Vetting of 384 TESS Objects of Interest with TRICERATOPS and Statistical Validation of 12 Planet Candidates
Steven Giacalone, Courtney D. Dressing, Eric L. N. Jensen, Karen A. Collins, George R. Ricker, Roland Vanderspek, S. Seager, Joshua N. Winn, Jon M. Jenkins, Tho… 展开作者
Steven Giacalone, Courtney D. Dressing, Eric L. N. Jensen, Karen A. Collins, George R. Ricker, Roland Vanderspek, S. Seager, Joshua N. Winn, Jon M. Jenkins, Thomas Barclay, Khalid Barkaoui, Charles Cadieux, David Charbonneau, Kevin I. Collins, Dennis M. Conti, Rene Doyon, Phil Evans, Mourad Ghachoui, Michael Gillon, Natalia M. Guerrero, Rhodes Hart, Emmanuel Jehin, John F. Kielkopf, Brian McLean, Felipe Murgas, Enric Palle, Hannu Parviainen, Francisco J. Pozuelos, Howard M. Relles, Avi Shporer, Quentin Socia, Chris Stockdale, Thiam-Guan Tan, Guillermo Torres, Joseph D. Twicken, William C. Waalkes, Ian A. Waite
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.
Vetting Ambiguous Planetary Candidates (APC) in TESS Data: Insights from LATTE Package and Detection of Nine Potential Exoplanet Candidates
Pakistan Space and Upper Atmosphere Research Commission (SUPARCO)（巴基斯坦空间与高层大气研究委员会）；Institute of Frontier and Interdisciplinary Science, Shandong University（山东大学前沿交叉科学研究院）
We present the detection of 1,617 new transiting planet candidates, identified in the Transiting Exoplanet Survey Satellite (TESS) full-frame images (FFIs) observed during the Primary Mission (Sectors 1 - 26). These candidates were initially detected by the Quick-Look Pipeline (QLP), which extracts FFI lightcurves for and searches all stars brighter than TESS magnitude T = 13.5 mag in each sector. However, QLP heavily relies on manual inspection for the identification of planet candidates, limiting vetting efforts to planet-hosting stars brighter than T = 10.5 mag and leaving millions of poten…
NASA's Transiting Exoplanet Survey Satellite (TESS) presents us with an unprecedented volume of space-based photometric observations that must be analyzed in an efficient and unbiased manner. With at least $\sim1,000,000$ new light curves generated every month from full frame images alone, automated planet candidate identification has become an attractive alternative to human vetting. Here we present a deep learning model capable of performing triage and vetting on TESS candidates. Our model is modified from an existing neural network designed to automatically classify Kepler candidates, and i…
We examined the period distribution of transit-like signatures uncovered in a Box-Least Squares transit search of TESS light curves, and show significant pileups at periods related to instrumental and astrophysical noise sources. Signatures uncovered in a search of inverted light curves feature similar structures in the period distribution. Automated vetting methods will need to remove these excess detections, and light curve inversion appears to be a suitable method for simulating false alarms and designing new vetting metrics.
The Transiting Exoplanet Survey Satellite (TESS) has detected thousands of exoplanet candidates since 2018, most of which have yet to be confirmed. A key step in the confirmation process of these candidates is ruling out false positives through vetting. Vetting also eases the burden on follow-up observations, provides input for demographics studies, and facilitates training machine learning algorithms. Here we present the TESS Triple-9 (TT9) catalog -- a uniformly-vetted catalog containing dispositions for 999 exoplanet candidates listed on ExoFOP-TESS, known as TESS Objects of Interest (TOIs)…
ExoNet: Calibrated Multimodal Deep Learning for TESS Exoplanet Candidate Vetting using Phase-Folded Light Curves, Stellar Parameters, and Multi-Head Attention
We statistically validated a sample of hot Neptune candidates applying a two-step vetting technique using DAVE and TRICERATOPS. We performed a systematic validation of 250 transit-like events in the Transiting Exoplanet Survey Satellite (TESS) archive in the parameter region defined by $P\leq 4$ d and $3R_\oplus\leq R\leq 5R_\oplus$. Through our analysis, we identified 18 hot Neptune-sized candidates, with a false positive probability $<50\%$. Nine of these planet candidates still need to be confirmed. For each of the nine targets we retrieved the stellar parameters using ARIADNE and derived c…
