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Register a new userSimulations Predicting the Ability of Multi-Color Simultaneous Photometry to Distinguish TESS Candidate Exoplanets from False Positives
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The Transiting Exoplanet Survey Satellite (TESS) is currently concluding its 2-year 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. (2018) 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 $sim$17% ($sim$18%) of all TESS discoveries, and $sim$13% ($sim$15%) of $R_{rm pl} < 4R_oplus$ discoveries. Our TOI analysis shows that MuSCAT (MuSCAT2) can distinguish BEB false positives for $sim$55% ($sim$52%) of TOIs with transit depths greater than 0.001, for $sim$64% ($sim$61%) of TOIs with transit depths greater than 0.002, and for $sim$70% ($sim$68%) of TOIs with transit depth greater than 0.003. Our work shows that MuSCAT and MuSCAT2 can validate hundreds of $R_{rm pl} < 4R_oplus$ candidate exoplanets, thus supporting the TESS mission in achieving its Level 1 Science Requirement.
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The radial velocity technique is currently used to classify transiting objects. While capable of identifying grazing binary eclipses, this technique cannot reliably identify blends, a chance overlap of a faint background eclipsing binary with an ordinary foreground star. Blends generally have no observable radial velocity shifts, as the foreground star is brighter by several magnitudes and therefore dominates the spectrum, but their combined light can produce events that closely resemble those produced by transiting exoplanets. The radial velocity technique takes advantage of the mass difference between planets and stars to classify exoplanet candidates. However, the existence of blends renders this difference an unreliable discriminator. Another difference must therefore be utilized for this classification -- the physical size of the transiting body. Due to the dependence of limb darkening on color, planets and stars produce subtly different transit shapes. These differences can be relatively weak, little more than 1/10th the transit depth. However, the presence of even small color differences between the individual components of the blend increases this difference. This paper will show that this color difference is capable of discriminating between exoplanets and blends reliably, theoretically capable of classifying even terrestrial-class transits, unlike the radial velocity technique.
The Transiting Exoplanet Survey Satellite (TESS) is the first high-precision full-sky photometry survey in space. We present light curves from a magnitude limited set of stars and other stationary luminous objects from the TESS Full Frame Images, as reduced by the MIT Quick Look Pipeline (QLP). Our light curves cover the full two-year TESS Primary Mission and include $sim$ 14,770,000 and $sim$ 9,600,000 individual light curve segments in the Southern and Northern ecliptic hemispheres, respectively. We describe the photometry and detrending techniques we used to create the light curves, and compare the noise properties with theoretical expectations. All of the QLP light curves are available at MAST as a High Level Science Product via doi.org/10.17909/t9-r086-e880 (https://archive.stsci.edu/hlsp/qlp). This is the largest collection of TESS photometry available to the public to date.
We present the results from the first two years of the Planet Hunters TESS citizen science project, which identifies planet candidates in the TESS data by engaging members of the general public. Over 22,000 citizen scientists from around the world visually inspected the first 26 Sectors of TESS data in order to help identify transit-like signals. We use a clustering algorithm to combine these classifications into a ranked list of events for each sector, the top 500 of which are then visually vetted by the science team. We assess the detection efficiency of this methodology by comparing our results to the list of TESS Objects of Interest (TOIs) and show that we recover 85 % of the TOIs with radii greater than 4 Earth radii and 51 % of those with radii between 3 and 4 Earth radii. Additionally, we present our 90 most promising planet candidates that had not previously been identified by other teams, 73 of which exhibit only a single transit event in the TESS light curve, and outline our efforts to follow these candidates up using ground-based observatories. Finally, we present noteworthy stellar systems that were identified through the Planet Hunters TESS project.
The Kilodegree Extremely Little Telescope (KELT) project has been conducting a photometric survey for transiting planets orbiting bright stars for over ten years. The KELT images have a pixel scale of ~23/pixel---very similar to that of NASAs 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 higher spatial resolution, cadence, and photometric precision than the KELT telescopes, as well as spectroscopic observations of the candidate host stars. The KELT-FUN team has followed-up over 1,600 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 1,128 bright stars (6<V<10) 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.
The benchmark exoplanet GJ 1214b is one of the best studied transiting planets in the transition zone between rocky Earth-sized planets and gas or ice giants. This class of super-Earth/mini-Neptune planets is unknown in our Solar System, yet is one of the most frequently detected classes of exoplanets. Understanding the transition from rocky to gaseous planets is a crucial step in the exploration of extrasolar planetary systems, in particular with regard to the potential habitability of this class of planets. GJ 1214b has already been studied in detail from various platforms at many different wavelengths. Our airborne observations with SOFIA add information in the Paschen-alpha cont. 1.9 micron infrared wavelength band, which is not accessible by any other current ground- or space-based instrument due to telluric absorption or limited spectral coverage. We used FLIPO and FPI+ on SOFIA to comprehensively analyse the transmission signal of the possible water-world GJ 1214b through photometric observations during transit in three optical and one infrared channels. We present four simultaneous light curves and corresponding transit depths in three optical and one infrared channel, which we compare to previous observations and state-of-the-art synthetic atmospheric models of GJ 1214b. The final precision in transit depth is between 1.5 and 2.5 times the theoretical photon noise limit, not sensitive enough to constrain the theoretical models any better than previous observations. This is the first exoplanet observation with SOFIA that uses its full set of instruments available to exoplanet spectrophotometry. Therefore we use these results to evaluate SOFIAs potential in this field and suggest future improvements.
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