A Population of Planetary Systems Characterized by Short-Period, Earth-Sized Planets
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A Population of planetary systems characterized by short-period, Earth-sized planets Jason H. Steffena,1 and Jeffrey L. Coughlinb,c aDepartment of Physics and Astronomy, University of Nevada, Las Vegas, NV 89154-4002; bSETI Institute, Mountain View, CA 94043; and cNASA Ames Research Center, Moffett Field, CA 94035 Edited by Neta A. Bahcall, Princeton University, Princeton, NJ, and approved August 15, 2016 (received for review April 26, 2016) We analyze data from the Quarter 1–17 Data Release 24 (Q1–Q17 population diverged from that which produced the more typical DR24) planet candidate catalog from NASA’s Kepler mission, spe- Kepler-like systems. cifically comparing systems with single transiting planets to sys- This work will proceed as follows. We first describe our sample tems with multiple transiting planets, and identify a population of selection process and outline a Monte Carlo study of the singles exoplanets with a necessarily distinct system architecture. Such an and multis to identify regions of interest in planet parameters. architecture likely indicates a different branch in their evolution- For one of these regions, we estimate the contribution of two ary past relative to the typical Kepler system. The key feature of possible sources for the observations—namely false positives and these planetary systems is an isolated, Earth-sized planet with a nontransiting planets. We conclude by discussing possible origins roughly 1-d orbital period. We estimate that at least 24 of the 144 and implications of these results. systems we examined (≳17%) are members of this population. Accounting for detection efficiency, such planetary systems occur Comparison of Singles and Multis with a frequency similar to the hot Jupiters. We select our sample of planet candidates from the Q1–Q17 DR24 Kepler planet candidate catalog (16). This is the first such exoplanets | Kepler | planetary systems catalog to have robotically and uniformly evaluated all planetary signals detected by the Kepler pipeline. In this catalog, a wide odern surveys of exoplanets have produced a variety of range of false positives are identified, including instrumental ar- Mplanetary systems with properties that are often quite distinct tifacts, spotty stars, pulsating stars, eclipsing binaries, and con- from the Solar System (1). The architectures of these systems, the tamination from variable stars due to crowding, stray light, and orbits and masses of the planets and how those quantities relate to detector effects. This false positive identification is based solely on each other, indicate potential differences in their formation and Kepler data; i.e., no ground-based follow-up observations are used. evolutionary histories (2–6). These histories, in turn, give insights We construct our sample starting with the 4,293 planet candidates, into the various processes at work in the formation and sub- plus 9 confirmed planets that were misclassified as false positives sequent dynamical evolution of the system. Identifying different (ref. 16, section 5.2.5), in the Q1–Q17 DR24 catalog. The com- planet populations and the occurrence rates of those popula- pleteness of this catalog is investigated in detail in refs. 16 and 17. ASTRONOMY tions are, therefore, key ingredients to generalizing our planet Beyond the vetting done in producing the catalog, each candi- formation models. Hot Jupiters, for example, are a distinct date has been analyzed using the VESPA (Validation of Exoplanet population of planets with histories that differ from both the Signals using a Probabilistic Algorithm) code (18) to determine the Solar System and most of the planetary systems discovered to probability that the transit-like signal is actually a false positive date (7–10). caused by an undetected eclipsing binary star. These scenarios can Several studies of the architectures of planetary systems dis- include such cases as an eclipsing binary that has a secondary covered by NASA’s Kepler mission have noted differences between eclipse depth below the noise level, or one that has nearly identical the single-planet systems and the multiplanet systems (2, 11–13). eclipse depths and is detected at half the orbital period. The dis- For example, multiplanet systems rarely contain hot Jupiters with tribution of the total probability that the planet candidates are nearby planetary companions (9, 10)—thus far, WASP-47 is the among the considered false positive scenarios is shown in Fig. 1. only exception to this rule (14). Studies comparing the relative frequencies of systems with two, three, and higher multiplicity Significance show that planetary systems typically have multiple planets whose orbits are mutually inclined by a few degrees (2, 12, 15). However, Characterizing the variety of planets and planetary systems these models also indicate an excess of observed single-planet orbiting distant stars (exoplanets) is a key ingredient to im- systems when mutual inclinations are