Astrophysical False Positives Research Articles

NotPlaNET: Removing False Positives from Planet Hunters TESS with Machine Learning

Differentiating between real transit events and false-positive signals in photometric time-series data is a bottleneck in the identification of transiting exoplanets, particularly long-period planets. This differentiation typically requires visual inspection of a large number of transit-like signals to rule out instrumental and astrophysical false positives that mimic planetary transit signals. We build a one-dimensional convolutional neural network (CNN) to separate eclipsing binaries and other false positives from potential planet candidates, reducing the number of light curves that require human vetting. Our CNN is trained using the TESS light curves that were identified by Planet Hunters citizen scientists as likely containing a transit. We also include the background flux and centroid information. The light curves are visually inspected and labeled by project scientists and are minimally preprocessed, with only normalization and data augmentation taking place before training. The median percentage of contaminants flagged across the test sectors is 18% with a maximum of 37% and a minimum of 10%. Our model keeps 100% of the planets for 16 of the 18 test sectors, while incorrectly flagging one planet candidate (0.3%) for one sector and two (0.6%) for the remaining sector. Our method shows potential to reduce the number of light curves requiring manual vetting by up to a third with minimal misclassification of planet candidates.

Population study of astrophysical false positive detections in the southern plato field

ABSTRACT For the upcoming PLAnetary Transits and Oscillation of stars (PLATO) satellite mission, a large number of target stars are required to yield a statistically significant number of planet transits. Locating the centres of the long duration observational phase (LOP) fields closer to the Galactic plane will increase the target star numbers but also the astrophysical false positives (FPs) from blended eclipsing binary systems. We utilize the Binary Stellar Evolution and Population Synthesis code, to create a complete synthetic stellar and planetary population for the proposed southern LOP field (LOPS0), as well as for a representative portion of the northern LOP field (LOPN-sub). For LOPS0, we find an overall low FP rate for planets smaller than Neptunes. The FP rate generally shows little variation with Galactic longitude (l), and a modest increase with decreasing Galactic latitude (|b|). The location of the LOPS field centre within the current allowed region is not strongly constrained by FPs. Analysis of LOPN-sub suggests a markedly increased number of FPs across the full range of planet radii at low |b| resulting in approximately twice the percentage of FP detection rate in the LOPN-sub compared to the corresponding southern field segment in the planet radius range −0.2 < log (R/R⊕) ≤ 0.4. However, only a few per cent of fully eclipsing FPs in LOPS0 in this radius range have periods between 180 and 1000 d so the vast majority of FPs are expected to be outside the period range of interest for PLATO.

The Discovery of a Planetary Companion Interior to Hot Jupiter WASP-132 b

Hot Jupiters are generally observed to lack close planetary companions, a trend that has been interpreted as evidence for high-eccentricity migration. We present the discovery and validation of WASP-132 c (TOI-822.02), a 1.85 ± 0.10 R ⊕ planet on a 1.01 day orbit interior to the hot Jupiter WASP-132 b. Transiting Exoplanet Survey Satellite and ground-based follow-up observations, in conjunction with vetting and validation analysis, enable us to rule out common astrophysical false positives and validate the observed transit signal produced by WASP-132 c as a planet. Running the validation tools vespa and TRICERATOPS on this signal yields false-positive probabilities of 9.02 × 10−5 and 0.0107, respectively. Analysis of archival CORALIE radial velocity data leads to a 3σ upper limit of 28.23 ms−1 on the amplitude of any 1.01 day signal, corresponding to a 3σ upper mass limit of 37.35 M ⊕. Dynamical simulations reveal that the system is stable within the 3σ uncertainties on the planetary and orbital parameters for timescales of ∼100 Myr. The existence of a planetary companion near the hot Jupiter WASP-132 b makes the giant planet’s formation and evolution via high-eccentricity migration highly unlikely. Being one of just a handful of nearby planetary companions to hot Jupiters, WASP-132 c carries with it significant implications for the formation of the system and hot Jupiters as a population.