We have adapted the algorithmic tools developed during the Kepler mission to vet the quality of transit-like signals for use on the K2 mission data. Using the four sets of publicly-available lightcurves on MAST, we produced a uniformly-vetted catalog of 772 transiting planet candidates from K2 as listed at the NASA Exoplanet archive in the K2 Table of Candidates. Our analysis marks 676 of these as planet candidates and 96 as false positives. All confirmed planets pass our vetting tests. 60 of our false positives are new identifications -- effectively doubling the overall number of astrophysica…
ExoMiner++: Enhanced Transit Classification and a New Vetting Catalog for 2-Minute TESS Data
KBR Inc.（KBR公司）；NASA Ames Research Center (NASA ARC)（NASA艾姆斯研究中心）；The SETI Institute（SETI研究所）；NASA Goddard Space Flight Center（NASA戈达德太空飞行中心）；University of California, Berkeley（加州大学伯克利分校）；Yale University（耶鲁大学）；Pacific Northwest National Laboratory（太平洋西北国家实验室）；Center for Astrophysics | Harvard & Smithsonian（哈佛-史密森天体物理中心）；Massachusetts Institute of Technology（麻省理工学院）；The Ohio State University（俄亥俄州立大学）；Ural Federal University（乌拉尔联邦大学）；Nicolaus Copernicus University（尼古拉斯·哥白尼大学）；University of Birmingham（伯明翰大学）；Brigham Young University（杨百翰大学）；Hazelwood Observatory（黑泽尔伍德天文台）；Union College（联合学院）
Assessing the Impact of High-Resolution Imaging on Statistical Validation of TESS Planet Candidates
Holaxis；Department of Astronomy, California Institute of Technology（加州理工学院天文系）；NASA Exoplanet Science Institute, Caltech/IPAC（NASA系外行星科学研究所，加州理工学院/IPAC）；Department of Physics and Astronomy, University of Kansas（堪萨斯大学物理与天文学系）；Bay Area Environmental Research Institute（湾区环境研究所）；NASA Ames Research Center（NASA艾姆斯研究中心）；Department of Astronomy, The University of Texas at Austin（德克萨斯大学奥斯汀分校天文系）
COUNTESS I: A Uniformly Vetted Catalog of Known and New Transiting Exoplanets in the TESS Northern Continuous Viewing Zone
University of Florida（佛罗里达大学）；Penn State（宾夕法尼亚州立大学）；Center for Exoplanets and Habitable Worlds（系外行星与宜居世界中心）；Caltech/IPAC-NASA Exoplanet Science Institute（加州理工学院/IPAC-NASA 系外行星科学研究所）；California Institute of Technology（加州理工学院）
WATSON-Net: Vetting, Validation, and Analysis of Transits from Space Observations with Neural Networks
Dpto. Física Teórica y del Cosmos. Universidad de Granada（格拉纳达大学理论物理与宇宙学系）；AI Engineering, Avature, Spain（Avature人工智能工程）；CITIC-Research Center of Information and Communication Technologies, University of A Coruña（阿维拉大学信息与通信技术研究中心）；CIGUS CITIC - Department of Computer Science and Information Technologies, University of A Coruña（阿维拉大学CIGUS CITIC-计算机科学与信息科技系）
We exploit high quality photometry from the EVEREST pipeline to evaluate false-positive exoplanet candidates from the K2 mission. We compare the practical capabilities of EVEREST's pixel-level decorrelation scheme to the data analysis pipelines widely used at the time of these planet candidates' discovery. Removing stellar variability from the EVEREST-corrected light curves, we search for potential secondary eclipses. For each object exhibiting a secondary eclipse, we compare the implied brightness temperature of the planet candidate to its calculated equilibrium temperature. We thereby identi…
The Transiting Exoplanet Survey Satellite (TESS) mission is providing the scientific community with millions of light curves of stars spread across the whole sky. Since 2018 the telescope has detected thousands of planet candidates that need to be meticulously scrutinized before being considered amenable targets for follow-up programs. We present the second catalog of the Plant Patrol citizen science project containing 999 uniformly-vetted exoplanet candidates within the TESS ExoFOP archive. The catalog was produced by fully exploiting the power of the Citizen Science Planet Patrol project. We…
State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary…
Finding Circumbinary Planets: A Semi-Automated Transit Search of TESS Eclipsing Binaries
University of Warwick（华威大学）；Centre for Exoplanets and Habitability, University of Warwick（华威大学系外行星与宜居性中心）；School of Physics and Astronomy, University of Birmingham（伯明翰大学物理与天文学学院）
Catholic University of America（美国天主教大学）；Tel Aviv University（特拉维夫大学）；ThetaRay（ThetaRay公司）
A novel artificial intelligence (AI) technique that uses machine learning (ML) methodologies combines several algorithms, which were developed by ThetaRay, Inc., is applied to NASA's Transiting Exoplanets Survey Satellite (TESS) dataset to identify exoplanetary candidates. The AI/ML ThetaRay system is trained initially with Kepler exoplanetary data and validated with confirmed exoplanets before its application to TESS data. Existing and new features of the data, based on various observational parameters, are constructed and used in the AI/ML analysis by employing semi-supervised and unsupervis…