modeled by simple distri- proving our understanding of the Solar System and of planet butions [e.g., a Rayleigh distribution (2, 12, 13, 15)]. Although formation in general. One important observable property of a this discrepancy can be mitigated, to an extent, with more so- planetary system is its architecture—the sizes and orbital pe- phisticated, single-parameter models (2), additional investigations riods of the planets in a system and how they are related to comparing single-planet and multiplanet systems are warranted each other. From a statistical analysis of the planet candidate as a means to identify and characterize the source of the possible catalog from NASA’s Kepler mission, we identify a population excess of single-planet systems and to uncover populations of of planetary systems characterized by a unique system architec- planets with unique system architectures. ture. Differences in system architecture indicate different paths in Here we investigate differences between the properties of the the formation or dynamical history of a planetary system—giving singles and multis (i.e., single-planet and multi-planet systems) clues to the physical conditions or processes that drive systems given in the most recent Kepler planet candidate catalog in an along those paths. effort to identify planet populations that may be present among the singles that do not appear in similar numbers among the Author contributions: J.H.S. performed research; J.H.S. and J.L.C. analyzed data; and J.H.S. multis. Should such populations exist, they could contribute to and J.L.C. wrote the paper. the putative excess of single-planet systems. The distinguishing The authors declare no conflict of interest. characteristics of these systems may give insights into their ori- This article is a PNAS Direct Submission. gins and, hence, into when and how the evolutionary path of the 1To whom correspondence should be addressed. Email: [email protected]. www.pnas.org/cgi/doi/10.1073/pnas.1606658113 PNAS | October 25, 2016 | vol. 113 | no. 43 | 12023–12028 Downloaded by guest on September 27, 2021 larger tails (e.g., it has nonzero probability density in the region of the hot Jupiters), the distribution of multis must have a higher peak to be properly normalized. This peak then systematically overproduces planets in its vicinity, as is seen in Fig. 3. For the remainder of this work, we will focus on the fourth region of interest, the population of hot Earths on 1-d orbits. Source Budget for Hot Earths There are four possible sources of hot-Earth candidates. They may be (i) statistical false positives—photometric fluctuations that mimic a transit signal—(ii) astrophysical false positives such as background eclipsing binary stars, (iii) the innermost planets of standard Kepler multiplanet systems where the rest of the system is not detected, or (iv) planets from systems with a new and distinct architecture—such as single planets or planets that are widely separated from their neighbors. We calculate the budget for each Fig. 1. Total astrophysical false positive probabilities for all KOIs as de- of the first three sources to determine how many, if any, hot Earths termined by the VESPA software. Our sample of systems was restricted to may be members of this distinct population. The results of our those where the maximum, total false positive probability for any candidate study, which are discussed in more detail in subsequent sections, in the system was less than 0.2. are broken down in Table 1. Stellar and Statistical False Positives from Kepler Data. In the planet We obtain the VESPA false positives probabilities from the NASA candidate catalog, there are 144 hot-Earth planet candidates with Exoplanet Archive, and remove any candidate system (including singles) either that was not vetted using VESPA or where the total false positive probability is greater than 0.2 for the worst-case candidate within the system. Our resulting sample includes 3,063 candidates in 2,373 systems—1,890 in single systems and 1,173 candidates in 483 multiplanet systems. Fig. 2 shows a kernel density estimation (KDE) of the distri- bution of planet size and orbital period for the single-planet and multiplanet systems. If the observed single-planet systems are actually multiplanet systems where only one planet happens to transit, and if we assume that the detection efficiency is similar for both groups, then we should be able to reconstruct the size/period distribution of singles by randomly drawing samples from the multis. Regions where the sample multis are unable to consistently reproduce the observed frequency of singles merit further study, as they may indicate the presence of distinct planet populations. We ran 100,000 realizations of a Monte Carlo simulation where 1,890 random draws from the KDE for multis are com- pared with the observed singles in logarithmically uniform bins in planet size and orbital period. The results of this simulation are shown in Fig. 3. Bins with black circles and disks indicate where less than 2.5 and 0.5%, respectively, of the realizations repro- duce the singles.