The Discovery of a Planetary Companion Interior to Hot Jupiter WASP-132 b

Hot Jupiters are generally observed to lack close planetary companions, a trend that has been interpreted as evidence for high-eccentricity migration. We present the discovery and validation of WASP-132 c (TOI-822.02), a 1.85 $\pm$ 0.10 $R_{\oplus}$ planet on a 1.01 day orbit interior to the hot Jupiter WASP-132 b. Transiting Exoplanet Survey Satellite (TESS) and ground-based follow-up observations, in conjunction with vetting and validation analysis, enable us to rule out common astrophysical false positives and validate the observed transit signal produced by WASP-132 c as a planet. Running the validation tools \texttt{vespa} and \texttt{triceratops} on this signal yield false positive probabilities of $9.02 \times 10^{-5}$ and 0.0107, respectively. Analysis of archival CORALIE radial velocity data leads to a 3$\sigma$ upper limit of 28.23 ms$^{-1}$ on the amplitude of any 1.01-day signal, corresponding to a 3$\sigma$ upper mass limit of 37.35 $M_{\oplus}$. Dynamical simulations reveal that the system is stable within the 3$\sigma$ uncertainties on planetary and orbital parameters for timescales of $\sim$100 Myr. The existence of a planetary companion near the hot Jupiter WASP-132 b makes the giant planet's formation and evolution via high-eccentricity migration highly unlikely. Being one of just a handful of nearby planetary companions to hot Jupiters, WASP-132 c carries with it significant implications for the formation of the system and hot Jupiters as a population.

Follow-up Photometry in Another Band Helps to Reduce Kepler’s False-positive Rates

Abstract The Kepler mission’s single-band photometry suffers from astrophysical false positives, most commonly of background eclipsing binaries (BEBs) and companion transiting planets (CTPs). Multicolor photometry can reveal the color-dependent depth feature of false positives and thus exclude them. In this work, we aim to estimate the fraction of false positives that cannot be classified by Kepler alone but can be identified from their color-dependent depth feature if a reference band (z, K s , and Transiting Exoplanet Survey Satellite (TESS)) is adopted in follow-up observation. We construct physics-based blend models to simulate multiband signals of false positives. Nearly 65%–95% of the BEBs and more than 80% of the CTPs that host a Jupiter-sized planet will show detectable depth variations if the reference band can achieve a Kepler-like precision. The K s band is most effective in eliminating BEBs exhibiting features of any depth, while the z and TESS bands are better for identifying giant candidates, and their identification rates are more sensitive to photometric precision. Given the radius distribution of planets transiting the secondary star in binary systems, we derive a formalism to calculate the overall identification rate for CTPs. By comparing the likelihood distribution of the double-band depth ratio for BEB and planet models, we calculate the false-positive probability (FPP) for typical Kepler candidates. Additionally, we show that the FPP calculation helps distinguish the planet candidate’s host star in an unresolved binary system. The framework of the analysis in this paper can be easily adapted to predict the multicolor photometric yield for other transit surveys, especially TESS.

Vetting of 384 TESS Objects of Interest with TRICERATOPS and Statistical Validation of 12 Planet Candidates

Abstract We present TRICERATOPS, a new Bayesian tool that can be used to vet and validate TESS Objects of Interest (TOIs). We test the tool on 68 TOIs that have been previously confirmed as planets or rejected as astrophysical false positives. By looking in the false-positive probability (FPP)−nearby false-positive probability (NFPP) plane, we define criteria that TOIs must meet to be classified as validated planets (FPP < 0.015 and NFPP < 10−3), likely planets (FPP < 0.5 and NFPP < 10−3), and likely nearby false positives (NFPP > 10−1). We apply this procedure on 384 unclassified TOIs and statistically validate 12, classify 125 as likely planets, and classify 52 as likely nearby false positives. Of the 12 statistically validated planets, 9 are newly validated. TRICERATOPS is currently the only TESS vetting and validation tool that models transits from nearby contaminant stars in addition to the target star. We therefore encourage use of this tool to prioritize follow-up observations that confirm bona fide planets and identify false positives originating from nearby stars.