The Transiting Exoplanet Survey Satellite (TESS) is focusing on relatively bright stars and has found thousands of planet candidates. However, mainly because of the low spatial resolution of its cameras ($\approx$ 21 arcsec/pixel), TESS is expected to detect several false positives (FPs); hence, vetting needs to be done. Here, we present a follow-up program of TESS candidates orbiting solar-analogue stars that are in the all-sky PLATO input catalogue. Using Gaia photometry and astrometry we built an absolute colour-magnitude diagram and isolated solar-analogue candidates' hosts. We performed a…
NASA Goddard Space Flight Center（美国国家航空航天局戈达德太空飞行中心）；Universities Space Research Association（大学空间研究协会）；The Catholic University of America（美国天主教大学）；Universita di Napoli Federico II（那不勒斯费德里科二世大学）；Science Systems and Applications, Inc.（科学系统与应用公司）；University of Maryland, Baltimore County（马里兰大学巴尔的摩县分校）
The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ~75% of the sky throughout its two year primary mission, resulting in millions of TESS 30-minute cadence light curves to analyze in the search for transiting exoplanets. To search this vast data trove for transit signals, we aim to provide an approach that is both computationally efficient and produces highly performant predictions. This approach minimizes the required human search effort. We present a convolutional neural network, which we train to identify planetary transit signals and dismiss false positiv…
Department of Physics, University of Warwick（沃里克大学物理系）；Centre for Exoplanets and Habitability, University of Warwick（沃里克大学系外行星与宜居性中心）；Instituto de Ciencias Físicas (CONICET / ECyT-UNSAM)（物理科学研究所（CONICET / ECyT-UNSAM））；Gerencia de Tecnología de la información y de las Comunicaciones (GTIC), Subgerencia Vinculación y Desarrollo de Nuevas Tecnologías de la Información, DTE-CNEA. Centro Atómico Constituyentes（信息与通信技术管理局（GTIC），技术联络与发展新技术子部门，DTE-CNEA原子构成中心）；Instituto Tecnológico de Buenos Aires (ITBA)（布宜诺斯艾利斯技术研究所）
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 …
LinkedIn Corporation（领英公司）；California Institute of Technology（加州理工学院）；Saratoga High School（萨拉托加高中）；University of Southern California（南加州大学）
The Transiting Exoplanet Survey Satellite (TESS) has now been operational for a little over two years, covering the Northern and the Southern hemispheres once. The TESS team processes the downlinked data using the Science Processing Operations Center pipeline and Quick Look pipeline to generate alerts for follow-up. Combined with other efforts from the community, over two thousand planet candidates have been found of which tens have been confirmed as planets. We present our pipeline, Nigraha, that is complementary to these approaches. Nigraha uses a combination of transit finding, supervised m…
The Occurrence Rate of Planets Around Subgiant Stars from TESS Photometric Survey
Indian Institute of Science Education and Research Kolkata（印度科学教育研究所加尔各答分校）；Tata Institute of Fundamental Research（塔塔基础研究所）；Thüringer Landessternwarte Tautenburg（图林根州陶滕堡天文台）
Transiting exoplanets in multi-planet systems exhibit non-Keplerian orbits as a result of the gravitational influence from companions which can cause the times and durations of transits to vary. The amplitude and periodicity of the transit time variations (TTV) are characteristic of the perturbing planet's mass and orbit. The objects of interest (TOI) from the Transiting Exoplanet Survey Satellite (TESS) are analyzed in a uniform way to search for TTVs with sectors 1-3 of data. Due to the volume of targets in the TESS candidate list, artificial intelligence is used to expedite the search for p…
We present a study on the effect of undetected stellar companions on the derived planetary radii for the Kepler Objects of Interest (KOIs). The current production of the KOI list assumes that the each KOI is a single star. Not accounting for stellar multiplicity statistically biases the planets towards smaller radii. The bias towards smaller radii depends on the properties of the companion stars and whether the planets orbit the primary or the companion stars. Defining a planetary radius correction factor $X_R$, we find that if the KOIs are assumed to be single, then, {\it on average}, the pla…
We report on the discovery and validation of TOI 813b (TIC 55525572 b), a transiting exoplanet identified by citizen scientists in data from NASA's Transiting Exoplanet Survey Satellite (TESS) and the first planet discovered by the Planet Hunters TESS project. The host star is a bright (V = 10.3 mag) subgiant ($R_\star=1.94\,R_\odot$, $M_\star=1.32\,M_\odot$). It was observed almost continuously by TESS during its first year of operations, during which time four individual transit events were detected. The candidate passed all the standard light curve-based vetting checks, and ground-based fol…
