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تسجيل مستخدم جديدExploring Exoplanet Populations with NASAs Kepler Mission
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The Kepler Mission is exploring the diversity of planets and planetary systems. Its legacy will be a catalog of discoveries sufficient for computing planet occurrence rates as a function of size, orbital period, star-type, and insolation flux. The mission has made significant progress toward achieving that goal. Over 3,500 transiting exoplanets have been identified from the analysis of the first three years of data, 100 of which are in the habitable zone. The catalog has a high reliability rate (85-90% averaged over the period/radius plane) which is improving as follow-up observations continue. Dynamical (e.g. velocimetry and transit timing) and statistical methods have confirmed and characterized hundreds of planets over a large range of sizes and compositions for both single and multiple-star systems. Population studies suggest that planets abound in our galaxy and that small planets are particularly frequent. Here, I report on the progress Kepler has made measuring the prevalence of exoplanets orbiting within 1 AU of their host stars in support of NASAs long-term goal of finding habitable environments beyond the solar system.
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We have carried out an intensive study of photometric (Kepler Mission) and spectroscopic data on the system Kepler-2 (HAT-P-7A) using the dedicated software WinFitter. The mean individual data-point error of the normalized flux values for this system
is 0.00015, leading to the models specification for the mean reference flux to an accuracy of $sim$0.5 ppm. This testifies to the remarkably high accuracy of the binned data-set, derived from over 1.8 million individual observations. Spectroscopic data are reported with the similarly high-accuracy radial velocity amplitude measure of $sim$2 m s$^{-1}$. The analysis includes discussion of the fitting quality and model adequacy. Our derived absolute parameters for Kepler-2 are as follows: $M_p$ (Jupiter) 1.80 $pm$ 0.13; $R_{star}$ 1.46 $pm 0.08 times 10^6$ km; $R_p$ 1.15 $pm 0.07 times 10^5$ km. These values imply somewhat larger and less condensed bodies than previously catalogued, but within reasonable error estimates of such literature parameters. We find also tidal, reflection and Doppler effect parameters, showing that the optimal model specification differs slightly from a `cleaned model that reduces the standard deviation of the $sim$3600 binned light curve points to less than 0.9 ppm. We consider these slight differences, making comparisons with the hot-jupiter systems Kepler-1 (TrES-2) and 13.
We have used the {it Spitzer Space Telescope} to observe two transiting planetary systems orbiting low mass stars discovered in the Kepler Ktwo mission. The system K2-3 (EPIC 201367065) hosts three planets while EPIC 202083828 (K2-26) hosts a single
planet. Observations of all four objects in these two systems confirm and refine the orbital and physical parameters of the planets. The refined orbital information and more precise planet radii possible with Spitzer will be critical for future observations of these and other Ktwo targets. For K2-3b we find marginally significant evidence for a Transit Timing Variation between the Ktwo and Spitzer epochs.
Numerous telescopes and techniques have been used to find and study extrasolar planets, but none has been more successful than NASAs Kepler Space Telescope. Kepler has discovered the majority of known exoplanets, the smallest planets to orbit normal
stars, and the worlds most likely to be similar to our home planet. Most importantly, Kepler has provided our first look at typical characteristics of planets and planetary systems for planets with sizes as small as and orbits as large as those of the Earth.
Over 30% of the ~4000 known exoplanets to date have been discovered using validation, where the statistical likelihood of a transit arising from a false positive (FP), non-planetary scenario is calculated. For the large majority of these validated pl
anets calculations were performed using the vespa algorithm (Morton et al. 2016). Regardless of the strengths and weaknesses of vespa, it is highly desirable for the catalogue of known planets not to be dependent on a single method. We demonstrate the use of machine learning algorithms, specifically a gaussian process classifier (GPC) reinforced by other models, to perform probabilistic planet validation incorporating prior probabilities for possible FP scenarios. The GPC can attain a mean log-loss per sample of 0.54 when separating confirmed planets from FPs in the Kepler threshold crossing event (TCE) catalogue. Our models can validate thousands of unseen candidates in seconds once applicable vetting metrics are calculated, and can be adapted to work with the active TESS mission, where the large number of observed targets necessitates the use of automated algorithms. We discuss the limitations and caveats of this methodology, and after accounting for possible failure modes newly validate 50 Kepler candidates as planets, sanity checking the validations by confirming them with vespa using up to date stellar information. Concerning discrepancies with vespa arise for many other candidates, which typically resolve in favour of our models. Given such issues, we caution against using single-method planet validation with either method until the discrepancies are fully understood.
The prime Kepler mission detected 34,032 transit-like signals, out of which 8,054 were identified as likely due to astrophysical planet transits or eclipsing binaries. We manually examined 306 of the remaining 25,978 detections, and found six plausib
le transiting or eclipsing objects, five of which are plausible planet candidates (PCs), and one stellar companion. One of our new PCs is a possible new second planet in the KOI 4302 system. Another new PC is a possible new planet around the KOI 4246, and when combined with a different possible planet rescued by the False Positive Working Group, we find that KOI 4246 may be a previously unrecognized three-planet system. end{abstract}
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