Simulations Predicting the Ability of Multi-color Simultaneous Photometry to Distinguish TESS Candidate Exoplanets from False Positives

The Transiting Exoplanet Survey Satellite (TESS) is currently concluding its 2 yr primary science mission searching 85% of the sky for transiting exoplanets. TESS has already discovered well over one thousand TESS objects of interest (TOIs), but these candidate exoplanets must be distinguished from astrophysical false positives using other instruments or techniques. The 3-band Multi-color Simultaneous Camera for Studying Atmospheres of Transiting Planets (MuSCAT), as well as the 4-band MuSCAT2, can be used to validate TESS discoveries. Transits of exoplanets are achromatic when observed in multiple bandpasses, while transit depths for false positives often vary with wavelength. We created software tools to simulate MuSCAT/MuSCAT2 TESS follow-up observations and reveal which planet candidates can be efficiently distinguished from blended eclipsing binary (BEB) false positives using these two instruments, and which must be validated using other techniques. We applied our software code to the Barclay et al.predicted TESS discoveries, as well as to TOIs downloaded from the ExoFOP-TESS website. We estimate that MuSCAT (MuSCAT2 values in parentheses) will be able to use its multi-color capabilities to distinguish BEB false positives for ∼17% (∼18%) of all TESS discoveries, and ∼13% (∼15%) of Rpl < 4R⊕ discoveries. Our TOI analysis shows that MuSCAT (MuSCAT2) can distinguish BEB false positives for ∼55% (∼52%) of TOIs with transit depths greater than 0.001, for ∼64% (∼61%) of TOIs with transit depths greater than 0.002, and for ∼70% (∼68%) of TOIs with transit depth greater than 0.003. Our work shows that MuSCAT and MuSCAT2 can validate hundreds of Rpl < 4R⊕ candidate exoplanets, thus supporting the TESS mission in achieving its Level 1 Science Requirement of measuring the masses of 50 exoplanets smaller in size than Neptune. Our software tools will assist scientists as they prioritize and optimize follow-up observations of TOIs.

Comparing Approximate Bayesian Computation with the Poisson-Likelihood Method for Exoplanet Occurrence Rates

Abstract We present Kepler exoplanet occurrence rates inferred with approximate Bayesian computation (ABC). By using the same planet catalog, stellar sample, and characterization of completeness and reliability as Bryson et al. (2020), we are able to provide the first direct comparison of results from ABC to those derived with the popular Poisson-likelihood method. For planets with orbital periods between 50 and 400 days and radii between 0.75 and 2.5 R ⊕, we find an integrated occurrence rate F 0 = 0.596 − 0.099 + 0.092 planets per GK dwarf star. After correcting for reliability against astrophysical false positives and false alarms, we find F 0 = 0.421 − 0.072 + 0.086 . Our findings agree within 1σ of Bryson et al. (2020), indicating that the results are robust and not method-dependent.

The Independent Discovery of Planet Candidates around Low-mass Stars and Astrophysical False Positives from the First Two TESS Sectors

Continuous data releases throughout the TESS primary mission will provide unique opportunities for the exoplanet community at large to contribute to maximizing TESS's scientific return via the discovery and validation of transiting planets. This paper introduces our independent detection pipeline of periodic transit events along with the results of its inaugural application to the recently released 2 minute light curves of low mass stars from the first two TESS sectors. The stellar parameters within our sample are refined using precise parallax measurements from the GAIA DR2 which reduces the number of low mass stars in our sample relative to those listed in the TESS Input Catalog. In lieu of the follow-up observations required to confirm or refute the planetary nature of transit-like signals, a validation of transit-like events flagged by our pipeline is performed statistically. The resulting vetted catalog contains seven probable blended eclipsing binaries, eight known TOIs, plus eight new planet candidates smaller than 4 Earth radii. This work demonstrates the ability of our pipeline to detect sub-Neptune-sized planet candidates which to-date, represent some of the most attractive targets for future atmospheric characterization via transmission or thermal emission spectroscopy and for radial velocity efforts aimed at the completion of the TESS level one requirement to deliver 50 planets smaller than 4 Earth radii with measured masses.