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 …
We present the discovery and validation of a three-planet system orbiting the nearby (31.1 pc) M2 dwarf star TOI-700 (TIC 150428135). TOI-700 lies in the TESS continuous viewing zone in the Southern Ecliptic Hemisphere; observations spanning 11 sectors reveal three planets with radii ranging from 1 R$_\oplus$ to 2.6 R$_\oplus$ and orbital periods ranging from 9.98 to 37.43 days. Ground-based follow-up combined with diagnostic vetting and validation tests enable us to rule out common astrophysical false-positive scenarios and validate the system of planets. The outermost planet, TOI-700 d, has …
The James Webb Space Telescope (JWST) will be able to probe the atmospheres and surface properties of hot, terrestrial planets via emission spectroscopy. We identify 18 potentially terrestrial planet candidates detected by the Transiting Exoplanet Survey Satellite (TESS) that would make ideal targets for these observations. These planet candidates cover a broad range of planet radii ($R_{\rm p} \sim 0.6 - 2.0 R_\oplus$) and orbit stars of various magnitudes ($K_s = 5.78 - 10.78$, $V = 8.4 - 15.69$) and effective temperatures ($T_{\rm eff }\sim 3000 - 6000$ K). We use ground-based observations …
Hidden Gems in TESS: sherlock finds two new rocky planets around nearby M dwarfs
University of Birmingham（伯明翰大学）；Université de Liège（列日大学）；Universidad de Granada（格拉纳达大学）；Avature；Instituto de Astrofísica de Andalucía (IAA-CSIC)（安达卢西亚天体物理研究所）；Instituto de Astrofisica de Canarias (IAC)（加那利天体物理研究所）；Massachusetts Institute of Technology（麻省理工学院）；Universidad de Tarapacá（塔拉帕卡大学）；Observatoire de Genève, Département d’Astronomie, Université de Genève（日内瓦大学天文学系天文台）；Univ. Grenoble Alpes, CNRS, IPAG（格勒诺布尔阿尔卑斯大学）；NASA Ames Research Center（美国国家航空航天局艾姆斯研究中心）
DART-Vetter: A Deep LeARning Tool for automatic triage of exoplanet candidates
Department of Science and Technology, Parthenope University of Naples（科学与技术系，那不勒斯帕尔泰诺大学）；INAF, Osservatorio Astronomico di Capodimonte（国家天文台，卡波迪蒙特天文台）；European Southern Observatory（欧洲南方天文台）；NASA Goddard Space Flight Center（美国国家航空航天局戈达德空间飞行中心）
TOI-4616 b: a benchmark Earth-sized planet transiting a nearby M4 dwarf
University of Bern（伯尔尼大学）；Universidad Nacional Autónoma de México, Instituto de Astronomía（墨西哥国立自治大学天文研究所）；Université de Liége（列日大学）；University of Birmingham（伯明翰大学）；Instituto de Astrofísica de Andalucía (IAA-CSIC)（安达卢西亚天体物理学研究所（CSIC））；Massachusetts Institute of Technology（麻省理工学院）；Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology（麻省理工学院卡弗里天体物理学与空间研究研究所）；Cavendish Laboratory（卡文迪许实验室）；ETH Zürich（苏黎世联邦理工学院）
We report the Transiting Exoplanet Survey Satellite (TESS) discovery of three terrestrial-sized planets transiting L 98-59 (TOI-175, TIC 307210830) -- a bright M dwarf at a distance of 10.6 pc. Using the Gaia-measured distance and broad-band photometry we find that the host star is an M3 dwarf. Combined with the TESS transits from three sectors, the corresponding stellar parameters yield planet radii ranging from 0.8REarth to 1.6REarth. All three planets have short orbital periods, ranging from 2.25 to 7.45 days with the outer pair just wide of a 2:1 period resonance. Diagnostic tests produced…
Given that Campaign 16 of the K2 mission is one of just two K2 campaigns observed so far in "forward-facing" mode, which enables immediate follow-up observations from the ground, we present a catalog of interesting targets identified through photometry alone. Our catalog includes 30 high-quality planet candidates (showing no signs of being non-planetary in nature), 48 more ambiguous events that may be either planets or false positives, 164 eclipsing binaries, and 231 other regularly periodic variable sources. We have released light curves for all targets in C16, and have also released system p…
University of Warwick（华威大学）；The Alan Turing Institute（阿兰·图灵研究所）
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 planets 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 …
Characterization of the Compact Multi-planet System TOI-789: Validation of Three Terrestrial Planets, Dynamical Characterization, and Detection of a Fourth Temperate Candidate
A chemo-dynamical search for planet-candidate hosts of possible extragalactic origin
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台光学天文重点实验室）；School of Science, Hangzhou Dianzi University（杭州电子科技大学理学院）；Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University（北京师范大学天文与前沿科学研究院）；School of Physics and Astronomy, Beijing Normal University（北京师范大学物理与天文学院）
