J/AJ/155/205 Occurrence rates for Q1-Q16 KOI catalog planet cand. (Hsu+, 2018)
Improving the accuracy of planet occurrence rates from Kepler using approximate
Bayesian computation.
Hsu D.C., Ford E.B., Ragozzine D., Morehead R.C.
<Astron. J., 155, 205-205 (2018)>
=2018AJ....155..205H 2018AJ....155..205H (SIMBAD/NED BibCode)
ADC_Keywords: Exoplanets ; Stars, F-type ; Stars, G-type ; Stars, K-type ;
Models
Keywords: catalogs - methods: data analysis - methods: statistical -
planetary systems - stars: statistics
Abstract:
We present a new framework to characterize the occurrence rates of
planet candidates identified by Kepler based on hierarchical Bayesian
modeling, approximate Bayesian computing (ABC), and sequential importance
sampling. For this study, we adopt a simple 2D grid in planet radius
and orbital period as our model and apply our algorithm to estimate
occurrence rates for Q1-Q16 planet candidates orbiting solar-type stars.
We arrive at significantly increased planet occurrence rates for small
planet candidates (Rp<1.25 R⊕) at larger orbital periods
(P>80 day) compared to the rates estimated by the more common inverse
detection efficiency method (IDEM). Our improved methodology estimates
that the occurrence rate density of small planet candidates in the
habitable zone of solar-type stars is 1.6-0.5+1.2 per factor of 2
in planet radius and orbital period. Additionally, we observe a local
minimum in the occurrence rate for strong planet candidates marginalized
over orbital period between 1.5 and 2 R⊕ that is consistent with
previous studies. For future improvements, the forward modeling approach
of ABC is ideally suited to incorporating multiple populations, such
as planets, astrophysical false positives, and pipeline false alarms,
to provide accurate planet occurrence rates and uncertainties.
Furthermore, ABC provides a practical statistical framework for answering
complex questions (e.g., frequency of different planetary architectures)
and providing sound uncertainties, even in the face of complex selection
effects, observational biases, and follow-up strategies. In summary,
ABC offers a powerful tool for accurately characterizing a wide variety
of astrophysical populations.
Description:
In this study, we introduce approximate Bayesian computing (ABC) as a
tool for overcoming the above challenges to characterize the exoplanet
population in general and planet occurrence rates in particular. We also
develop a practical algorithm for applying ABC to infer planet occurrence
rates as a function of planet size and orbital period, allowing for direct
comparisons to results using previous methods. We verify and validate
the ABC algorithm using simulated data sets and report the results of
applying our algorithm to a recent catalog of Kepler planet candidates.
For observed planet candidate catalog properties, we adopt the Q1-Q16
planet candidate catalog obtained from the NASA Exoplanet Archive in 2017
March (Rowe et al. 2014, J/ApJ/784/45; Mullally et al. 2015, J/ApJS/217/31).
We find Np=3380 planet candidates associated with our target stars and
having estimated planet radii (Rp) in the range 0.5-16 R⊕ and
orbital periods (P) in the range 0.5-320 days.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 83 117 ABC, simplified Bayesian model, and IDEM
estimated occurrence rates for Q1-Q16 KOI catalog
planet candidates associated with FGK stars
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See also:
J/ApJ/784/45 : Kepler's multiple planet candidates. III. (Rowe+, 2014)
J/ApJ/790/146 : Planets in Kepler's multi-transiting systems (Fabrycky+, 2014)
J/ApJS/211/2 : Revised stellar properties of Q1-16 Kepler targets
(Huber+, 2014)
J/ApJ/809/8 : Terrestrial planet occurrence rates for KOI stars
(Burke+, 2015)
J/ApJ/812/46 : Transit metric for Q1-Q17 Kepler candidates (Thompson+, 2015)
J/ApJ/814/130 : Planet occurrence rates calculated for KOIs (Mulders+, 2015)
J/ApJS/217/18 : Potential transit signals in Kepler Q1-Q17 (Seader+, 2015)
J/ApJS/217/31 : Kepler planetary candidates. VI. 4yr Q1-Q16 (Mullally+, 2015)
J/ApJ/828/99 : Kepler pipeline transit signal recovery. III.
(Christiansen+, 2016)
J/ApJS/224/12 : Kepler planetary candidates. VII. 48-month (Coughlin+, 2016)
Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
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1- 6 F6.2 d b_Per [0.5/160] Lower value of period bin
8- 13 F6.2 d B_Per [1.25/320] Upper value of period bin
15- 19 F5.2 Rgeo b_Rad [0.5/12] Lower value of radius bin
21- 25 F5.2 Rgeo B_Rad [0.75/16] Upper value of radius bin
27 A1 --- l_ABC [<] Limit flag on ABC
28- 34 E7.3 --- ABC [3.6e-05/1.4] Full approximate Bayesian computing
(ABC) model estimated planet occurrence rate
36- 42 E7.3 --- e_ABC [2.2e-05/0.13]? Lower limit uncertainty in ABC
44- 50 E7.3 --- E_ABC [3.2e-05/0.19]? Upper limit uncertainty in ABC
52 A1 --- l_Bay [<] Limit flag on Bay
53- 59 E7.3 --- Bay [2.4e-05/0.8] Simplified Bayesian model estimated
planet occurrence rate
61- 67 E7.3 --- e_Bay [3.1e-05/0.086]? Uncertainty in Bay
69- 75 E7.3 --- IDEM [2.7e-05/0.174]? Inverse detection efficiency
method (IDEM) estimated planet occurrence rate
77- 83 E7.3 --- e_IDEM [2.6e-05/0.066]? Uncertainty in IDEM
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History:
From electronic version of the journal
(End) Tiphaine Pouvreau [CDS] 07-Dec-2018