The Palomar Transient Factory Sky2Night programme

Abstract We present results of the Sky2Night project: a systematic, unbiased search for fast optical transients with the Palomar Transient Factory. We have observed 407deg2 in R-band for eight nights at a cadence of 2 h. During the entire duration of the project, the 4.2 m William Herschel Telescope on La Palma was dedicated to obtaining identification spectra for the detected transients. During the search, we found 12 supernovae, 10 outbursting cataclysmic variables, nine flaring M-stars, three flaring active galactic nuclei, and no extragalactic fast optical transients. Using this systematic survey for transients, we have calculated robust observed rates for the detected types of transients, and upper limits of the rate of extragalactic fast optical transients of $\mathcal {R}\lt 37\times 10^{-4}$deg−2 d−1 and $\mathcal {R}\lt 9.3\times 10^{-4}$deg−2 d−1 for time-scales of 4 h and 1 d and a limiting magnitude of R ≈ 19.7. We use the results of this project to determine what kind of and how many astrophysical false positives we can expect when following up gravitational wave detections in search for kilonovae.

The KELT Follow-up Network and Transit False-positive Catalog: Pre-vetted False Positives for TESS

Abstract The Kilodegree Extremely Little Telescope (KELT) project has been conducting a photometric survey of transiting planets orbiting bright stars for over 10 years. The KELT images have a pixel scale of ∼23″ pixel−1—very similar to that of NASA’s Transiting Exoplanet Survey Satellite (TESS)—as well as a large point-spread function, and the KELT reduction pipeline uses a weighted photometric aperture with radius 3′. At this angular scale, multiple stars are typically blended in the photometric apertures. In order to identify false positives and confirm transiting exoplanets, we have assembled a follow-up network (KELT-FUN) to conduct imaging with spatial resolution, cadence, and photometric precision higher than the KELT telescopes, as well as spectroscopic observations of the candidate host stars. The KELT-FUN team has followed-up over 1600 planet candidates since 2011, resulting in more than 20 planet discoveries. Excluding ∼450 false alarms of non-astrophysical origin (i.e., instrumental noise or systematics), we present an all-sky catalog of the 1128 bright stars (6 &lt; V &lt; 13) that show transit-like features in the KELT light curves, but which were subsequently determined to be astrophysical false positives (FPs) after photometric and/or spectroscopic follow-up observations. The KELT-FUN team continues to pursue KELT and other planet candidates and will eventually follow up certain classes of TESS candidates. The KELT FP catalog will help minimize the duplication of follow-up observations by current and future transit surveys such as TESS.

Kepler-503b: An Object at the Hydrogen Burning Mass Limit Orbiting a Subgiant Star

Abstract Using spectroscopic radial velocities with the Apache Point Observatory Galaxy Evolution Experiment (APOGEE) instrument and Gaia distance estimates, we demonstrate that Kepler-503b, currently considered a validated Kepler planet, is in fact a brown-dwarf/low-mass star in a nearly circular 7.2-day orbit around a subgiant star. Using a mass estimate for the primary star derived from stellar models, we derive a companion mass and radius of 0.075 ± 0.003 M ⊙ (78.6 ± 3.1 M Jup) and ( R Jup), respectively. Assuming that the system is coeval, the evolutionary state of the primary indicates the age is ∼6.7 Gyr. Kepler-503b sits right at the hydrogen-burning mass limit, straddling the boundary between brown dwarfs and very low-mass stars. More precise radial velocities and secondary eclipse spectroscopy with the James Webb Space Telescope (JWST) will provide improved measurements of the physical parameters and age of this important system to better constrain and understand the physics of these objects and their spectra. This system emphasizes the value of radial velocity observations to distinguish a genuine planet from astrophysical false positives, and is the first result from the Sloan Digital Sky Survey (SDSS)-IV monitoring of Kepler planet candidates with the multi-object APOGEE instrument.

