53 R⨀ star (like KOI-868). Yellow
symbols represent simulated Kepler observations, the solid ellipse illustrates our
best-fit model for a single moon, and the dashed line is our best-fit model for a
two-moon scenario. Bayesian statistics favors the one-moon interpretation.
References
[1] Heller+ (2014) Astrobiology 14 798
[2] Barclay+ (2013) Nature 494 452
[3] Kipping+ (2015) ApJ 813 14
[4] Kipping+ (2012) ApJ 750 115
[5] Szabó+ (2013) A&A 553 A17
[6] Heller (2014) ApJ 787 14
[7] Hippke (2015) ApJ 806 51
[8] Hippke & Angerhausen (2015) ApJ 810 29
[9] Canup & Ward (2006) Nature 441 834
[10] Heller & Pudritz (2015) ApJ 806 181
[11] Kopparapu+ (2013) ApJ 765 131
[12] Heller & Pudritz (2015) A&A 578 A19
[13] Heller+ (2016) ApJ 820 88
[14] Heller+ (2016) A&A 591 A67