Kepler Data Validation I—Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for ∼200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018.

Improving the Accuracy of Planet Occurrence Rates from Kepler Using Approximate Bayesian Computation

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 (R p &lt; 1.25 R ⊕) at larger orbital periods (P &gt; 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 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.

Transit shapes and self-organizing maps as a tool for ranking planetary candidates: application toKeplerandK2

A crucial step in planet hunting surveys is to select the best candidates for follow up observations, given limited telescope resources. This is often performed by human `eyeballing', a time consuming and statistically awkward process. Here we present a new, fast machine learning technique to separate true planet signals from astrophysical false positives. We use Self Organising Maps (SOMs) to study the transit shapes of \emph{Kepler} and \emph{K2} known and candidate planets. We find that SOMs are capable of distinguishing known planets from known false positives with a success rate of 87.0\%, using the transit shape alone. Furthermore, they do not require any candidates to be dispositioned prior to use, meaning that they can be used early in a mission's lifetime. A method for classifying candidates using a SOM is developed, and applied to previously unclassified members of the \emph{Kepler} KOI list as well as candidates from the \emph{K2} mission. The method is extremely fast, taking minutes to run the entire KOI list on a typical laptop. We make \texttt{Python} code for performing classifications publicly available, using either new SOMs or those created in this work. The SOM technique represents a novel method for ranking planetary candidate lists, and can be used both alone or as part of a larger autovetting code.

First results of the Kourovka Planet Search: discovery of transiting exoplanet candidates in the first three target fields

We present the first results of our search for transiting exoplanet candidates as part of the Kourovka Planet Search (KPS) project. The primary objective of the project is to search for new hot Jupiters which transit their host stars, mainly in the Galactic plane, in the $R_c$ magnitude range of 11 to 14 mag. Our observations were performed with the telescope of the MASTER robotic network, installed at the Kourovka astronomical observatory of the Ural Federal University (Russia), and the Rowe-Ackermann Schmidt Astrograph, installed at the private Acton Sky Portal Observatory (USA). As test observations, we observed three celestial fields of size $2\times2$ deg$^2$ during the period from 2012 to 2015. As a result, we discovered four transiting exoplanet candidates among the 39000 stars of the input catalogue. In this paper, we provide the description of the project and analyse additional photometric, spectral, and speckle interferometric observations of the discovered transiting exoplanet candidates. Three of the four transiting exoplanet candidates are most likely astrophysical false positives, while the nature of the fourth (most promising) candidate remains to be ascertained. Also, we propose an alternative observing strategy that could increase the project's exoplanet haul.

FALSE POSITIVE PROBABILITIES FOR ALL KEPLER OBJECTS OF INTEREST: 1284 NEWLY VALIDATED PLANETS AND 428 LIKELY FALSE POSITIVES

ABSTRACT We present astrophysical false positive probability calculations for every Kepler Object of Interest (KOI)—the first large-scale demonstration of a fully automated transiting planet validation procedure. Out of 7056 KOIs, we determine that 1935 have probabilities &lt;1% of being astrophysical false positives, and thus may be considered validated planets. Of these, 1284 have not yet been validated or confirmed by other methods. In addition, we identify 428 KOIs that are likely to be false positives, but have not yet been identified as such, though some of these may be a result of unidentified transit timing variations. A side product of these calculations is full stellar property posterior samplings for every host star, modeled as single, binary, and triple systems. These calculations use vespa, a publicly available Python package that is able to be easily applied to any transiting exoplanet candidate.

THE TRANSITING EXOPLANET SURVEY SATELLITE: SIMULATIONS OF PLANET DETECTIONS AND ASTROPHYSICAL FALSE POSITIVES

The Transiting Exoplanet Survey Satellite (TESS) is a NASA-sponsored Explorer mission that will perform a wide-field survey for planets that transit bright host stars. Here, we predict the properties of the transiting planets that TESS will detect along with the eclipsing binary stars that produce false-positive photometric signals. The predictions are based on Monte Carlo simulations of the nearby population of stars, occurrence rates of planets derived from Kepler, and models for the photometric performance and sky coverage of the TESS cameras. We expect that TESS will find approximately 1700 transiting planets from 200,000 pre-selected target stars. This includes 556 planets smaller than twice the size of Earth, of which 419 are hosted by M dwarf stars and 137 are hosted by FGK dwarfs. Approximately 130 of the $R < 2~R_\oplus$ planets will have host stars brighter than K = 9. Approximately 48 of the planets with $R < 2~R_\oplus$ lie within or near the habitable zone ($0.2 < S/S_\oplus < 2$), and between 2-7 such planets have host stars brighter than K = 9. We also expect approximately 1100 detections of planets with radii 2-4 R_Earth, and 67 planets larger than $4~R_\oplus$. Additional planets larger than $2~R_\oplus$ can be detected around stars that are not among the pre-selected target stars, because TESS will also deliver full-frame images at a 30-minute cadence. The planet detections are accompanied by over one thousand astrophysical false positives. We discuss how TESS data and ground-based observations can be used to distinguish the false positives from genuine planets. We also discuss the prospects for follow-up observations to measure the masses and atmospheres of the TESS planets.

ADAPTIVE OPTICS IMAGES. III. 87 KEPLER OBJECTS OF INTEREST

The Kepler mission has revolutionized our understanding of exoplanets, but some of the planet candidates identified by Kepler may actually be astrophysical false positives or planets whose transit depths are diluted by the presence of another star. Adaptive optics images made with ARIES at the MMT of 87 Kepler Objects of Interest place limits on the presence of fainter stars in or near the Kepler aperture. We detected visual companions within 1" for five stars, between 1" and 2" for seven stars, and between 2" and 4" for 15 stars. For those systems, we estimate the brightness of companion stars in the Kepler bandpass and provide approximate corrections to the radii of associated planet candidates due to the extra light in the aperture. For all stars observed, we report detection limits on the presence of nearby stars. ARIES is typically sensitive to stars approximately 5.3 Ks magnitudes fainter than the target star within 1" and approximately 5.7 Ks magnitudes fainter within 2", but can detect stars as faint as delta Ks = 7.5 under ideal conditions.

The contribution of secondary eclipses as astrophysical false positives to exoplanet transit surveys

We investigate in this paper the astrophysical false-positive configuration in exoplanet-transit surveys that involves eclipsing binaries and giant planets which present only a secondary eclipse, as seen from the Earth. To test how an eclipsing binary configuration can mimic a planetary transit, we generate synthetic light curve of three examples of secondary-only eclipsing binary systems that we fit with a circular planetary model. Then, to evaluate its occurrence we model a population of binaries in double and triple system based on binary statistics and occurrence. We find that 0.061% +/- 0.017% of main-sequence binary stars are secondary-only eclipsing binaries mimicking a planetary transit candidate down to the size of the Earth. We then evaluate the occurrence that an occulting-only giant planet can mimic an Earth-like planet or even smaller planet. We find that 0.009% +/- 0.002% of stars harbor a giant planet that present only the secondary transit. Occulting-only giant planets mimic planets smaller than the Earth that are in the scope of space missions like Kepler and PLATO. We estimate that up to 43.1 +/- 5.6 Kepler Objects of Interest can be mimicked by this new configuration of false positives, re-evaluating the global false-positive rate of the Kepler mission from 9.4% +/- 0.9% to 11.3% +/- 1.1%. We note however that this new false-positive scenario occurs at relatively long orbital period compared with the median period of Kepler candidates.